data_mining_UI_campus_recruitment_kaggle.ipynb

{"cells":[{"cell_type":"markdown","metadata":{"id":"gfEgNx6xxpls"},"source":["# ***Data Mining* pada Data *Campus Recruitment* Kaggle**"]},{"cell_type":"markdown","metadata":{"id":"-DuG-FynyKb0"},"source":["*Mata kuliah Data Mining Universitas Indonesia*"]},{"cell_type":"markdown","metadata":{"id":"jz41t9-zyQZi"},"source":["* Alva Andhika Sa'id\n","* Farhan Alfarizi\n","* M. Ibnu Ridho \n","* M. Ilham Randi "]},{"cell_type":"markdown","metadata":{"id":"EA3Zm-HaphO7"},"source":["Kontribusi kelompok:\n","* Alva: melakukan klasifikasi, membuat ppt klasifikasi\n","* Farhan: melakukan preprocessing data, membuat ppt pengenalan data, menyatukan ppt\n","* Ilham: melakukan visualisasi, membuat ppt visualisasi\n","* Ibnu: melakukan clustering, membuat ppt clustering"]},{"cell_type":"markdown","metadata":{"id":"3-8V5GtSpsFa"},"source":["Presentasi dilakukan bersama dan semua materi dipelajari bersama-sama"]},{"cell_type":"markdown","metadata":{"id":"qel2y80Wxgtj"},"source":["# Import Module"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"n18pxstAwC4X","vscode":{"languageId":"python"}},"outputs":[],"source":["#Import Module\n","import warnings; warnings.simplefilter('ignore')\n","import umap, numpy as np, matplotlib.pyplot as plt, pandas as pd, seaborn as sns\n","import matplotlib.cm as cm\n","from collections import Counter\n","plt.style.use('bmh'); sns.set()\n","import os\n","from sklearn import cluster, datasets\n","from sklearn.metrics import silhouette_score as siluet\n","from sklearn.metrics.cluster import homogeneity_score as purity\n","from sklearn.metrics import normalized_mutual_info_score as NMI \n","from sklearn.preprocessing import MinMaxScaler\n","from sklearn.cluster import KMeans\n","import scipy\n","from scipy import stats\n","from sklearn.preprocessing import StandardScaler\n","\n","sns.set(style=\"ticks\", color_codes=True)\n","plt.style.use('bmh'); sns.set()"]},{"cell_type":"markdown","metadata":{"id":"yrw02Bc4wTj-"},"source":["# Exploratory Data Analysis"]},{"cell_type":"markdown","metadata":{"id":"9ONTM-d_KBDW"},"source":["## Data Preprocessing"]},{"cell_type":"markdown","metadata":{"id":"1ci6yJvim4dJ"},"source":["### Pengenalan Data"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":564},"executionInfo":{"elapsed":3435,"status":"ok","timestamp":1609927153417,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"DlWy5lowwbfX","outputId":"18aad3cf-4650-4cad-cb54-05d95adf331f","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["--2021-01-06 09:59:12--  https://www.dropbox.com/s/4jgeh38nisdsxrb/Placement_Data_Full_Class.csv?dl=0\n","Resolving www.dropbox.com (www.dropbox.com)... 162.125.82.18, 2620:100:6032:18::a27d:5212\n","Connecting to www.dropbox.com (www.dropbox.com)|162.125.82.18|:443... connected.\n","HTTP request sent, awaiting response... 301 Moved Permanently\n","Location: /s/raw/4jgeh38nisdsxrb/Placement_Data_Full_Class.csv [following]\n","--2021-01-06 09:59:12--  https://www.dropbox.com/s/raw/4jgeh38nisdsxrb/Placement_Data_Full_Class.csv\n","Reusing existing connection to www.dropbox.com:443.\n","HTTP request sent, awaiting response... 302 Found\n","Location: https://uc9c12abacc9292d6c78530a0a8c.dl.dropboxusercontent.com/cd/0/inline/BGeJhSif1QMy-gl8fGsugbyXltOrTMk1ZkI8CmlWxbD-M4PPsc4a26AGYfeiAvzZhKgNCWj71qEja0R9STrMosBeIuPCpNs1TMuUDkLTrXCFNzCTzJW4NCKrrOGh3J4MLkk/file# [following]\n","--2021-01-06 09:59:12--  https://uc9c12abacc9292d6c78530a0a8c.dl.dropboxusercontent.com/cd/0/inline/BGeJhSif1QMy-gl8fGsugbyXltOrTMk1ZkI8CmlWxbD-M4PPsc4a26AGYfeiAvzZhKgNCWj71qEja0R9STrMosBeIuPCpNs1TMuUDkLTrXCFNzCTzJW4NCKrrOGh3J4MLkk/file\n","Resolving uc9c12abacc9292d6c78530a0a8c.dl.dropboxusercontent.com (uc9c12abacc9292d6c78530a0a8c.dl.dropboxusercontent.com)... 162.125.82.15, 2620:100:6032:15::a27d:520f\n","Connecting to uc9c12abacc9292d6c78530a0a8c.dl.dropboxusercontent.com (uc9c12abacc9292d6c78530a0a8c.dl.dropboxusercontent.com)|162.125.82.15|:443... connected.\n","HTTP request sent, awaiting response... 200 OK\n","Length: 19712 (19K) [text/plain]\n","Saving to: ‘Placement_Data_Full_Class.csv’\n","\n","Placement_Data_Full 100%[===================>]  19.25K  --.-KB/s    in 0.01s   \n","\n","2021-01-06 09:59:13 (1.28 MB/s) - ‘Placement_Data_Full_Class.csv’ saved [19712/19712]\n","\n"]},{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>sl_no</th>\n","      <th>gender</th>\n","      <th>ssc_p</th>\n","      <th>ssc_b</th>\n","      <th>hsc_p</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_p</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>etest_p</th>\n","      <th>specialisation</th>\n","      <th>mba_p</th>\n","      <th>status</th>\n","      <th>salary</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>M</td>\n","      <td>67.00</td>\n","      <td>Others</td>\n","      <td>91.00</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>58.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>55.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>58.80</td>\n","      <td>Placed</td>\n","      <td>270000.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2</td>\n","      <td>M</td>\n","      <td>79.33</td>\n","      <td>Central</td>\n","      <td>78.33</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>77.48</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>86.5</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>66.28</td>\n","      <td>Placed</td>\n","      <td>200000.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>3</td>\n","      <td>M</td>\n","      <td>65.00</td>\n","      <td>Central</td>\n","      <td>68.00</td>\n","      <td>Central</td>\n","      <td>Arts</td>\n","      <td>64.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>75.0</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>57.80</td>\n","      <td>Placed</td>\n","      <td>250000.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>4</td>\n","      <td>M</td>\n","      <td>56.00</td>\n","      <td>Central</td>\n","      <td>52.00</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>52.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>66.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>59.43</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>5</td>\n","      <td>M</td>\n","      <td>85.80</td>\n","      <td>Central</td>\n","      <td>73.60</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>73.30</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>96.8</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>55.50</td>\n","      <td>Placed</td>\n","      <td>425000.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   sl_no gender  ssc_p    ssc_b  ...  specialisation  mba_p      status    salary\n","0      1      M  67.00   Others  ...          Mkt&HR  58.80      Placed  270000.0\n","1      2      M  79.33  Central  ...         Mkt&Fin  66.28      Placed  200000.0\n","2      3      M  65.00  Central  ...         Mkt&Fin  57.80      Placed  250000.0\n","3      4      M  56.00  Central  ...          Mkt&HR  59.43  Not Placed       NaN\n","4      5      M  85.80  Central  ...         Mkt&Fin  55.50      Placed  425000.0\n","\n","[5 rows x 15 columns]"]},"execution_count":87,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["import shutil\n","import os\n","from pathlib import Path\n","import pandas as pd\n","\n","!wget -O Placement_Data_Full_Class.csv https://www.dropbox.com/s/4jgeh38nisdsxrb/Placement_Data_Full_Class.csv?dl=0\n","df = pd.read_csv('Placement_Data_Full_Class.csv')\n","df.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3429,"status":"ok","timestamp":1609927153419,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"e7zl7MkAmt02","outputId":"5f94a816-dfe6-4b17-ba4f-023065b603fc","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n"]},{"data":{"text/plain":["('Jumlah baris=', 215, 'Jumlah kolom=', 15)"]},"execution_count":88,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["print(type(df)) #Data penelitian terdiri atas 215 baris dan 15 kolom\n","r,c=df.shape\n","\"Jumlah baris=\",r,\"Jumlah kolom=\",c"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3418,"status":"ok","timestamp":1609927153421,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"aQmqmxVHmopt","outputId":"8ff9997b-893c-47eb-9ab5-94079f31695f","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 215 entries, 0 to 214\n","Data columns (total 15 columns):\n"," #   Column          Non-Null Count  Dtype  \n","---  ------          --------------  -----  \n"," 0   sl_no           215 non-null    int64  \n"," 1   gender          215 non-null    object \n"," 2   ssc_p           215 non-null    float64\n"," 3   ssc_b           215 non-null    object \n"," 4   hsc_p           215 non-null    float64\n"," 5   hsc_b           215 non-null    object \n"," 6   hsc_s           215 non-null    object \n"," 7   degree_p        215 non-null    float64\n"," 8   degree_t        215 non-null    object \n"," 9   workex          215 non-null    object \n"," 10  etest_p         215 non-null    float64\n"," 11  specialisation  215 non-null    object \n"," 12  mba_p           215 non-null    float64\n"," 13  status          215 non-null    object \n"," 14  salary          148 non-null    float64\n","dtypes: float64(6), int64(1), object(8)\n","memory usage: 25.3+ KB\n"]}],"source":["df.info()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":297},"executionInfo":{"elapsed":3413,"status":"ok","timestamp":1609927153422,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"82Xw4R_Ywb5t","outputId":"81aa85cc-d7b0-4f15-c55c-42629746cce0","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>sl_no</th>\n","      <th>ssc_p</th>\n","      <th>hsc_p</th>\n","      <th>degree_p</th>\n","      <th>etest_p</th>\n","      <th>mba_p</th>\n","      <th>salary</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>215.000000</td>\n","      <td>215.000000</td>\n","      <td>215.000000</td>\n","      <td>215.000000</td>\n","      <td>215.000000</td>\n","      <td>215.000000</td>\n","      <td>148.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>108.000000</td>\n","      <td>67.303395</td>\n","      <td>66.333163</td>\n","      <td>66.370186</td>\n","      <td>72.100558</td>\n","      <td>62.278186</td>\n","      <td>288655.405405</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>62.209324</td>\n","      <td>10.827205</td>\n","      <td>10.897509</td>\n","      <td>7.358743</td>\n","      <td>13.275956</td>\n","      <td>5.833385</td>\n","      <td>93457.452420</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>1.000000</td>\n","      <td>40.890000</td>\n","      <td>37.000000</td>\n","      <td>50.000000</td>\n","      <td>50.000000</td>\n","      <td>51.210000</td>\n","      <td>200000.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>54.500000</td>\n","      <td>60.600000</td>\n","      <td>60.900000</td>\n","      <td>61.000000</td>\n","      <td>60.000000</td>\n","      <td>57.945000</td>\n","      <td>240000.000000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>108.000000</td>\n","      <td>67.000000</td>\n","      <td>65.000000</td>\n","      <td>66.000000</td>\n","      <td>71.000000</td>\n","      <td>62.000000</td>\n","      <td>265000.000000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>161.500000</td>\n","      <td>75.700000</td>\n","      <td>73.000000</td>\n","      <td>72.000000</td>\n","      <td>83.500000</td>\n","      <td>66.255000</td>\n","      <td>300000.000000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>215.000000</td>\n","      <td>89.400000</td>\n","      <td>97.700000</td>\n","      <td>91.000000</td>\n","      <td>98.000000</td>\n","      <td>77.890000</td>\n","      <td>940000.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["            sl_no       ssc_p  ...       mba_p         salary\n","count  215.000000  215.000000  ...  215.000000     148.000000\n","mean   108.000000   67.303395  ...   62.278186  288655.405405\n","std     62.209324   10.827205  ...    5.833385   93457.452420\n","min      1.000000   40.890000  ...   51.210000  200000.000000\n","25%     54.500000   60.600000  ...   57.945000  240000.000000\n","50%    108.000000   67.000000  ...   62.000000  265000.000000\n","75%    161.500000   75.700000  ...   66.255000  300000.000000\n","max    215.000000   89.400000  ...   77.890000  940000.000000\n","\n","[8 rows x 7 columns]"]},"execution_count":90,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df.describe()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3400,"status":"ok","timestamp":1609927153423,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"7zcyE01Ewb3L","outputId":"b3c3c283-5413-48fd-cdfd-21ce082637f6","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["sl_no               int64\n","gender             object\n","ssc_p             float64\n","ssc_b              object\n","hsc_p             float64\n","hsc_b              object\n","hsc_s              object\n","degree_p          float64\n","degree_t           object\n","workex             object\n","etest_p           float64\n","specialisation     object\n","mba_p             float64\n","status             object\n","salary            float64\n","dtype: object"]},"execution_count":91,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df.dtypes"]},{"cell_type":"markdown","metadata":{"id":"QwH6rN7Tm-U5"},"source":["Berikut adalah penjelasan setiap variabel\n","\n","*   ssc_p = Persentase nilai Secondary Education 10th grade\n","*   ssc_b = Board Secondary Education 10th grade\n","*   hsc_p = Persentase nilai Higher Secondary Edu 12th grade\n","*   hsc_b = Board Higher Secondary Edu 12th grade\n","*   hsc_s = Peminatan saat 12th grade\n","*   degree_p = Persentase Nilai Undergraduate Education\n","*   degree_t = Jurusan Undergraduate Education\n","*   workex = Pengalaman Kerja\n","*   etest_p = Persentase Nilai Employment Test oleh kampus\n","*   specialisation = Jurusan saat Master Business Academy\n","*   mba_p = Persentase Nilai Master Business Academy\n","* salary = Gaji\n","* status = Diterima kerja atau belum\n"]},{"cell_type":"markdown","metadata":{"id":"JiSuembVn4bA"},"source":["### Pengecekan Missing Value"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3393,"status":"ok","timestamp":1609927153424,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"xUNgH2yKwciR","outputId":"2384c751-47e9-4343-f12e-e0d33eb7bb66","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["sl_no              0\n","gender             0\n","ssc_p              0\n","ssc_b              0\n","hsc_p              0\n","hsc_b              0\n","hsc_s              0\n","degree_p           0\n","degree_t           0\n","workex             0\n","etest_p            0\n","specialisation     0\n","mba_p              0\n","status             0\n","salary            67\n","dtype: int64"]},"execution_count":92,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df.isnull().sum()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3387,"status":"ok","timestamp":1609927153425,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"HFFYmWvuyL-Z","outputId":"1322db54-c506-4ba1-a480-f41d315e1cac","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["Placed        148\n","Not Placed     67\n","Name: status, dtype: int64"]},"execution_count":93,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df['status'].value_counts()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"executionInfo":{"elapsed":3340,"status":"ok","timestamp":1609927153426,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"LdtPViHtydfj","outputId":"4b1a1238-ac9c-4f3c-c921-5d5f46d197e1","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>sl_no</th>\n","      <th>gender</th>\n","      <th>ssc_p</th>\n","      <th>ssc_b</th>\n","      <th>hsc_p</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_p</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>etest_p</th>\n","      <th>specialisation</th>\n","      <th>mba_p</th>\n","      <th>status</th>\n","      <th>salary</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>3</th>\n","      <td>4</td>\n","      <td>M</td>\n","      <td>56.0</td>\n","      <td>Central</td>\n","      <td>52.0</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>52.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>66.00</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>59.43</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>6</td>\n","      <td>M</td>\n","      <td>55.0</td>\n","      <td>Others</td>\n","      <td>49.8</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>67.25</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>55.00</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>51.58</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>7</td>\n","      <td>F</td>\n","      <td>46.0</td>\n","      <td>Others</td>\n","      <td>49.2</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>79.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>74.28</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>53.29</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>10</td>\n","      <td>M</td>\n","      <td>58.0</td>\n","      <td>Central</td>\n","      <td>70.0</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>61.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>54.00</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>52.21</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>13</td>\n","      <td>F</td>\n","      <td>47.0</td>\n","      <td>Central</td>\n","      <td>55.0</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>65.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>62.00</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>65.04</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>198</th>\n","      <td>199</td>\n","      <td>F</td>\n","      <td>67.0</td>\n","      <td>Central</td>\n","      <td>70.0</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>65.00</td>\n","      <td>Others</td>\n","      <td>No</td>\n","      <td>88.00</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>71.96</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>201</th>\n","      <td>202</td>\n","      <td>M</td>\n","      <td>54.2</td>\n","      <td>Central</td>\n","      <td>63.0</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>58.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>79.00</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>58.44</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>206</th>\n","      <td>207</td>\n","      <td>M</td>\n","      <td>41.0</td>\n","      <td>Central</td>\n","      <td>42.0</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>60.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>97.00</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>53.39</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>208</th>\n","      <td>209</td>\n","      <td>F</td>\n","      <td>43.0</td>\n","      <td>Central</td>\n","      <td>60.0</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>65.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>92.66</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>62.92</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>214</th>\n","      <td>215</td>\n","      <td>M</td>\n","      <td>62.0</td>\n","      <td>Central</td>\n","      <td>58.0</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>53.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>89.00</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>60.22</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>67 rows × 15 columns</p>\n","</div>"],"text/plain":["     sl_no gender  ssc_p    ssc_b  ...  specialisation  mba_p      status  salary\n","3        4      M   56.0  Central  ...          Mkt&HR  59.43  Not Placed     NaN\n","5        6      M   55.0   Others  ...         Mkt&Fin  51.58  Not Placed     NaN\n","6        7      F   46.0   Others  ...         Mkt&Fin  53.29  Not Placed     NaN\n","9       10      M   58.0  Central  ...         Mkt&Fin  52.21  Not Placed     NaN\n","12      13      F   47.0  Central  ...          Mkt&HR  65.04  Not Placed     NaN\n","..     ...    ...    ...      ...  ...             ...    ...         ...     ...\n","198    199      F   67.0  Central  ...          Mkt&HR  71.96  Not Placed     NaN\n","201    202      M   54.2  Central  ...          Mkt&HR  58.44  Not Placed     NaN\n","206    207      M   41.0  Central  ...         Mkt&Fin  53.39  Not Placed     NaN\n","208    209      F   43.0  Central  ...          Mkt&HR  62.92  Not Placed     NaN\n","214    215      M   62.0  Central  ...          Mkt&HR  60.22  Not Placed     NaN\n","\n","[67 rows x 15 columns]"]},"execution_count":94,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df[df['status']=='Not Placed']"]},{"cell_type":"markdown","metadata":{"id":"qMXLz6XNoFKv"},"source":["terlihat bahwa missing value pada variabel 'salary' adalah untuk mahasiswa - mahasiswa yang belum ditempatkan/diterima kerja di manapun. "]},{"cell_type":"markdown","metadata":{"id":"70V8hkiaoSzB"},"source":["### Pengolahan Data"]},{"cell_type":"markdown","metadata":{"id":"-3XvlfiVogAL"},"source":["Membuang variabel yang tidak dibutuhkan"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"qDQ_RwRwzZM-","vscode":{"languageId":"python"}},"outputs":[],"source":["df.drop('sl_no', axis=1, inplace=True)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":204},"executionInfo":{"elapsed":3305,"status":"ok","timestamp":1609927153427,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"3IfaFWLezmX2","outputId":"a2e996e0-bec2-485c-882f-363eb3167ef4","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>gender</th>\n","      <th>ssc_p</th>\n","      <th>ssc_b</th>\n","      <th>hsc_p</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_p</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>etest_p</th>\n","      <th>specialisation</th>\n","      <th>mba_p</th>\n","      <th>status</th>\n","      <th>salary</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>M</td>\n","      <td>67.00</td>\n","      <td>Others</td>\n","      <td>91.00</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>58.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>55.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>58.80</td>\n","      <td>Placed</td>\n","      <td>270000.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>M</td>\n","      <td>79.33</td>\n","      <td>Central</td>\n","      <td>78.33</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>77.48</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>86.5</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>66.28</td>\n","      <td>Placed</td>\n","      <td>200000.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>M</td>\n","      <td>65.00</td>\n","      <td>Central</td>\n","      <td>68.00</td>\n","      <td>Central</td>\n","      <td>Arts</td>\n","      <td>64.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>75.0</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>57.80</td>\n","      <td>Placed</td>\n","      <td>250000.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>M</td>\n","      <td>56.00</td>\n","      <td>Central</td>\n","      <td>52.00</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>52.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>66.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>59.43</td>\n","      <td>Not Placed</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>M</td>\n","      <td>85.80</td>\n","      <td>Central</td>\n","      <td>73.60</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>73.30</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>96.8</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>55.50</td>\n","      <td>Placed</td>\n","      <td>425000.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  gender  ssc_p    ssc_b  hsc_p  ... specialisation  mba_p      status    salary\n","0      M  67.00   Others  91.00  ...         Mkt&HR  58.80      Placed  270000.0\n","1      M  79.33  Central  78.33  ...        Mkt&Fin  66.28      Placed  200000.0\n","2      M  65.00  Central  68.00  ...        Mkt&Fin  57.80      Placed  250000.0\n","3      M  56.00  Central  52.00  ...         Mkt&HR  59.43  Not Placed       NaN\n","4      M  85.80  Central  73.60  ...        Mkt&Fin  55.50      Placed  425000.0\n","\n","[5 rows x 14 columns]"]},"execution_count":96,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"TRjYp0kvopaP","vscode":{"languageId":"python"}},"outputs":[],"source":["#Mengubah tipe variabel 'object' menjadi 'category'\n","df[\"gender\"] = df[\"gender\"].astype('category')\n","df[\"ssc_b\"] = df[\"ssc_b\"].astype('category')\n","df[\"hsc_b\"] = df[\"hsc_b\"].astype('category')\n","df[\"hsc_s\"] = df[\"hsc_s\"].astype('category')\n","df[\"degree_t\"] = df[\"degree_t\"].astype('category')\n","df[\"workex\"] = df[\"workex\"].astype('category')\n","df[\"specialisation\"] = df[\"specialisation\"].astype('category')\n","df[\"status\"] = df[\"status\"].astype('category')"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":4007,"status":"ok","timestamp":1609927154146,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"5OpJVWOxosHB","outputId":"71f58b79-92d5-4c33-fa6e-9e54dd20c2a4","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["gender            category\n","ssc_p              float64\n","ssc_b             category\n","hsc_p              float64\n","hsc_b             category\n","hsc_s             category\n","degree_p           float64\n","degree_t          category\n","workex            category\n","etest_p            float64\n","specialisation    category\n","mba_p              float64\n","status            category\n","salary             float64\n","dtype: object"]},"execution_count":98,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df.dtypes"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3986,"status":"ok","timestamp":1609927154148,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"yM37hwfKqqt1","outputId":"af3ef1ef-42a4-472c-95b8-4d3bb64d7ec1","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["count       215.000000\n","mean     198702.325581\n","std      154780.926716\n","min           0.000000\n","25%           0.000000\n","50%      240000.000000\n","75%      282500.000000\n","max      940000.000000\n","Name: salary, dtype: float64"]},"execution_count":99,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df['salary'] = df['salary'].fillna(0)\n","df['salary'].describe()"]},{"cell_type":"markdown","metadata":{"id":"jOIR70MomUPo"},"source":["### Memisahkan Variabel Tertentu"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":204},"executionInfo":{"elapsed":3969,"status":"ok","timestamp":1609927154151,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"zhfEu_NsqoPn","outputId":"a9dd1559-8d83-4cc5-b1a2-b357ce179918","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>ssc_p</th>\n","      <th>hsc_p</th>\n","      <th>degree_p</th>\n","      <th>etest_p</th>\n","      <th>mba_p</th>\n","      <th>salary</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>67.00</td>\n","      <td>91.00</td>\n","      <td>58.00</td>\n","      <td>55.0</td>\n","      <td>58.80</td>\n","      <td>270000.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>79.33</td>\n","      <td>78.33</td>\n","      <td>77.48</td>\n","      <td>86.5</td>\n","      <td>66.28</td>\n","      <td>200000.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>65.00</td>\n","      <td>68.00</td>\n","      <td>64.00</td>\n","      <td>75.0</td>\n","      <td>57.80</td>\n","      <td>250000.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>56.00</td>\n","      <td>52.00</td>\n","      <td>52.00</td>\n","      <td>66.0</td>\n","      <td>59.43</td>\n","      <td>0.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>85.80</td>\n","      <td>73.60</td>\n","      <td>73.30</td>\n","      <td>96.8</td>\n","      <td>55.50</td>\n","      <td>425000.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   ssc_p  hsc_p  degree_p  etest_p  mba_p    salary\n","0  67.00  91.00     58.00     55.0  58.80  270000.0\n","1  79.33  78.33     77.48     86.5  66.28  200000.0\n","2  65.00  68.00     64.00     75.0  57.80  250000.0\n","3  56.00  52.00     52.00     66.0  59.43       0.0\n","4  85.80  73.60     73.30     96.8  55.50  425000.0"]},"execution_count":100,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["# Memilih hanya variable numerik\n","df_num = df.select_dtypes(include = ['float64'])\n","df_num.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":204},"executionInfo":{"elapsed":3962,"status":"ok","timestamp":1609927154153,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"ZDfzqx4DmiFL","outputId":"4596e2dd-62dd-4780-f5e3-246facbc9301","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>gender</th>\n","      <th>ssc_b</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>specialisation</th>\n","      <th>status</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>M</td>\n","      <td>Others</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>Placed</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>M</td>\n","      <td>Central</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>Placed</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>M</td>\n","      <td>Central</td>\n","      <td>Central</td>\n","      <td>Arts</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>Placed</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>M</td>\n","      <td>Central</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>Not Placed</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>M</td>\n","      <td>Central</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>Placed</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  gender    ssc_b    hsc_b  ... workex specialisation      status\n","0      M   Others   Others  ...     No         Mkt&HR      Placed\n","1      M  Central   Others  ...    Yes        Mkt&Fin      Placed\n","2      M  Central  Central  ...     No        Mkt&Fin      Placed\n","3      M  Central  Central  ...     No         Mkt&HR  Not Placed\n","4      M  Central  Central  ...     No        Mkt&Fin      Placed\n","\n","[5 rows x 8 columns]"]},"execution_count":101,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["# Memilih hanya variable kategorik\n","df_cat = df.select_dtypes(include = ['category'])\n","df_cat.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3953,"status":"ok","timestamp":1609927154156,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"5qewcRodCPqH","outputId":"2fd0a07c-4130-414f-a06d-0ced73edef03","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["gender\n","\n","M    139\n","F     76\n","Name: gender, dtype: int64\n","\n","\n","ssc_b\n","\n","Central    116\n","Others      99\n","Name: ssc_b, dtype: int64\n","\n","\n","hsc_b\n","\n","Others     131\n","Central     84\n","Name: hsc_b, dtype: int64\n","\n","\n","hsc_s\n","\n","Commerce    113\n","Science      91\n","Arts         11\n","Name: hsc_s, dtype: int64\n","\n","\n","degree_t\n","\n","Comm&Mgmt    145\n","Sci&Tech      59\n","Others        11\n","Name: degree_t, dtype: int64\n","\n","\n","workex\n","\n","No     141\n","Yes     74\n","Name: workex, dtype: int64\n","\n","\n","specialisation\n","\n","Mkt&Fin    120\n","Mkt&HR      95\n","Name: specialisation, dtype: int64\n","\n","\n","status\n","\n","Placed        148\n","Not Placed     67\n","Name: status, dtype: int64\n","\n","\n"]}],"source":["kat = ['gender', 'ssc_b', 'hsc_b', 'hsc_s', 'degree_t', 'workex',\n","       'specialisation', 'status']\n","for i in kat:\n","  print(i +'\\n')\n","  print(df[i].value_counts())\n","  print('\\n')"]},{"cell_type":"markdown","metadata":{"id":"0jrgq6ELrD5v"},"source":["### Membuat Variabel Dummy"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":258},"executionInfo":{"elapsed":3946,"status":"ok","timestamp":1609927154158,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"0DmT9oQiBcCL","outputId":"cc4163d6-9bbe-4b7e-85e8-a4ce84a0420b","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>gender</th>\n","      <th>ssc_p</th>\n","      <th>ssc_b</th>\n","      <th>hsc_p</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_p</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>etest_p</th>\n","      <th>specialisation</th>\n","      <th>mba_p</th>\n","      <th>status</th>\n","      <th>salary</th>\n","      <th>F</th>\n","      <th>M</th>\n","      <th>Central</th>\n","      <th>Others</th>\n","      <th>Central</th>\n","      <th>Others</th>\n","      <th>Arts</th>\n","      <th>Commerce</th>\n","      <th>Science</th>\n","      <th>Comm&amp;Mgmt</th>\n","      <th>Others</th>\n","      <th>Sci&amp;Tech</th>\n","      <th>No</th>\n","      <th>Yes</th>\n","      <th>Mkt&amp;Fin</th>\n","      <th>Mkt&amp;HR</th>\n","      <th>Not Placed</th>\n","      <th>Placed</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>M</td>\n","      <td>67.00</td>\n","      <td>Others</td>\n","      <td>91.00</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>58.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>55.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>58.80</td>\n","      <td>Placed</td>\n","      <td>270000.0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>M</td>\n","      <td>79.33</td>\n","      <td>Central</td>\n","      <td>78.33</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>77.48</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>86.5</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>66.28</td>\n","      <td>Placed</td>\n","      <td>200000.0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>M</td>\n","      <td>65.00</td>\n","      <td>Central</td>\n","      <td>68.00</td>\n","      <td>Central</td>\n","      <td>Arts</td>\n","      <td>64.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>75.0</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>57.80</td>\n","      <td>Placed</td>\n","      <td>250000.0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>M</td>\n","      <td>56.00</td>\n","      <td>Central</td>\n","      <td>52.00</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>52.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>66.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>59.43</td>\n","      <td>Not Placed</td>\n","      <td>0.0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>M</td>\n","      <td>85.80</td>\n","      <td>Central</td>\n","      <td>73.60</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>73.30</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>96.8</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>55.50</td>\n","      <td>Placed</td>\n","      <td>425000.0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  gender  ssc_p    ssc_b  hsc_p  ... Mkt&Fin Mkt&HR  Not Placed Placed\n","0      M  67.00   Others  91.00  ...       0      1           0      1\n","1      M  79.33  Central  78.33  ...       1      0           0      1\n","2      M  65.00  Central  68.00  ...       1      0           0      1\n","3      M  56.00  Central  52.00  ...       0      1           1      0\n","4      M  85.80  Central  73.60  ...       1      0           0      1\n","\n","[5 rows x 32 columns]"]},"execution_count":103,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["for i in kat:\n","  dff = pd.get_dummies(df[i])\n","  df = pd.concat([df, dff], axis = 1)\n","df.head()\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"FU3jeqNfCL2H","vscode":{"languageId":"python"}},"outputs":[],"source":["#Base label 1\n","# Gender : Male\n","# ssc_b : Central\n","# hsc_b : Central\n","# workex : Yes\n","# specialisation : mkt&fin\n","# status: Placed: 1\n","\n","#Base label 0\n","# hsc_s : Arts\n","# degree_t : Others\n","df.drop('Others', axis=1, inplace=True)\n","df.drop('F', axis=1,inplace=True)\n","df.drop('Arts', axis=1, inplace=True)\n","df.drop('No', axis=1, inplace=True)\n","df.drop('Mkt&HR', axis=1, inplace=True)\n","df.drop('Not Placed', axis=1,inplace=True)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":241},"executionInfo":{"elapsed":3916,"status":"ok","timestamp":1609927154159,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"9uOodMWUOnsj","outputId":"53a39633-4d2e-463a-b29c-4c16085445d5","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>gender</th>\n","      <th>ssc_p</th>\n","      <th>ssc_b</th>\n","      <th>hsc_p</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_p</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>etest_p</th>\n","      <th>specialisation</th>\n","      <th>mba_p</th>\n","      <th>status</th>\n","      <th>salary</th>\n","      <th>M</th>\n","      <th>Central</th>\n","      <th>Central</th>\n","      <th>Commerce</th>\n","      <th>Science</th>\n","      <th>Comm&amp;Mgmt</th>\n","      <th>Sci&amp;Tech</th>\n","      <th>Yes</th>\n","      <th>Mkt&amp;Fin</th>\n","      <th>Placed</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>M</td>\n","      <td>67.00</td>\n","      <td>Others</td>\n","      <td>91.00</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>58.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>55.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>58.80</td>\n","      <td>Placed</td>\n","      <td>270000.0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>M</td>\n","      <td>79.33</td>\n","      <td>Central</td>\n","      <td>78.33</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>77.48</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>86.5</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>66.28</td>\n","      <td>Placed</td>\n","      <td>200000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>M</td>\n","      <td>65.00</td>\n","      <td>Central</td>\n","      <td>68.00</td>\n","      <td>Central</td>\n","      <td>Arts</td>\n","      <td>64.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>75.0</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>57.80</td>\n","      <td>Placed</td>\n","      <td>250000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>M</td>\n","      <td>56.00</td>\n","      <td>Central</td>\n","      <td>52.00</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>52.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>66.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>59.43</td>\n","      <td>Not Placed</td>\n","      <td>0.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>M</td>\n","      <td>85.80</td>\n","      <td>Central</td>\n","      <td>73.60</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>73.30</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>96.8</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>55.50</td>\n","      <td>Placed</td>\n","      <td>425000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  gender  ssc_p    ssc_b  hsc_p  ... Sci&Tech Yes  Mkt&Fin Placed\n","0      M  67.00   Others  91.00  ...        1   0        0      1\n","1      M  79.33  Central  78.33  ...        1   1        1      1\n","2      M  65.00  Central  68.00  ...        0   0        1      1\n","3      M  56.00  Central  52.00  ...        1   0        0      0\n","4      M  85.80  Central  73.60  ...        0   0        1      1\n","\n","[5 rows x 24 columns]"]},"execution_count":105,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"9FnMfsCRQOc3","vscode":{"languageId":"python"}},"outputs":[],"source":["df.rename(columns={ df.columns[15]: \"bse\", df.columns[16]:\"bhse\", 'Commerce':'hse_com', 'Science':'hse_sci','Comm&Mgmt':'deg_com', 'Sci&Tech':'deg_sci', 'Yes':'work_ex', 'Mkt&Fin':'master_jurusan', 'Placed':'Target'},inplace=True)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":241},"executionInfo":{"elapsed":3894,"status":"ok","timestamp":1609927154162,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"8UnOqQ_-T7dr","outputId":"4723dd5f-29e5-47c5-eaac-4c76216ac5e3","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>gender</th>\n","      <th>ssc_p</th>\n","      <th>ssc_b</th>\n","      <th>hsc_p</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_p</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>etest_p</th>\n","      <th>specialisation</th>\n","      <th>mba_p</th>\n","      <th>status</th>\n","      <th>salary</th>\n","      <th>M</th>\n","      <th>bhse</th>\n","      <th>bhse</th>\n","      <th>hse_com</th>\n","      <th>hse_sci</th>\n","      <th>deg_com</th>\n","      <th>deg_sci</th>\n","      <th>work_ex</th>\n","      <th>master_jurusan</th>\n","      <th>Target</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>M</td>\n","      <td>67.00</td>\n","      <td>Others</td>\n","      <td>91.00</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>58.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>55.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>58.80</td>\n","      <td>Placed</td>\n","      <td>270000.0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>M</td>\n","      <td>79.33</td>\n","      <td>Central</td>\n","      <td>78.33</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>77.48</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>86.5</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>66.28</td>\n","      <td>Placed</td>\n","      <td>200000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>M</td>\n","      <td>65.00</td>\n","      <td>Central</td>\n","      <td>68.00</td>\n","      <td>Central</td>\n","      <td>Arts</td>\n","      <td>64.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>75.0</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>57.80</td>\n","      <td>Placed</td>\n","      <td>250000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>M</td>\n","      <td>56.00</td>\n","      <td>Central</td>\n","      <td>52.00</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>52.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>66.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>59.43</td>\n","      <td>Not Placed</td>\n","      <td>0.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>M</td>\n","      <td>85.80</td>\n","      <td>Central</td>\n","      <td>73.60</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>73.30</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>96.8</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>55.50</td>\n","      <td>Placed</td>\n","      <td>425000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  gender  ssc_p    ssc_b  hsc_p  ... deg_sci work_ex  master_jurusan Target\n","0      M  67.00   Others  91.00  ...       1       0               0      1\n","1      M  79.33  Central  78.33  ...       1       1               1      1\n","2      M  65.00  Central  68.00  ...       0       0               1      1\n","3      M  56.00  Central  52.00  ...       1       0               0      0\n","4      M  85.80  Central  73.60  ...       0       0               1      1\n","\n","[5 rows x 24 columns]"]},"execution_count":107,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":241},"executionInfo":{"elapsed":3876,"status":"ok","timestamp":1609927154163,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"65wvSYylsTj7","outputId":"f3bfc795-513b-4905-d9d4-df2fb5ab41b7","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>gender</th>\n","      <th>ssc_p</th>\n","      <th>ssc_b</th>\n","      <th>hsc_p</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_p</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>etest_p</th>\n","      <th>specialisation</th>\n","      <th>mba_p</th>\n","      <th>status</th>\n","      <th>salary</th>\n","      <th>M</th>\n","      <th>bse</th>\n","      <th>bhse</th>\n","      <th>hse_com</th>\n","      <th>hse_sci</th>\n","      <th>deg_com</th>\n","      <th>deg_sci</th>\n","      <th>work_ex</th>\n","      <th>master_jurusan</th>\n","      <th>Target</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>M</td>\n","      <td>67.00</td>\n","      <td>Others</td>\n","      <td>91.00</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>58.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>55.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>58.80</td>\n","      <td>Placed</td>\n","      <td>270000.0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>M</td>\n","      <td>79.33</td>\n","      <td>Central</td>\n","      <td>78.33</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>77.48</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>86.5</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>66.28</td>\n","      <td>Placed</td>\n","      <td>200000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>M</td>\n","      <td>65.00</td>\n","      <td>Central</td>\n","      <td>68.00</td>\n","      <td>Central</td>\n","      <td>Arts</td>\n","      <td>64.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>75.0</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>57.80</td>\n","      <td>Placed</td>\n","      <td>250000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>M</td>\n","      <td>56.00</td>\n","      <td>Central</td>\n","      <td>52.00</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>52.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>66.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>59.43</td>\n","      <td>Not Placed</td>\n","      <td>0.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>M</td>\n","      <td>85.80</td>\n","      <td>Central</td>\n","      <td>73.60</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>73.30</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>96.8</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>55.50</td>\n","      <td>Placed</td>\n","      <td>425000.0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  gender  ssc_p    ssc_b  hsc_p  ... deg_sci work_ex  master_jurusan Target\n","0      M  67.00   Others  91.00  ...       1       0               0      1\n","1      M  79.33  Central  78.33  ...       1       1               1      1\n","2      M  65.00  Central  68.00  ...       0       0               1      1\n","3      M  56.00  Central  52.00  ...       1       0               0      0\n","4      M  85.80  Central  73.60  ...       0       0               1      1\n","\n","[5 rows x 24 columns]"]},"execution_count":108,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["df.columns = ['gender', 'ssc_p', 'ssc_b', 'hsc_p', 'hsc_b', 'hsc_s', 'degree_p',\n","       'degree_t', 'workex', 'etest_p', 'specialisation', 'mba_p', 'status',\n","       'salary', 'M', 'bse', 'bhse', 'hse_com', 'hse_sci', 'deg_com',\n","       'deg_sci', 'work_ex', 'master_jurusan', 'Target']\n","df.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":204},"executionInfo":{"elapsed":3867,"status":"ok","timestamp":1609927154166,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"OrWZd45dUBY6","outputId":"ed7e4372-6327-47c4-8bab-bc022e816b2d","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>ssc_p</th>\n","      <th>hsc_p</th>\n","      <th>degree_p</th>\n","      <th>etest_p</th>\n","      <th>mba_p</th>\n","      <th>M</th>\n","      <th>bse</th>\n","      <th>bhse</th>\n","      <th>hse_com</th>\n","      <th>hse_sci</th>\n","      <th>deg_com</th>\n","      <th>deg_sci</th>\n","      <th>work_ex</th>\n","      <th>master_jurusan</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>67.00</td>\n","      <td>91.00</td>\n","      <td>58.00</td>\n","      <td>55.0</td>\n","      <td>58.80</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>79.33</td>\n","      <td>78.33</td>\n","      <td>77.48</td>\n","      <td>86.5</td>\n","      <td>66.28</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>65.00</td>\n","      <td>68.00</td>\n","      <td>64.00</td>\n","      <td>75.0</td>\n","      <td>57.80</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>56.00</td>\n","      <td>52.00</td>\n","      <td>52.00</td>\n","      <td>66.0</td>\n","      <td>59.43</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>85.80</td>\n","      <td>73.60</td>\n","      <td>73.30</td>\n","      <td>96.8</td>\n","      <td>55.50</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   ssc_p  hsc_p  degree_p  etest_p  ...  deg_com  deg_sci  work_ex  master_jurusan\n","0  67.00  91.00     58.00     55.0  ...        0        1        0               0\n","1  79.33  78.33     77.48     86.5  ...        0        1        1               1\n","2  65.00  68.00     64.00     75.0  ...        1        0        0               1\n","3  56.00  52.00     52.00     66.0  ...        0        1        0               0\n","4  85.80  73.60     73.30     96.8  ...        1        0        0               1\n","\n","[5 rows x 14 columns]"]},"execution_count":109,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["X = df.drop({'gender','ssc_b','hsc_b','hsc_s', 'degree_t', 'workex', 'specialisation','status', 'salary','Target'}, axis=1)\n","X.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Wip7rkg_WDrk","vscode":{"languageId":"python"}},"outputs":[],"source":["y = df['Target']"]},{"cell_type":"markdown","metadata":{"id":"W7yYVFVLBZfX"},"source":["## Visualisasi"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":204},"executionInfo":{"elapsed":3841,"status":"ok","timestamp":1609927154169,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"u4wfrpnxOK17","outputId":"6c918248-aab6-4ff8-fc99-359df3e1de8d","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>gender</th>\n","      <th>ssc_p</th>\n","      <th>ssc_b</th>\n","      <th>hsc_p</th>\n","      <th>hsc_b</th>\n","      <th>hsc_s</th>\n","      <th>degree_p</th>\n","      <th>degree_t</th>\n","      <th>workex</th>\n","      <th>etest_p</th>\n","      <th>specialisation</th>\n","      <th>mba_p</th>\n","      <th>status</th>\n","      <th>salary</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>M</td>\n","      <td>67.00</td>\n","      <td>Others</td>\n","      <td>91.00</td>\n","      <td>Others</td>\n","      <td>Commerce</td>\n","      <td>58.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>55.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>58.80</td>\n","      <td>Placed</td>\n","      <td>270000.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>M</td>\n","      <td>79.33</td>\n","      <td>Central</td>\n","      <td>78.33</td>\n","      <td>Others</td>\n","      <td>Science</td>\n","      <td>77.48</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>Yes</td>\n","      <td>86.5</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>66.28</td>\n","      <td>Placed</td>\n","      <td>200000.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>M</td>\n","      <td>65.00</td>\n","      <td>Central</td>\n","      <td>68.00</td>\n","      <td>Central</td>\n","      <td>Arts</td>\n","      <td>64.00</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>75.0</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>57.80</td>\n","      <td>Placed</td>\n","      <td>250000.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>M</td>\n","      <td>56.00</td>\n","      <td>Central</td>\n","      <td>52.00</td>\n","      <td>Central</td>\n","      <td>Science</td>\n","      <td>52.00</td>\n","      <td>Sci&amp;Tech</td>\n","      <td>No</td>\n","      <td>66.0</td>\n","      <td>Mkt&amp;HR</td>\n","      <td>59.43</td>\n","      <td>Not Placed</td>\n","      <td>0.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>M</td>\n","      <td>85.80</td>\n","      <td>Central</td>\n","      <td>73.60</td>\n","      <td>Central</td>\n","      <td>Commerce</td>\n","      <td>73.30</td>\n","      <td>Comm&amp;Mgmt</td>\n","      <td>No</td>\n","      <td>96.8</td>\n","      <td>Mkt&amp;Fin</td>\n","      <td>55.50</td>\n","      <td>Placed</td>\n","      <td>425000.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["  gender  ssc_p    ssc_b  hsc_p  ... specialisation  mba_p      status    salary\n","0      M  67.00   Others  91.00  ...         Mkt&HR  58.80      Placed  270000.0\n","1      M  79.33  Central  78.33  ...        Mkt&Fin  66.28      Placed  200000.0\n","2      M  65.00  Central  68.00  ...        Mkt&Fin  57.80      Placed  250000.0\n","3      M  56.00  Central  52.00  ...         Mkt&HR  59.43  Not Placed       0.0\n","4      M  85.80  Central  73.60  ...        Mkt&Fin  55.50      Placed  425000.0\n","\n","[5 rows x 14 columns]"]},"execution_count":111,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["dff = df[['gender', 'ssc_p', 'ssc_b', 'hsc_p', 'hsc_b', 'hsc_s', 'degree_p',\n","       'degree_t', 'workex', 'etest_p', 'specialisation', 'mba_p', 'status',\n","       'salary']]\n","dff.head()"]},{"cell_type":"markdown","metadata":{"id":"JTxJABcPvseY"},"source":["### Cek Proporsi tiap Variabel Kategorik"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"OUFwbOlbvU4O","vscode":{"languageId":"python"}},"outputs":[],"source":["col1 = ['gender', 'ssc_b', 'hsc_b', 'hsc_s']\n","col2 = ['degree_t', 'workex', 'specialisation', 'status']"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":615},"executionInfo":{"elapsed":4497,"status":"ok","timestamp":1609927154847,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"PEheDzZqu7Am","outputId":"cfe998cb-25eb-4f47-f5bf-d095cc774010","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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size 1440x720 with 4 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(2, 2, figsize=(20, 10))\n","for variable, subplot in zip(col1, ax.flatten()):\n","    sns.countplot(df[variable], ax=subplot)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":615},"executionInfo":{"elapsed":5342,"status":"ok","timestamp":1609927155707,"user":{"displayName":"Muhammad Ilham 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size 1440x720 with 4 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["fig, ax = plt.subplots(2, 2, figsize=(20, 10))\n","for variable, subplot in zip(col2, ax.flatten()):\n","    sns.countplot(df[variable], ax=subplot)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":615},"executionInfo":{"elapsed":5330,"status":"ok","timestamp":1609927155708,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"c7UbomJ9QAIK","outputId":"cc8bed1b-7a57-4dc4-c614-48272567c0b4","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 720x720 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["plt.figure(figsize=(10,10))\n","\n","sns.countplot(x='degree_t',hue='status',data=df)\n","plt.ylabel('Candidates')\n","plt.yticks(range(0,110,10))\n","ax=plt.gca()\n","\n","#Berdasarkan hasil visualisasi terlihat bahwa kandidat yang mendapat pekerjaan maoyritas mengambil jurusan comm&mgmt\n","#Kemungkinan mendapatkan pekerjaan lebih besar untuk kandidat yang mengambil comm&mgmt dan Sci&Tech dibanding jurusan lainnya"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":619},"executionInfo":{"elapsed":5850,"status":"ok","timestamp":1609927156242,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"FiFi3afgY4pC","outputId":"05b19702-fafd-4d86-84af-829f704cc527","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 720x720 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["plt.figure(figsize=(10,10))\n","\n","sns.countplot(x='specialisation',hue='status',data=df)\n","plt.ylabel('Candidates')\n","plt.yticks(range(0,110,10))\n","ax=plt.gca()\n","\n","#Berdasarkan visualisasi terlihat bahwa spesialisasi Mkt&Fin cenderung memiliki kemungkinan mendapatkan kerja lebih besar dibanding spesialisasi Mkt&HR"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":382},"executionInfo":{"elapsed":6546,"status":"ok","timestamp":1609927156955,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"LdKYIm5aqPzP","outputId":"27163a63-5eeb-4136-f538-e2dae953277b","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 451.175x360 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p= sns.catplot(x=\"degree_t\", y=\"salary\", hue=\"specialisation\", kind=\"swarm\", data=dff)\n","\n","#Berdasarkan hasil visualisasi dapat dilihat bahwa terdapat 2 outlier di jurusan comm&mgmt dengan spesialisasi Mkt&Fin\n","#Outlier juga ditemukan di jurusan sci&Tech dengan spesialisasi Mkt&Fin\n","#Secara keseluruhan terlihat tidak terdapat perbedaan siginifkan pada gaji antar kedua spesialisasi di ketiga jurusan \n","#Terlihat bahwa sepsialisasi Mkt&Fin memiliki beberapa outlier yang membuat gaji pada Mkt&Fin terkesan lebih tinggi"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":382},"executionInfo":{"elapsed":7797,"status":"ok","timestamp":1609927158215,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"moKBKDz0FGir","outputId":"3f568bf1-aaab-4504-acd4-888893d0b7d3","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 458.975x360 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p= sns.catplot(x=\"degree_t\", y=\"ssc_p\", hue=\"status\", kind=\"swarm\", data=dff)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":382},"executionInfo":{"elapsed":2009,"status":"ok","timestamp":1609927253589,"user":{"displayName":"Muhammad Ilham 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","text/plain":["<Figure size 458.975x360 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p= sns.catplot(x=\"degree_t\", y=\"hsc_p\", hue=\"status\", kind=\"swarm\", data=dff)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":382},"executionInfo":{"elapsed":7783,"status":"ok","timestamp":1609927158216,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"w2Qedn2TFqtJ","outputId":"63a557d8-bfbf-4bb8-dc9b-acd733f13203","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 458.975x360 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p= sns.catplot(x=\"degree_t\", y=\"mba_p\", hue=\"status\", kind=\"swarm\", data=dff)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":382},"executionInfo":{"elapsed":8782,"status":"ok","timestamp":1609927159231,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"_9o2MKxvWzEC","outputId":"7d92e3eb-ce55-44f4-8c34-dee5f5f87cb9","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 458.975x360 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p= sns.catplot(x=\"degree_t\", y=\"etest_p\", hue=\"status\", kind=\"swarm\", data=dff)\n","\n","#Berdasarkan visualisasi terlihat tidak ada perbedaan kemungkinan penerimaan kerja pada ketiga jurusan berdasarkan nilai Employment Test dari kampus\n","#Maka  dapat dikatakan nilai Employment Test tidak siginifikan untuk penentuan status penempatan kerja"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":382},"executionInfo":{"elapsed":8766,"status":"ok","timestamp":1609927159232,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"5L7w7zmpviI5","outputId":"c04be917-fa28-4966-c9b7-512eac796f54","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 458.975x360 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p= sns.catplot(x=\"degree_t\", y=\"degree_p\", hue=\"status\", kind=\"swarm\", data=dff)\n","\n","#Berdasarkan hasil visualisasi dapat dikatakan bahwa mahasiswa yg memiliki degree_p dibawah 55 cenderung tidak mendapat pekerjaan\n","#Dapat dilihat juga bahwa semakin tinggi nilai degree_p maka cenderung semakin besar kemungkinan seseorang mendapatkan pekerjaan\n","#Terdapat outlier di jurusan sci&Tech dan jurusan lain dimana ada mahasiswa yg memiliki degree_p sangat tinggi"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":382},"executionInfo":{"elapsed":1884,"status":"ok","timestamp":1609928087405,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"SSrrKqcVwelO","outputId":"742c07b7-7578-4001-e24c-6b97d56eab28","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 458.975x360 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p= sns.catplot(x=\"workex\", y=\"degree_p\", hue=\"status\", kind=\"swarm\", data=dff)\n","\n","#Berdasarkan hasil visualisasi dapat dikatakan bahwa orang yang memiliki nilai degree_p diatas rata2 (66,37) memiliki peluang mendapat kerja lebih tinggi walaupun tidak memiliki pengalaman bekerja\n","#Mahasiswa yang memiliki pengalaman kerja cenderung berpeluang lebih besar untuk mendapat pekerjaan"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":382},"executionInfo":{"elapsed":1858,"status":"ok","timestamp":1609928276000,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"FiKh7HuXMXip","outputId":"e815cc16-cba1-4cc2-c81a-d49ca0867193","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 458.975x360 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p= sns.catplot(x=\"workex\", y=\"ssc_p\", hue=\"status\", kind=\"swarm\", data=dff)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":598},"executionInfo":{"elapsed":10383,"status":"ok","timestamp":1609927160873,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"qs67tCT3werQ","outputId":"4ef58dbf-cda4-4c61-bca0-dc5193acfbdf","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 864x720 with 2 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["corr = df_num.corr()\n","plt.figure(figsize=(12, 10))\n","sns.heatmap(corr, cbar=True, annot=True, annot_kws={\"size\": 14}, square=True);\n"]},{"cell_type":"markdown","metadata":{"id":"9YtO_49jszhv"},"source":["## Clustering"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"3pWr57rfwewq","vscode":{"languageId":"python"}},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","from sklearn.cluster import KMeans\n","from sklearn.preprocessing import MinMaxScaler"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":10356,"status":"ok","timestamp":1609927160875,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"AO-eOi4f5uST","outputId":"b274ec16-1a94-4cb7-becf-7795734004f2","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["[[0.53823954 0.88962109 0.19512195 0.10416667 0.28448276 0.28723404]\n"," [0.79241394 0.68088962 0.6702439  0.76041667 0.56484258 0.21276596]\n"," [0.49701093 0.5107084  0.34146341 0.52083333 0.2470015  0.26595745]\n"," ...\n"," [0.53823954 0.49423394 0.56097561 0.1875     0.69377811 0.31382979]\n"," [0.68253968 0.47775947 0.19512195 0.41666667 0.33808096 0.21702128]\n"," [0.43516801 0.34596376 0.07317073 0.8125     0.33770615 0.        ]]\n"]}],"source":["scaler = MinMaxScaler()\n","x_scaled = scaler.fit_transform(df_num)\n","print (x_scaled)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":386},"executionInfo":{"elapsed":11714,"status":"ok","timestamp":1609927162249,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"a36J6CeaZX3W","outputId":"a275e17d-77b4-4b89-f3cd-3e3fef1b195b","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["Text(0.5, 1.0, 'Elbow curve')"]},"execution_count":126,"metadata":{"tags":[]},"output_type":"execute_result"},{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfIAAAFgCAYAAABAP/uYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3deXhUhb3/8fdMNrLv+06AEJYYtkR2AdlkFfRKUfvrrUpbvMotIqA+omDVhlrUKgq01ra3FLWyI6jQILvsCAFEBJKQhRBCWBLCksz8/kCnUsAkMMnJTD6v5/F5mMmcM58vwXxyljnHZLVarYiIiIhDMhsdQERERG6dilxERMSBqchFREQcmIpcRETEganIRUREHJiKXERExIGpyEUc1KJFi/jJT35ie5ycnExubq6BiUTECK5GBxCRm+vbty+nTp3CxcXF9ty9997LtGnTDEwlIo2JilykkZszZw7dunUzOka9qaqqwtVVP4pEbpV2rYs4kXXr1tGvXz8yMjLIzMzEYrEAYLFYeOedd+jTpw9du3Zl8uTJnD9/HoApU6bw5z//GYDi4mKSk5OZP38+AHl5eaSnp9vW858++ugjBg8eTIcOHbjnnnvYv38/cP1u/qlTp/L6668DsHXrVnr16sW8efPo3r07zzzzDIMHD2bt2rW211dVVXHnnXfa1rdnzx7GjBlD586dGT58OFu3brXnX5uIQ1ORiziR1atXs3DhQhYvXkxWVhYLFy4Erh5PX7x4MX/7299Ys2YNFy5cYMaMGQB06dKFbdu2AbBt2zZiY2PZvn277XGnTp0wm6//UbFq1SreeustMjMz2bVrF++++y4BAQG1ynnq1CnOnj3L2rVreemllxgyZAgrVqywfX3jxo0EBgbStm1biouL+cUvfsGvfvUrtm3bxpQpU3jyySc5ffr0bf1diTgLFblII/f444/TuXNn238fffTRTV/72GOPERAQQFRUFD/96U9t5bh8+XJ+9rOfERsbi7e3NxMnTmTlypVUVVWRnp7Ozp07sVgsbN++nUcffZRdu3YBsH37dtLT02/4Xh9//DGPPvooqampmEwm4uPjiY6OrtVMZrOZJ598End3d5o1a8awYcPIysqisrLSlnfIkCEALF26lF69etG7d2/MZjPdu3enXbt2rFu3rtZ/hyLOTAemRBq52bNn1/oYeWRkpO3P0dHRnDx5EoCTJ09eU7LR0dFUVVVRWlpKXFwcnp6eHDx4kJ07d/L444/z8ccfc/ToUbZv387DDz98w/cqKioiLi7ulmYKDAzEw8PD9jg+Pp6kpCTWrl1Lnz59yMrKYsmSJQAUFhby6aefXrfrPSMj45beW8TZqMhFnEhRUREtW7YErhZgWFgYAGFhYRQUFNheV1hYiKurK8HBwcDV3eufffYZV65cITw8nC5durBkyRLOnj1LSkrKDd8rMjKSvLy8G37N09PTtnUNUFJSQnh4uO2xyWS6bpmhQ4eyYsUKLBYLLVq0ID4+3vY+I0aM4De/+U1d/ipEmgztWhdxIu+99x5nz56lqKiIv/3tb9xzzz3A1ZL861//yvHjx6moqOD1119n8ODBtrPF09PT+fvf/07nzp0ByMjI4O9//zudOnW65qNvP3Tffffx5z//mezsbKxWK7m5ubZfFlq3bs2KFSuorq5m/fr1tmPuP+aee+5h06ZNLFiwgKFDh9qeHz58OGvXrmXDhg1UV1dz6dIltm7dyokTJ27r70rEWWiLXKSR++Uvf3lNmXbr1o3Zs2ff8LX9+vVj1KhRlJeXc++993LfffcBMHr0aIqLi3nooYe4dOkSPXr04Pnnn7ct16VLFyoqKujSpQsAnTp14uLFi7Ziv5HBgwdz5swZnnrqKduu+5kzZxIdHc1zzz3H1KlTmT9/PnfffTd33313jXOGhYWRlpbG9u3beeONN2zPR0ZG8s477/C73/2Op556CrPZTGpqKi+++GKN6xRpCkxWq9VqdAgRERG5Ndq1LiIi4sBU5CIiIg5MRS4iIuLAVOQiIiIOTEUuIiLiwFTkIiIiDqxOnyN/++23eeutt1i+fDmtWrViz549TJs2jUuXLhEdHc3vfvc725WifqiyspJnnnmG/fv34+LiwpQpU+jTp89tBS8rq8Bisc8n54KDfSgtLbfLuhozzelcNKdz0ZzOxZ5zms0mAgO9b/r1Whf5/v372bNnj+16zRaLhaeffppXX32Vzp0788477/Daa6/x6quvXrfse++9h4+PD6tXryYnJ4cHH3yQzz//HG/vmwericVitVuRf7++pkBzOhfN6Vw0p3NpqDlrtWv98uXLzJgx45orKWVnZ+Ph4WG78tOYMWP49NNPb7j8qlWreOCBBwBISEigXbt2rF+//jaji4iISK2K/M0332T48OHExMTYnisqKiIqKsr2OCgoCIvFwpkzZ65bvrCw8Jo7L0VGRuo6ySIiInZQ46713bt3k52dzaRJkxoiT60FB/vYdX2hob52XV9jpTmdi+Z0LprTuTTUnDUW+fbt2zly5Aj9+vUD4MSJEzzyyCM8/PDDFBYW2l53+vRpzGYzAQEB160jKiqKgoICgoKCgKtb87d7L+HS0nK7HX8IDfWlpOS8XdbVmGlO56I5nYvmdC72nNNsNv3oxmuNu9bHjRvHxo0bycrKIisri4iICN577z0effRRLl68yI4dOwD44IMPGDRo0A3XMWjQID788EMAcnJy2LdvHz179ryVeUREROQHbvlz5GazmZkzZzJ9+nQGDBjA9u3beeqpp2xfHzFiBMXFxQA88sgjnDt3jv79+/OLX/yCGTNm4ONj313jIiIiTZHD3sZUu9brTnM6F83pXDSnc2lUu9ZFRESk8VKRi4iIOLAmX+TFpy9QXnnF6BgiIiK3pE7XWndGf/rkAM083Jh4fyomk8noOCIiInXS5LfIu7WNYP/RUvYdPW10FBERkTpr8kXe844owoO8WLT+CBbHPIFfRESasCZf5K4uZh4c1Jq84nJ2fH3S6DgiIiJ10uSLHKBXhxiiQ7xZvOEY1RaL0XFERERqTUUOuJhN3NurOcWnL7B5n+7KJiIijkNF/p0OLUNIjPRj6aZjXKmqNjqOiIhIrajIv2MymRjduzmnz13ii92FNS8gIiLSCKjIf6BNQhAp8YGs2JLDxctVRscRERGpkYr8P4zq3ZzzF66wevtxo6OIiIjUSEX+H5Ki/OnQMoRPt+Xp0q0iItLoqchv4N5ezbl4qZpVW3ONjiIiIvKjVOQ3EBPqw51tw/nXjnzOlF8yOo6IiMhNqchvYkSPRKotVpZvzjE6ioiIyE2pyG8iLNCLXndEsX5PISfPVBodR0RE5IZU5D9iaLcEzGYTSzccMzqKiIjIDanIf0Sgrwf9OsXw5f4TFJSUGx1HRETkOiryGtxzZzzNPFxYtP6o0VFERESuoyKvgY+nGwPT49h9+BRHC88ZHUdEROQaKvJa6N85Fl8vNxatP2J0FBERkWuoyGvB08OVIV0TOJBTxsGc00bHERERsVGR11KfDlEE+nqwcP1RrFar0XFEREQAFXmtubm6MKJHIkcLz7Hn21NGxxEREQHAtTYvGj9+PPn5+ZjNZry8vHj++efx9fXl8ccft73m/PnzlJeXs23btuuWf+utt/jHP/5BWFgYAB07duSFF16w0wgNp3v7CFZ9mcui9Ue5IykEs9lkdCQREWnialXkmZmZ+Pr6ArBmzRqeffZZFi9ezNKlS22vefnll6murr7pOkaOHMmUKVNuM66xXMxm7u3VnDlL97P1YDFd20YYHUlERJq4Wu1a/77EAcrLyzGZrt0SvXz5MsuXL2f06NH2TdcIdW4dRlyYD0s2HKWq2mJ0HBERaeJqtUUO8Nxzz7Fp0yasVit/+tOfrvlaVlYW4eHhtG3b9qbLf/LJJ2zcuJHQ0FCeeOIJOnTocOupDWQ2mRjVuzlv/HMvG/YW0adDtNGRRESkCTNZ63gK9pIlS/jkk0/44x//aHvuscceo2fPnvz0pz+94TIlJSUEBATg5ubGpk2bmDRpEitXriQwMPD20hvEarUy5e2NFJ+uYN6z/fFwczE6koiINFF1LnKA1NRU1q1bR2BgIMXFxQwcOJC1a9fWuphHjRrF1KlTSU9Pr3Pg75WWlmOx2OdjYKGhvpSUnK/TMt8cP8Nv5+/i/j5JDM6It0uO+nYrczoizelcNKdz0Zx1ZzabCA72ufnXa1pBRUUFRUVFtsdZWVn4+/sTEBAAwOLFi+ndu/ePlnhxcbHtzwcPHqSgoIDExMRaDdBYtYoNoF3zIFZuyeXCxSqj44iISBNV4zHyyspKJkyYQGVlJWazGX9/f+bMmWM74W3x4sU899xz1y332GOP8eSTT9K+fXtmzZrF/v37MZvNuLm5MXPmTEJDQ+0/TQMb3SuJ6X/Zzufb8xjZs7nRcUREpAm6pV3rjYHRu9a/986SbPYdLSXzl13x83K3S576ol1azkVzOhfN6Vwa1a51+XH39kzk8pVqVm7JNTqKiIg0QSry2xQZ7E33dpFk7Srg9LmLRscREZEmRkVuB8N7JABWlm06ZnQUERFpYlTkdhDi78ldadFs3HuCE6cvGB1HRESaEBW5nQzploCbq5klG44aHUVERJoQFbmd+Hu7079LDNsOniSv2PnPyBQRkcZBRW5Hg9Lj8G7myqL12ioXEZGGoSK3I69mbgy+M569R0o5nH/G6DgiItIEqMjtrF/HGPy93Vn4xREc9Fo7IiLiQFTkdubh7sLQbgl8k3+W/cdOGx1HREScnIq8HvROiyLEvxkL1x3Foq1yERGpRyryeuDqYmZEj0Ryi8+z61CJ0XFERMSJqcjrSde2EUSFeLN4w1GqLRaj44iIiJNSkdcTs9nEvT2bU1R6gc3ZJ4yOIyIiTkpFXo86tgohIcKXZRuPcaVKW+UiImJ/KvJ6ZDKZGN07idJzl1i3p8DoOCIi4oRU5PWsTUIgreMCWLE5h4uXq4yOIyIiTkZFXs9MJhOjeidx7sIV1uzINzqOiIg4GRV5A2gR7U9aixBWbc2jvPKK0XFERMSJqMgbyL29mnPxUhWfbs0zOoqIiDgRFXkDiQ3zIaNNOGt2HOds+SWj44iIiJNQkTegET0TqbZYWb45x+goIiLiJFTkDSg80IueqZGs21NIyZlKo+OIiIgTUJE3sGHdEzGbTSzbeMzoKCIi4gRU5A0s0NeDfh1j2Lz/BAWnKoyOIyIiDk5FboDBd8bh4ebCkvVHjY4iIiIOzrU2Lxo/fjz5+fmYzWa8vLx4/vnnSUlJoW/fvri7u+Ph4QHApEmT6Nmz53XLV1ZW8swzz7B//35cXFyYMmUKffr0se8kDsTXy52B6XEs3XiMY0XnSIz0MzqSiIg4qFoVeWZmJr6+vgCsWbOGZ599lsWLFwPwhz/8gVatWv3o8u+99x4+Pj6sXr2anJwcHnzwQT7//HO8vb1vM77jGtAlln/tzGfRuiM8NaaD0XFERMRB1WrX+vclDlBeXo7JZKrTm6xatYoHHngAgISEBNq1a8f69evrtA5n4+nhypCu8ezPKeNgbpnRcURExEHVaosc4LnnnmPTpk1YrVb+9Kc/2Z6fNGkSVquVTp06MXHiRPz8rt9NXFhYSHR0tO1xZGQkJ07c3j26g4N9bmv5/xQa6lvzi+zs/gGtWbMzn2Wbc+jZKbbOvyDdCiPmNILmdC6a07loTvuqdZG//PLLACxZsoSZM2fyxz/+kfnz5xMZGcnly5d5+eWXmTFjBq+99lq9hf2h0tJyLBarXdYVGupLScl5u6yrroZ2jeevnx5izZYc0lqG1Ot7GTlnQ9KczkVzOhfNWXdms+lHN17rfNb6yJEj2bp1K2VlZURGRgLg7u7O2LFj2bVr1w2XiYqKoqDg3/fjLioqIiIioq5v7ZS6t48kLNCTReuPYLHa5xcTERFpOmos8oqKCoqKimyPs7Ky8Pf3x8PDg/Pnr/62YbVaWblyJSkpKTdcx6BBg/jwww8ByMnJYd++fTc8u70pcnUxM7JnIvklFWw7UGx0HBERcTA17lqvrKxkwoQJVFZWYjab8ff3Z86cOZSWlvLEE09QXV2NxWIhKSmJF154wbbciBEjmDdvHuHh4TzyyCNMnTqV/v37YzabmTFjBj4+9j3G7cjSU8JZuSWPJRuO0bl1GK4u+ni/iIjUjslqdcz9uc5yjPx7e749xR8+3stPByVzV1p0zQvcgsYwZ0PQnM5FczoXzVl3dj9GLvXjjqRgkqL9WLbxGJevVBsdR0REHISKvJEwmUzc1zuJM+WXydpVUPMCIiIiqMgbleS4QNomBrHyy1wqL1UZHUdERByAiryRGd27OeWVV/hsW57RUURExAGoyBuZhAg/OiWH8tn245y/cNnoOCIi0sipyBuhe3s25/KValZ+mWt0FBERaeRU5I1QVIg33dpF8K+dBZw+d9HoOCIi0oipyBupEd0TsVqtLN+cY3QUERFpxFTkjVRIgCd3pUWz4asiik9fMDqOiIg0UiryRmxot3hcXU0s2XjM6CgiItJIqcgbMX8fD/p3jmXrgWLyip3/koYiIlJ3KvJGblBGHF4erixef9ToKCIi0gipyBs572ZuDL4zjq+OlPJt/lmj44iISCOjIncAd3eKxc/LjYXrjuCgN6sTEZF6oiJ3AB7uLgztlsCh42fYn3Pa6DgiItKIqMgdRO+0aIL9mrFw3VFtlYuIiI2K3EG4uZoZ0SOR3BPn2fVNidFxRESkkVCRO5Bu7SKIDPZi0fqjWCzaKhcRERW5QzGbTdzbszlFpRfYsv+E0XFERKQRUJE7mE7JocRH+LJkwzGuVFmMjiMiIgZTkTsYk8nE6N7NKT13kfVfFRodR0REDKYid0BtE4JIjg1g+eYcLl2uNjqOiIgYSEXugK5ulSdxruIya3YeNzqOiIgYSEXuoFrE+HNHUjCrvsyj4uIVo+OIiIhBVOQO7N5ezblwqYpPt+YZHUVERAziWpsXjR8/nvz8fMxmM15eXjz//PNEREQwefJk8vLycHd3Jz4+nhkzZhAUFHTd8lOnTmXz5s0EBgYCMGjQIH71q1/Zd5ImKC7cl/SUMFbvOM7dnWLw9/EwOpKIiDSwWhV5ZmYmvr6+AKxZs4Znn32W999/n0cffZSMjAzba1577TVeeeWVG65j3LhxPPTQQ3aKLd+7t2dzdnxdwootuTzYv5XRcUREpIHVatf69yUOUF5ejslkIiAgwFbiAGlpaRQW6uNQDS08yIseqZF8sbuAU2crjY4jIiINrNbHyJ977jnuuusuXn/9dTIzM6/5msViYcGCBfTt2/emy7///vsMGzaM8ePHc+TIkVtPLNcZ3j0Bk8nE0o3HjI4iIiINzGSt4620lixZwieffMIf//hH23PTp0+nuLiYt99+G7P5+t8NiouLCQ0NxWw2s2TJEt58803WrFmDi4vL7U8gALy3LJtl64/w9tN9iQ33rXkBERFxCnUucoDU1FTWrVtHYGAgmZmZHDp0iDlz5uDu7l6r5TMyMli0aBHR0dF1Dvy90tJyu904JDTUl5KS83ZZl1HOXbjMlDlbaJcYxOP3tr/ha5xhztrQnM5FczoXzVl3ZrOJ4GCfm3+9phVUVFRQVFRke5yVlYW/vz8BAQHMmjWL7OxsZs+e/aMlXlxcbPvzhg0bMJvNhIeH13YGqQU/L3cGdoll56ESjhWdMzqOiIg0kBrPWq+srGTChAlUVlZiNpvx9/dnzpw5fPvtt8ydO5eEhATGjBkDQExMDLNnzwZgxIgRzJs3j/DwcKZMmUJpaSkmkwkfHx/effddXF1rdcK81MHA9Dj+tTOfxeuPMvGBNKPjiIhIA6ixTUNCQvjoo49u+LVDhw7ddLmlS5fa/vyXv/yl7smkzjw9XBnSNYGP1n7LobwykuMCjY4kIiL1TFd2czJ9O0YT4OPOwnVHuYXTH0RExMGoyJ2Mu5sLw7sn8m3BWfYeKTU6joiI1DMVuRPqkRpJWIAni9YfxaKtchERp6Yid0KuLmZG9kzk+Mlyth88aXQcERGpRypyJ5XeJpyYUG8WbzhKVbXF6DgiIlJPVOROymwycW+v5pwsq2TTvqKaFxAREYekIndiaS1CSIryY9mmHK5UVRsdR0RE6oGK3ImZTCZG9U6i7PwlsnYVGB1HRETqgYrcyaXEB9ImIZBPtuRy4eIVo+OIiIidqcibgNG9kyivvMJfPzmgi8SIiDgZFXkTkBjpR//OsazcnMM/1hxWmYuIOBHduaSJGNOvBV5e7ixdf4SqagsPD0zGbDIZHUtERG6TiryJMJlMPDK8LVVXqvhkSy5Xqiz89z2tcTFrp4yIiCNTkTchJpOJ0b2TcHc1s3jDMa5UWXhsWBtcXVTmIiKOSkXeBA3rnoibqwsfrf2WqmoLvxzRDjdXlbmIiCPST+8malBGHA/2b8Xuw6d4e9E+Ll/RBWNERByRirwJ69cphv83KJnso6W8+fFeLl1WmYuIOBoVeRPXOy2aR4am8HVeGbM+2kPlpSqjI4mISB2oyIVu7SL5xfC2HCk4x+8/3KMrwImIOBAVuQCQnhLO+HvbkXviPDMX7Ob8hctGRxIRkVpQkYtNx1ahPDE6laLSC8xcsJuzFSpzEZHGTkUu10hNCuZ/70ul5EwlmfN3UXb+ktGRRETkR6jI5TopCUFM/K80zpRf4rfzd3LqbKXRkURE5CZU5HJDrWIDeGpMGhWVVWTO30Vx2QWjI4mIyA2oyOWmkqL8efonHbh0xcJv5++iqLTC6EgiIvIfVOTyo+IjfJk8tgNWi5XM+bvIP1ludCQREfmBWhX5+PHjGT58OCNHjmTs2LEcPHgQgGPHjvHAAw8wcOBAHnjgAXJycm64fHV1NdOnT+fuu++mf//+/POf/7TbAFL/YkJ9mPJgR8xmE5n/2EXuifNGRxIRke/UqsgzMzNZtmwZS5Ys4ec//znPPvssAC+88AJjx47ls88+Y+zYsUybNu2Gyy9fvpy8vDw+//xzPvzwQ9566y3y8/PtN4XUu8hgb6Y+2JFm7i7MXLCbIwVnjY4kIiLUssh9fX1tfy4vL8dkMlFaWsqBAwcYOnQoAEOHDuXAgQOcPn36uuVXrlzJ/fffj9lsJigoiLvvvptPP/3UTiNIQwkL9GLqg53w9XTjtQ/38M3xM0ZHEhFp8mp9jPy5557jrrvu4vXXXyczM5OioiLCw8NxcXEBwMXFhbCwMIqKiq5btqioiKioKNvjyMhITpw4YYf40tCC/Zsx5cGOBPl6MOujPRzIuf4XNxERaTi1vh/5yy+/DMCSJUuYOXMmEyZMqLdQtREc7GPX9YWG+tb8IidgjzlDQ33JfKIn0+Zu4c2P9/Lsz9LpnBJuh3T2o++nc9GczkVz2leti/x7I0eOZNq0aURERFBcXEx1dTUuLi5UV1dz8uRJIiMjr1smMjKSwsJCUlNTgeu30G9FaWk5Fov1ttbxvdBQX0pKnP8ELnvPOfG/7uD3H+zhN3/eyi9HtKNTcqjd1n079P10LprTuWjOujObTT+68VrjrvWKioprdpdnZWXh7+9PcHAwKSkprFixAoAVK1aQkpJCUFDQdesYNGgQ//znP7FYLJw+fZo1a9YwcODAW5lHGhEfTzee/kkaCRG+vLskm20Hi42OJCLS5NS4RV5ZWcmECROorKzEbDbj7+/PnDlzMJlMvPjii0ydOpV33nkHPz8/MjMzbcs99thjPPnkk7Rv354RI0bw1VdfMWDAAAAef/xxYmNj628qaTBezdyY+EAab/7zK+Yu28+VKgvd21+/V0ZEROqHyWq12mf/dAPTrvW6q885L12u5q1FezmQU8ZPByVzV1p0vbxPbej76Vw0p3PRnHV327vWRWrDw92FCfelkpoUzN8+PcTqHceNjiQi0iSoyMVu3Fxd+J9R7enYKpQFaw6z6stcoyOJiDg9FbnYlauLmV+OaEt6Shj//OIIyzYew0GP3oiIOIQ6f/xMpCauLmbGDWuLm4uZJRuPcbnKwujezTGZTEZHExFxOipyqRdms4n/HpKCm6uZlV/mcqXKwph+LVTmIiJ2piKXemM2mXh4YDKurmZW7zjOlWoLDw1ohVllLiJiNypyqVcmk4mf9GuJm6uZVV/mcaWqmv8enILZrDIXEbEHFbnUO5PJxH29k3B3dWHpxmNUVVt5ZEgKri4611JE5HapyKVBmEwmRvRIxNXFxMJ1R6mqsvCLEW1V5iIit0k/RaVBDemawJh+Ldn5TQlvL9rHlapqoyOJiDg0Fbk0uAFdYnl4YDJ7j5Tyh4/3cumKylxE5FapyMUQfTpE8/N7UjiQW8brH31F5aUqoyOJiDgkFbkYpkdqJI8Na8O3+WeZ9eEeLly8YnQkERGHoyIXQ93ZJoJfjWxLzonz/O6DPZRXqsxFROpCRS6G65Qcxv+Mak9BSQUz/7GLcxWXjY4kIuIwVOTSKNzRIoQJ96dysqySzH/souz8JaMjiYg4BBW5NBptE4L49X/dwenzl8j8xy5Kz140OpKISKOnIpdGJTkukKceSOP8hcv8dv4uTp6pNDqSiEijpiKXRqdFtD9P/6QDFy9XkTl/F0WlFUZHEhFptFTk0iglRPgxeWxHqqotZP5jNwUl5UZHEhFplFTk0mjFhvkwZWxHTCbI/Mdu8orPGx1JRKTRUZFLoxYV4s3UBzvi7mZm5j92c7TwnNGRREQaFRW5NHrhgV5MHdsRb09XXvtgN98cP2N0JBGRRkNFLg4hJMCTKWM74u/jwayP9nAw57TRkUREGgUVuTiMIL9mTB3bgVB/T974eC/7jpYaHUlExHAqcnEo/j4eTB7bgcggL95auJfd35QYHUlExFCuNb2grKyMyZMnk5eXh7u7O/Hx8cyYMYOcnBymT59ue11paSmhoaEsXrz4unVMnTqVzZs3ExgYCMCgQYP41a9+ZccxpCnx9XLn6bEdmPXhHt5Zks244W3p0jrM6FgiIoaoschNJhOPPvooGRkZAGRmZvLaa6/xyiuvsHTpUtvrxo8fT6dOnW66nnHjxvHQQw/ZIbIIeDdzY9KYDrz+z6+YszSbqg9xoowAACAASURBVKo2dG0XYXQsEZEGV+Ou9YCAAFuJA6SlpVFYWHjNa0pLS9m0aRMjRoywf0KRm/D0cGXif91BcmwAf1pxgPVfFda8kIiIk6lxi/yHLBYLCxYsoG/fvtc8v2TJErp3705ISMhNl33//ff58MMPiY2N5amnniIpKenWEn8nONjntpb/T6GhvnZdX2PljHP+ZnwPXvnLNv6y6muaNXNjSKivU855I5rTuWhO59JQc5qsVqu1ti+ePn06xcXFvP3225jN/96YHzJkCBMnTqRfv343XK64uJjQ0FDMZjNLlizhzTffZM2aNbi4uNxy8NLSciyWWkf/UaGhvpSUOP9Vw5x5zitVFt5dks2eb08xtEci/TtG4+vlbnSseuXM388f0pzORXPWndls+tGN11qftZ6ZmUlubi5vvPHGNSW+Z88ezp49S+/evW+6bHh4uG2ZkSNHcuHCBU6cOFHbtxapkZurmfH3tqNPh2hWbjrG1LlbWL7pGJcuVxsdTUSkXtWqyGfNmkV2djazZ8/G3f3arZyFCxcyfPhwXF1vvpe+uLjY9ucNGzZgNpsJDw+/xcgiN+bqYubhgcm8NakPreMCWbzhaqGv3ZVPVbXF6HgiIvWixmPkhw8fZu7cuSQkJDBmzBgAYmJimD17NhcvXmTlypV89NFH1y03YsQI5s2bR3h4OFOmTKG0tBSTyYSPjw/vvvvujxa/yO2Ii/DjidGpfJt/lo+/+Jb/+/wbPtt+nFG9mtO5dRhmk8noiCIidlOnY+SNiY6R111TnNNqtbL3SCkfrztCQUkF8RG+3HdXEm0TggxOefua4vfTmWlO59KQx8i1WSxOzWQycUeLENo3D2bL/hMs2XCM33+whzYJgdx3VxIJEX5GRxQRuS0qcmkSzGYT3dtHkp4SztrdBazYnMOMv+ygS+swRvVqTniQl9ERRURuiYpcmhQ3VzMDusTSo30kn27L4/Pteez6poRed0QxvHsC/j4eRkcUEakTFbk0SV7NXBnVqzn9OkazbHMO6/cUsim7iAFdYhmUHo9XM/2vISKOQT+tpEnz9/Hg4QHJDOgSy+L1R1mxOZcvdhcypGs8fTtG4+Z66xctEhFpCLqNqQgQHujFL0e044WfdSE+wpcPs77l2Xlfsmlfkd0+HSEiUh9U5CI/EB/hy1MPpDFpTBq+Xu6898lBXnh/G3sOn8JBP6kpIk5ORS5yA20Sgnj+/3XmVyPbUVVl4Q8L9/Lq/F0czj9jdDQRkWvoGLnITZhMJrq0DqNDyxA27i1i6aZjvPr3XaS1CGF07+ZEh9r3DnwiIrdCRS5SA1cXM3d1iKZr2whW7zjOqq25TPvzNrq1i2Bkj+YE+zczOqKINGEqcpFa8nB3YWi3BO7qEM0nW3L4184Cth44Sd+O0QztloCPp5vREUWkCVKRi9SRj6cbD/Rtyd2dYlm68Rirdxxnw95CBmfE079zLB7u+siaiDQcFbnILQr2b8bPh6QwMD2WheuOsmj9Uf61M5/hPRLpmRqJq4vOJRWR+qefNCK3KTrUhyfvS+WZhzoSFujJ/312iOf/tJVtB4v1kTURqXcqchE7aRkTwNQHO/Lk6FRcXczMWbqfl/66gwM5p42OJiJOTLvWRezIZDKR1jKE1KTvb5t6lNc+2EPbhEDuu6sF8RG+RkcUESejIhepB/++bWoYa3cVsGJLLtP/sp30lDDu7dWc8EDdNlVE7ENFLlKP3FxdGJAeR4/UKNttU3ceKqFXWhTDu+m2qSJy+1TkIg3g+9um9u0YzfJNV2+bunnfCfp3iWVwRhyeHvpfUURujX56iDSgAB8PHh6YzID072+bmsMXuwsY2i2BPh2icXPV+aciUjf6qSFigO9vmzrtZ52JD/fhg38d1m1TReSWqMhFDJQQ4cdTYzrw1Jg0fLzceO+Tg7z4/ja++la3TRWR2tGudZFGoG1CECn/L5AdX59k0fqjvPnxXlrF+HNfnxa0iPY3Op6INGIqcpFGwmwykZ4STsdWoWzYW8Syjcd45f920qFlCKN6JxEd4m10RBFphFTkIo2Mq4uZPh2i6dY2gs93HOfTrblMe28r3dtFMrJnIkF+um2qiPxbjUVeVlbG5MmTycvLw93dnfj4eGbMmEFQUBDJycm0atUKs/nqofaZM2eSnJx83TpOnTrF5MmTKSgowMPDg5deeok77rjD/tOIOBEPdxeGfXc2+4rNOWTtyufLA8Xc3SmGe7rGE2p0QBFpFEzWGs6oOXPmDIcOHSIjIwOAzMxMzp49yyuvvEJycjK7du3C2/vHd/k988wzxMbGMn78eHbs2MGzzz7LZ599hslkuuXgpaXldju7NzTUl5KS83ZZV2OmOR3bqbOVLN1wjM3ZJ2jm4cqoPi3o2joUr2bOfR90Z/1+/ifN6VzsOafZbCI42OfmX69pBQEBAbYSB0hLS6OwsLBOIT799FPGjBkDQOfOnXF3d2ffvn11WodIUxfi78kjQ9sw/ZF0WscFMP/Tr3n63c0sWn+U8sorRscTEYPU6Ri5xWJhwYIF9O3b1/bcww8/THV1Nb169eKJJ57A3d39mmXKysqwWq0EBQXZnouMjOTEiROkpqbeZnyRpicm1IcnRqdy/rKFv32ynxWbc1i94zh9O0YzsEscft7uNa9ERJxGnYr8pZdewsvLi4ceegiAL774gsjISMrLy3n66aeZPXs2v/71r+sl6H/6sd0MtyI0tGnclUpzOo9Q4MVx3cg9cY6P1nzDp1vz+NfOAu7plsC9d7VwqpPimsL3EzSns2moOWtd5JmZmeTm5jJnzhzbyW2RkZEA+Pj4cP/99/P+++9ft1xgYCAAp0+ftm2VFxUVERERcVvBdYy87jSnc/l+Ti8XEz8bmMzAzjF8siWXZeuPsmLjMXrfEcXgO+McvtCb2vfT2WnOurvtY+QAs2bNIjs7m9mzZ9t2nZ89e5aLFy8CUFVVxWeffUZKSsoNlx80aBAffPABADt27ODixYu0a9euToOIyI+LDPbm0aFteGVcBl3bhvPFngKmzt3C3z79mlNnKo2OJyL1pMaz1g8fPszQoUNJSEigWbOrv9nHxMTw6KOPMm3aNEwmE1VVVXTo0IFnn30Wb29viouLGTduHEuXLgWgpKSEp59+msLCQjw8PJg+fTodO3a8reDaIq87zelcaprz1NlKVn2Zx4a9hVit0LVdBEO6xjvcvdD1/XQumrPuatoir7HIGysVed1pTudS2znLzl9i1Ze5rPuqkKpqC3e2CWdotwQigx3jSnH6fjoXzVl3NRW5ruwm4uQCfT0Y278VQ7rG89m242TtzufL/cV0bh3GsG4JxITZ98RREWlYKnKRJsLfx4P/6tuCQXfGsXr7cf61M5/tX5+kY6tQhnVLID6iaZxJLOJsVOQiTYyflzujeycxMD2ONTuOs3pHPru+KSE1KZhh3RNIitLd1kQciYpcpIny8XRjZM/mDOgSx7925fP5tjxe/ttO2iYGMaxbAq1iA4yOKCK1oCIXaeK8mrkyrFsCd3eK4YvdBXy2LY/fzt9F67gAhnVPpHVcwG3dF0FE6peKXEQA8PRwZfCd8fTtFMO6PYWs2prL7xbspkWMP8O7J9A2IUiFLtIIqchF5Boebi4M6BJLnw5RrP+qiFVbc5n14VckRvoxrHsCdyQFq9BFGhEVuYjckJurC/06xdA7LYpN+4r4ZEsuf/h4L3HhPgzrlkiHViGYVegihlORi8iPcnUx0zstmu7tI/lyfzGfbMlh9uJ9RId6M6xbAp2TwzCbVegiRlGRi0ituLqY6ZEaSdd24Ww/eJLlm3OYs3Q/kcHHGNo1gfQ2YbiYa3X7BhGxIxW5iNSJi9nMnW0jSG8Tzs5DJSzflMMfVxxg6aZjDOkaT9e2Ebi6qNBFGoqKXERuidlkokvrMDolh7Ln8CmWb8rh/ZVfs3xTDvfcGU/39pG4uarQReqbilxEbovZZKJjq1A6tAxh39FSlm3K4W+fHWL55quF3uuOSNxcXYyOKeK0VOQiYhcmk4nUpBDaNw/mQE4ZyzcdY/7qb1ixOYdBGXHclRaNh7sKXcTeVOQiYlcmk4m2iUG0TQziUF4Zyzbl8GHWt6z8MpeB6XH06RCNp4d+9IjYi/5vEpF6kxwXyNNxgXybf5Zlm4/x8RdHWPVlLv27xHJ3pxi8mrkZHVHE4anIRaTetYjxZ+J/pXG08BwrNuewZMMxPtt2nLs7xdC/Syw+nip0kVulIheRBtM8yo8n70sl98R5VmzOYfnmHD7fcZx+HWMYkB6Ln5e70RFFHI6KXEQaXHyEL4+Pak9+STkrNuew6stc1uw8zl1p0QzKiCPAx8PoiCIOQ0UuIoaJCfXhlyPaMaJHBSs257JmRz5ZuwronRbF4Iw4gvyaGR1RpNFTkYuI4SKDvXlsWBtG9Ejgky25fLG7gHV7CujRPpL7+ifj5aJruYvcjIpcRBqNsEAv/vueFIZ1S2Dl1jw27i3kiz2FRId6k54STkZKGGGBXkbHFGlUVOQi0uiEBHjy04HJjOiRyKH8s/xrex6L1x9l8fqjJEb6kp4STpfWYdr1LoKKXEQaMX9vd4b0aE56ciilZy+y/euTbD1YzIdZ3/Jh1re0ivEno004nZLD8PPWGe/SNKnIRcQhBPs3Y1BGHIMy4ig+fYFtB4vZevAk//f5N8xffZiUhEDSU8Lo1CpUF5qRJkVFLiIOJzzIi2HdExnaLYGCkgq2Hixm28Fi3l/5Nf/32SHaJQaT0SactBYhur67OL0ai7ysrIzJkyeTl5eHu7s78fHxzJgxg7NnzzJt2jRKSkpwdXWlffv2vPDCCzRrdv0xq4cffpjCwkJ8fHwA+OlPf8ro0aPtP42INCkmk4mYMB9iwnwY1as5OSfOs/VAMdu/Psmeb0/h7mYmrUUI6SnhtG8epLuwiVMyWa1W64+94MyZMxw6dIiMjAwAMjMzOXv2LOPHj+fcuXO0adMGi8XCxIkTadmyJY8//vh163j44Yf5+c9/Tp8+fewWvLS0HIvlR6PXWmioLyUl5+2yrsZMczoXzXlzFquVw8fPsO3gSbZ/fZLyyit4erjQsWUo6W3CSYkPxNWlcd0rXd9P52LPOc1mE8HBPjf9eo1b5AEBAbYSB0hLS2PBggXExMT84E3MpKamcuTIkduMKyJy+8wmE8lxgSTHBTK2f0sO5pax7cBJdn5TwqbsE/h4utG5dRgZKWG0jA3AbNLn1MVx1ekYucViYcGCBfTt2/ea5y9evMjChQuZOHHiTZedOXMms2bNIjk5maeffprw8PBbSywiUgcuZjPtEoNplxjMwwOTyT5aytaDxWzOLuKL3QUE+LjTpXU46W3CaB7ph0mlLg6mxl3rPzR9+nSKi4t5++23MZuv7paqqqriiSeeICoqiueff/6GyxUVFREZGUl1dTVz585lw4YNLFiwwD4TiIjcgouXqth+oJj1e/LZcfAkVdUWwoO86NUhmp5p0SSo1MVB1LrIMzMzOXToEHPmzMHd/ernNaurq3nqqado1qwZr776aq3+0ZeXl5Oenk52drbtl4FboWPkdac5nYvmtJ8LF6+w65tTbDtYzIGcMixWK5HBXmSkhJPeJpyIoPq/mpy+n86lUR0jB5g1axbZ2dnMmzfPVuIWi4WpU6fi4uLCyy+/fNMSr6qq4syZM4SEhADwySef0KpVq9sqcRERe/Jq5kaP1Eh6pEZy7sJldh4qYduBYpZuPMaSjceID/clvU0YXVqHEeLvaXRckWvUWOSHDx9m7ty5JCQkMGbMGABiYmK4//77WbZsGa1atWLUqFEAdOzYkRdeeIHi4mLGjRvH0qVLuXz5MuPGjePKlSsAhIWFMWvWrHocSUTk1vl5udOnQzR9OkRTdv4S27+78Mw/1x7hn2uP0CLan/SUq6Xur9utSiNQp2PkjYl2rded5nQumrNhnTxTebXUD5wkv6QckwlaxwWS0Sacjq1C8fG8vavJNZY565vmrDu77FoXEWnqwgI8GdI1gSFdEyg4VcG2A8VsPVjMX1ZdvZpc28QgMlLCSWsZgqeHfrRKw9G/NhGROooO8ebeXs0Z2TORvOJy2yVi9x4pxc3VzB1JwaSnhJOaFIy7m64mJ/VLRS4icotMJhPxEb7ER/hy311JHCk4y7YDJ9n+dTE7DpXg4e5Cx5ZXLxHbNjGo0V1NTpyDilxExA7MJhMtYwJoGRPAmLtbcCjvDNsOFrPzUAlb9hfj3cyVTslXryaXHBeI2azPqIt9qMhFROzMxWymTUIQbRKCeGhAMtnHTl+97eqBYtZ/VYi/t/t3l4gNp3m0ny4RK7dFRS4iUo9cXa7egS2tRQiXrlSz78jVS8Su21PIv3bmE+znQXpKOL07xxHk5ard71JnKnIRkQbi4eZC59ZhdG4dRuWlKnYfLmHbwZN8vv04q7bm4eHmQnJcAG3iA2mTEER0qLcuEys1UpGLiBjA08OVbu0i6dYukoqLVyg6c5Etews5kFPG3iOlAPh5uZGSEGQr9mD/ZganlsZIRS4iYjDvZm50bR9EiwhfAE6fu8iBnDIO5J7mQE4ZWw8UAxAe6Gkr9tbxgbd9ERpxDipyEZFGJsivme3a71arlYJTFRzIKeNgzmm27D/BF7sLMAHxEb60SQgiJSGQltH++sx6E6UiFxFpxEwmEzGhPsSE+jCgSyxV1RaOFZ2zFftn2/JY+WUuri5mWsb40ybh6m74+HBffcStiVCRi4g4kKuFffXz6iN6JHLxchXfHD9zdVd8zmkWrjvKwnVH8fJwJSU+0FbsYYGeOnHOSanIRUQcWDN3V1KTQkhNunqr6LMVlzn43bH1Azmn2flNCQBBfh60iQ+iTUIgKQlB+Hu7Gxlb7EhFLiLiRPy93bmzTQR3tonAarVysqySA7lXS3334RI27isCIDrU21bsrWIDdKMXB6bvnIiIkzKZTIQHeREe5EWfDtFYLFZyi89zIOc0B3PLWLu7gNU7juNiNtE8yu+7XfFBNI/y04VpHIiKXESkiTCbTSRG+pEY6ceQrglcvlLNtwVnbbvhl2/KYdmmHDzcXUiO1YVpHIWKXESkiXJ3c7FdEx6SKK+8wqG8Mlux2y5M4+1Om/hA2xa7LkzTuKjIRUQEAB9PNzolh9EpOQyA0rMXOZB7moPfFfuXP7gwzdVfAK5emMa7mS5MYyQVuYiI3FCwfzN6pkbRMzXq6oVpSio4kHOaA7llbM4+wdr/uDBNm4RAWsb44+aqC9M0JBW5iIjUyGQyERPmQ0yYDwPS46iqtnC08Jyt2L+/MI2bq5kW0bowTUNSkYuISJ25uphpFRtAq9gARvaEyks/uDBN7r8vTOPdzJXW8YG2E+dCQnyMju50VOQiInLbPD1cuaNFCHe0+O7CNOWXOJhbZiv2nYeuXpjGx9ON6BBvYsJ8iP3uv6gQbzx0nfhbpiIXERG78/fx4M62EdzZ9uqFaYrLKjmYW8bJsxf5Nq+MjXuLuHSlGgCTCcIDvYj9btd9bJgPsaE+BPl56GNvtaAiFxGRemUymYgI8iIiyIvQUF9KSs5jsVopOVPJ8eJy8kvKOX6ynGNF59j+9Unbcl4erleLPdSH2PCrN46JDtXW+39SkYuISIMzm0yEB3oRHuhF59ZhtucrL1WRX1JO/smr5X68pJyN+4q4tOu7rXcgLMjru612b2LDfIkJ8ybYr1mT3XpXkYuISKPh6eFqu7vb9yxWK6fOVF4t9u/+yz1xjh0/2Hr39HAlNvTfx95jwnyICfHBw935t95rLPKysjImT55MXl4e7u7uxMfHM2PGDIKCgtizZw/Tpk3j0qVLREdH87vf/Y7g4ODr1lFZWckzzzzD/v37cXFxYcqUKfTp06deBhIREediNpkIC/QiLNDLdrEauLr1XlBSwfHvds3nnyxnU/YJLl3+wdZ7oOd1x96D/Z1r673GIjeZTDz66KNkZGQAkJmZyWuvvcZvfvMbnn76aV599VU6d+7MO++8w2uvvcarr7563Tree+89fHx8WL16NTk5OTz44IN8/vnneHt7238iERFpEjw9XGkR40+LGH/bcxarlVNnL15z7D2vuJwd3501f3U5F2JCry33mFDH3XqvscgDAgJsJQ6QlpbGggULyM7OxsPDg86dOwMwZswY+vXrd8MiX7VqFb/97W8BSEhIoF27dqxfv57Bgwfbaw4REZGrW+8BnoQFeNIpOdT2fOWlKgpOVVxz7H1L9gnW/mDrPfS7rffY0H/vng9xgK33Oh0jt1gsLFiwgL59+1JUVERUVJTta0FBQVgsFs6cOUNAQMA1yxUWFhIdHW17HBkZyYkTJ24reHCwfS8qEBrqa9f1NVaa07loTueiOetXXEzgNY8tFisnyy5wrPAcOUXnyCk6y7HCc+z6pgSr9eprPD1cSYj0IzHKj4QofxKj/IiP8KvV/dsbas46FflLL72El5cXDz30EKtXr66vTLVSWlqOxWK1y7q+/ziEs9OczkVzOhfNaQwXoEWEDy0ifKDD1Y3Ti5evP/a+dudxKjfn2JYLC7j22Pv3W+/m77be7Tmn2Wz60Y3XWhd5ZmYmubm5zJkzB7PZTGRkJIWFhbavnz59GrPZfN3WOEBUVBQFBQUEBQUBUFRUdM3uehERkcaimbsrSdH+JEX/+9i71Wql9OzFa8r9+Mnyq1vvtuWuHnuPD/flv0e0a7C8tSryWbNmkZ2dzbx583B3dwegXbt2XLx4kR07dtC5c2c++OADBg0adMPlBw0axIcffkj79u3Jyclh3759/P73v7ffFCIiIvXIZDIREuBJSIAnHVr++9j7pcvV5J/6d7Hnnyxn1+ES+p8sJ8zXvUGy1Vjkhw8fZu7cuSQkJDBmzBgAYmJimD17NjNnzuSFF1645uNn3xsxYgTz5s0jPDycRx55hKlTp9K/f3/MZjMzZszAx0cXzhcREcfm4e5CUpQ/SVH+1zzfkIcQTFar1T4HmhuYjpHXneZ0LprTuWhO59KQx8jNdnkXERERMYSKXERExIGpyEVERByYilxERMSBqchFREQcmIpcRETEganIRUREHJiKXERExIGpyEVERByYilxERMSB1ek2po2J2WzfG73be32NleZ0LprTuWhO52KvOWtaj8Nea11ERES0a11ERMShqchFREQcmIpcRETEganIRUREHJiKXERExIGpyEVERByYilxERMSBqchFREQcmIpcRETEganIRUREHJiKXERExIGpyEVERByYw9797HaVlZUxefJk8vLycHd3Jz4+nhkzZhAUFGR0NLsbP348+fn5mM1mvLy8eP7550lJSTE6Vr15++23eeutt1i+fDmtWrUyOo7d9e3bF3d3dzw8PACYNGkSPXv2NDiV/V26dIlXXnmFLVu24OHhQVpaGi+99JLRsewqPz+fxx9/3Pb4/PnzlJeXs23bNgNT1Y+1a9fy5ptvYrVasVqt/M///A8DBgwwOpbdffHFF7z55ptUVVXh7+/Pq6++SmxsbP2+qbWJKisrs3755Ze2x7/97W+tzzzzjIGJ6s+5c+dsf169erV15MiRBqapX9nZ2dZHHnnE2qdPH+uhQ4eMjlMvnHm2H3rppZesL7/8stVisVitVqu1pKTE4ET17ze/+Y11+vTpRsewO4vFYu3cubPt3+3BgwetaWlp1urqaoOT2deZM2es6enp1qNHj1qtVqt1yZIl1p///Of1/r5Ndtd6QEAAGRkZtsdpaWkUFhYamKj++Pr62v5cXl6OyeSc9wK+fPkyM2bM4MUXXzQ6itymiooKlixZwoQJE2z/XkNCQgxOVb8uX77M8uXLGT16tNFR6oXZbOb8+fPA1T0PYWFhmM3OVUG5ubmEhISQmJgIQO/evdm4cSOnT5+u1/dtsrvWf8hisbBgwQL69u1rdJR689xzz7Fp0yasVit/+tOfjI5TL958802GDx9OTEyM0VHq3aRJk7BarXTq1ImJEyfi5+dndCS7On78OAEBAbz99tts3boVb29vJkyYQOfOnY2OVm+ysrIIDw+nbdu2RkexO5PJxBtvvMH48ePx8vKioqKCefPmGR3L7hITEzl16hR79+4lNTWV5cuXA1BUVFSvh22d69ehW/TSSy/h5eXFQw89ZHSUevPyyy/zxRdf8Otf/5qZM2caHcfudu/eTXZ2NmPHjjU6Sr2bP38+y5YtY+HChVitVmbMmGF0JLurrq7m+PHjtGnThkWLFjFp0iSeeOIJysvLjY5WbxYuXOi0W+NVVVXMnTuXd955h7Vr1/Luu+/yv//7v1RUVBgdza58fX15/fXXefXVVxk1ahSlpaX4+fnh4uJSr+/b5Is8MzOT3Nxc3njjDafbzXMjI0eOZOvWrZSVlRkdxa62b9/OkSNH6NevH3379uXEiRM88sgjbNy40ehodhcZGQmAu7s7Y8eOZdeuXQYnsr/IyEhcXV0ZOnQoAHfccQeBgYEcO3bM4GT1o7i4mO3btzNs2DCjo9SLgwcPcvLkSTp16gRAp06d8PT05MiRIwYns79u3bqxYMECFi1axEMPPcTFixeJi4ur1/d0/ub6EbNmzSI7O5vZs2fj7u5udJx6UVFRQVFRke1xVlYW/v7+BAQEGJjK/saNG8fGjRvJysoiKyuLiIgI3nvvPXr06GF0NLu6cOGC7Tij1Wpl5cqVTvkJhKCgIDIyMti0aRMAx44do7S0lPj4eIOT1Y/FixfTu3dvAgMDjY5SLyIiIjhx4gRHjx4F4MiRI5SWltZ7wRmhpKQEuHrIdtasWYwZMwYvL696fc8me4z88OHDzJ07l4SEBMaMGQNATEwMs2fPNjiZfVVWVjJhwgQqKysxm834+/szZ84cpz3hzdmVlpbyxBNPUF1djcViISkpiRdeeMHoWPVi+vTpPPvss2RmZuLq6srMmTOd7lyAqlcTVgAAAH1JREFU7y1evJjnnnvO6Bj1JjQ0lBdffPGakxdfeeUVp9ugAHjjjTfYtWsXV65coXv37kyaNKne39NktVqt9f4uIiIiUi+a9K51ERERR6ciFxERcWAqchEREQemIhcREXFgKnIREREHpiIXERFxYCpyERERB6YiFxERcWD/H+SwCwBw9mrNAAAAAElFTkSuQmCC","text/plain":["<Figure size 576x396 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["distorsions, k1, kN = [], 2,10\n","for k in range(k1, kN):\n","    kmeans = cluster.KMeans(n_clusters=k).fit(x_scaled)\n","    distorsions.append(kmeans.inertia_)\n","#fig = plt.figure(figsize=(15, 5))\n","plt.plot(range(k1, kN), distorsions); plt.grid(True)\n","plt.title('Elbow curve')\n","\n","#Berdasarkan elbow method, kemungkinan cluster akan baik jika dipilih antara 3,4 atau 5."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":489},"executionInfo":{"elapsed":12685,"status":"ok","timestamp":1609927163231,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"eP12EQWwihr1","outputId":"abcc4a62-71fe-492b-af24-bde6610fab3f","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1080x576 with 6 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["from yellowbrick.cluster import SilhouetteVisualizer\n","fig, ax = plt.subplots(3, 2, figsize=(15,8))\n","for i in [2, 3, 4, 5,6,7]:\n","    km = KMeans(n_clusters=i, init='k-means++', n_init=10, max_iter=100, random_state=42)\n","    q, mod = divmod(i, 2)\n","    visualizer = SilhouetteVisualizer(km, colors='yellowbrick', ax=ax[q-1][mod])\n","    visualizer.fit(x_scaled)\n","\n","    #Berdasarkan proporsinya, jumlah cluster 2,3,4 memiliki proporsi yang cukup bagus.\n","    #Pada penelitian ini, kelompok kami memutuskan menggunakan jumlah cluster 4"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":12672,"status":"ok","timestamp":1609927163232,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"72TbUUb0aO3X","outputId":"5f9b9f36-ceb2-4e3f-b7c5-bf0b599047df","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n","       n_clusters=4, n_init=10, n_jobs=None, precompute_distances='auto',\n","       random_state=123, tol=0.0001, verbose=0)"]},"execution_count":128,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["kmeans_4 = KMeans(n_clusters = 4,random_state = 123) #4 Cluster\n","kmeans_4.fit(x_scaled)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"2UtmEL8ga-Lf","vscode":{"languageId":"python"}},"outputs":[],"source":["C_km=kmeans_4.predict(x_scaled)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":353},"executionInfo":{"elapsed":14515,"status":"ok","timestamp":1609927165097,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"wvtxeEeyv4m8","outputId":"824df452-736e-4f3c-8034-c2e996ef0cef","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 576x396 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["X2D = umap.UMAP(n_neighbors=5, min_dist=0.3, random_state=99).fit_transform(x_scaled)\n","fig, ax = plt.subplots()\n","ax.scatter(X2D[:,0], X2D[:,1], c=C_km, cmap =('RdBu'))\n","plt.show()\n","\n","#Terdapat 4 cluster yang dibedakan oleh 4 warna"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"7oN7EkNhcIgD","vscode":{"languageId":"python"}},"outputs":[],"source":["kmeansminipp = cluster.MiniBatchKMeans(n_clusters = 4,init='k-means++',random_state = 123)\n","kmeansminipp.fit(x_scaled)\n","C_kmmpp=kmeansminipp.predict(x_scaled)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":14493,"status":"ok","timestamp":1609927165099,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"eA5Lcp0_d1lG","outputId":"ebc644e6-dd2d-44fe-fc2d-66b632c365c8","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["array([[0.76771224, 0.62746485, 0.52871809, 0.80274709, 0.6357179 ,\n","        0.28542801],\n","       [0.29394603, 0.31388351, 0.2191542 , 0.40571434, 0.29579321,\n","        0.03223044],\n","       [0.60183275, 0.51279053, 0.4422948 , 0.23050336, 0.43354875,\n","        0.25813797],\n","       [0.51240823, 0.48712204, 0.40280425, 0.62772436, 0.27000538,\n","        0.30623568]])"]},"execution_count":132,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["kmeansminipp.cluster_centers_"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":354},"executionInfo":{"elapsed":14482,"status":"ok","timestamp":1609927165101,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"EWYyszrDXmL_","outputId":"e7d504a7-738e-45f4-e4b7-2ebaf464a0c3","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 576x396 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["cols = ['ssc','hsc','degree_p','etest_p','mba_p','salary']\n","dfC = pd.DataFrame(kmeansminipp.cluster_centers_, columns=cols)\n","dfC['cluster'] = dfC.index\n","\n","pd.plotting.parallel_coordinates(dfC, 'cluster', color=('r', 'g', 'b','m'))\n","plt.show()\n","\n","#Cluster 0 adalah cluster untuk mahasiswa yang memiliki nilai etest_p tertinggi\n","#Cluster 1 adalah cluster untuk mahasiswa dengan gaji terendah\n","#Cluster 2 adalah cluster untuk mahasiswa dengan nilai etest_p terendah\n","#Cluster 3 adalah cluster untuk mahasiswa dengan nilai mba_p terendah"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":173},"executionInfo":{"elapsed":14469,"status":"ok","timestamp":1609927165104,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"0Adv3JHUiEvX","outputId":"616b87ea-2558-4e7d-ed4c-602381941de7","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>ssc</th>\n","      <th>hsc</th>\n","      <th>degree_p</th>\n","      <th>etest_p</th>\n","      <th>mba_p</th>\n","      <th>salary</th>\n","      <th>cluster</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.767712</td>\n","      <td>0.627465</td>\n","      <td>0.528718</td>\n","      <td>0.802747</td>\n","      <td>0.635718</td>\n","      <td>0.285428</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0.293946</td>\n","      <td>0.313884</td>\n","      <td>0.219154</td>\n","      <td>0.405714</td>\n","      <td>0.295793</td>\n","      <td>0.032230</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.601833</td>\n","      <td>0.512791</td>\n","      <td>0.442295</td>\n","      <td>0.230503</td>\n","      <td>0.433549</td>\n","      <td>0.258138</td>\n","      <td>2</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.512408</td>\n","      <td>0.487122</td>\n","      <td>0.402804</td>\n","      <td>0.627724</td>\n","      <td>0.270005</td>\n","      <td>0.306236</td>\n","      <td>3</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        ssc       hsc  degree_p   etest_p     mba_p    salary  cluster\n","0  0.767712  0.627465  0.528718  0.802747  0.635718  0.285428        0\n","1  0.293946  0.313884  0.219154  0.405714  0.295793  0.032230        1\n","2  0.601833  0.512791  0.442295  0.230503  0.433549  0.258138        2\n","3  0.512408  0.487122  0.402804  0.627724  0.270005  0.306236        3"]},"execution_count":134,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["dfC"]},{"cell_type":"markdown","metadata":{"id":"g9NCSZzAwZiu"},"source":["* Cluster 0 adalah cluster untuk mahasiswa yang memiliki nilai etest_p tertinggi\n","* Cluster 1 adalah cluster untuk mahasiswa dengan gaji terendah\n","* Cluster 2 adalah cluster untuk mahasiswa dengan nilai etest_p terendah\n","* Cluster 3 adalah cluster untuk mahasiswa dengan nilai mba_p terendah"]},{"cell_type":"markdown","metadata":{"id":"-7h2fnAPLAWX"},"source":["#Pemodelan"]},{"cell_type":"markdown","metadata":{"id":"XLGSa9b5wYVh"},"source":["## Klasifikasi"]},{"cell_type":"markdown","metadata":{"id":"HlRpCQH5ZajC"},"source":["### Support Vector Machine"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Y5iL7tW2ZfbU","vscode":{"languageId":"python"}},"outputs":[],"source":["import sklearn\n","from sklearn import svm\n","from sklearn.model_selection import train_test_split\n","from sklearn import metrics\n","from sklearn.metrics import classification_report\n","from sklearn.metrics import confusion_matrix\n","from sklearn.metrics import accuracy_score\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.model_selection import cross_val_score\n","from sklearn.preprocessing import StandardScaler"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":21936,"status":"ok","timestamp":1609926249958,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"sEhSx12Wa9eB","outputId":"a4b851aa-50af-4c36-ea0d-b1e01d340fa5","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["(129, 14) (86, 14) 86\n","acc train0.8604651162790697\n","acc test0.9302325581395349\n","[[22  4]\n"," [ 2 58]]\n","              precision    recall  f1-score   support\n","\n","           0       0.92      0.85      0.88        26\n","           1       0.94      0.97      0.95        60\n","\n","    accuracy                           0.93        86\n","   macro avg       0.93      0.91      0.92        86\n","weighted avg       0.93      0.93      0.93        86\n","\n","[0.76923077 0.84615385 0.92307692 0.69230769 0.76923077 0.84615385\n"," 0.69230769 0.92307692 0.69230769 0.83333333]\n"]}],"source":["X_trains, X_tests, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=1)\n","print(X_trains.shape, X_tests.shape, len(y_test))\n","\n","sc = StandardScaler()\n","X_train = sc.fit_transform(X_trains)\n","X_test = sc.transform(X_tests)\n","\n","svmLinear= svm.SVC(kernel='linear', C=1)\n","svmLinear.fit(X_train, y_train)\n","y_train2 = svmLinear.predict(X_train)\n","y_pred = svmLinear.predict(X_test)\n","print('acc train' + str(accuracy_score(y_train, y_train2)))\n","print('acc test' + str(accuracy_score(y_test, y_pred)))\n","print(confusion_matrix(y_test, y_pred))\n","print(classification_report(y_test, y_pred))\n","print(cross_val_score(svmLinear, X_train, y_train, cv=10))"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":21931,"status":"ok","timestamp":1609926249959,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"BXsIGw4AdsJn","outputId":"14100157-00c2-480f-f62c-a8e925907296","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["(129, 14) (86, 14) 86\n","acc train0.875968992248062\n","acc test0.9186046511627907\n","[[21  5]\n"," [ 2 58]]\n","              precision    recall  f1-score   support\n","\n","           0       0.91      0.81      0.86        26\n","           1       0.92      0.97      0.94        60\n","\n","    accuracy                           0.92        86\n","   macro avg       0.92      0.89      0.90        86\n","weighted avg       0.92      0.92      0.92        86\n","\n","[0.76923077 0.84615385 1.         0.69230769 0.76923077 0.84615385\n"," 0.69230769 0.92307692 0.76923077 0.83333333]\n"]}],"source":["X_trains, X_tests, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=1)\n","print(X_trains.shape, X_tests.shape, len(y_test))\n","\n","sc = StandardScaler()\n","X_train = sc.fit_transform(X_trains)\n","X_test = sc.transform(X_tests)\n","\n","svmLinear10= svm.SVC(kernel='linear', C=10)\n","svmLinear10.fit(X_train, y_train)\n","y_train2 = svmLinear10.predict(X_train)\n","y_pred = svmLinear10.predict(X_test)\n","print('acc train' + str(accuracy_score(y_train, y_train2)))\n","print('acc test' + str(accuracy_score(y_test, y_pred)))\n","print(confusion_matrix(y_test, y_pred))\n","print(classification_report(y_test, y_pred))\n","print(cross_val_score(svmLinear10, X_train, y_train, cv=10))"]},{"cell_type":"markdown","metadata":{"id":"8a_CI48Io9Bf"},"source":["parameter terbaik didapatkan adalah C=1"]},{"cell_type":"markdown","metadata":{"id":"w2IIcOcn3ykY"},"source":["### SVM dengan SMOTE"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":21928,"status":"ok","timestamp":1609926249960,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"xxkkQlge24Bo","outputId":"278166aa-1e60-4932-cd66-1adf58a27a3d","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["Counter({1: 148, 0: 67})\n","Counter({1: 148, 0: 148})\n"]}],"source":["# borderline-SMOTE with SVM for imbalanced dataset\n","from collections import Counter\n","from sklearn.datasets import make_classification\n","from imblearn.over_sampling import SVMSMOTE\n","from matplotlib import pyplot\n","from numpy import where\n","# summarize class distribution\n","counter = Counter(y)\n","print(counter)\n","# transform the dataset\n","oversample = SVMSMOTE()\n","X_baru, y_baru = oversample.fit_resample(X, y)\n","# summarize the new class distribution\n","counter = Counter(y_baru)\n","print(counter)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1146,"status":"ok","timestamp":1609931843276,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"RK_j0r_KajfP","outputId":"36884f7b-a00a-4055-f75f-524207cf9020","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["array([[67.        , 91.        , 58.        , ...,  1.        ,\n","         0.        ,  0.        ],\n","       [79.33      , 78.33      , 77.48      , ...,  1.        ,\n","         1.        ,  1.        ],\n","       [65.        , 68.        , 64.        , ...,  0.        ,\n","         0.        ,  1.        ],\n","       ...,\n","       [65.22851495, 47.75492132, 55.85463021, ...,  1.48806058,\n","        -0.48806058,  1.        ],\n","       [52.        , 50.00676054, 61.02028163, ...,  0.        ,\n","         0.        ,  1.00676054],\n","       [50.23056865, 48.01698259, 58.24575435, ...,  0.        ,\n","         0.        ,  0.        ]])"]},"execution_count":155,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["X_baru"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":21923,"status":"ok","timestamp":1609926249961,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"-7SYR7Zz3eWN","outputId":"2b299180-15f2-4d7e-d576-8bcbbc0779ba","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["(177, 14) (119, 14) 86\n","acc train0.8757062146892656\n","acc test0.907563025210084\n","[[61  6]\n"," [ 5 47]]\n","              precision    recall  f1-score   support\n","\n","           0       0.92      0.91      0.92        67\n","           1       0.89      0.90      0.90        52\n","\n","    accuracy                           0.91       119\n","   macro avg       0.91      0.91      0.91       119\n","weighted avg       0.91      0.91      0.91       119\n","\n","[0.83333333 0.83333333 0.88888889 0.77777778 0.94444444 0.83333333\n"," 0.83333333 0.88235294 0.82352941 0.82352941]\n"]}],"source":["X_trains, X_tests, y_train_baru, y_test_baru = train_test_split(X_baru, y_baru, test_size=0.4, random_state=1)\n","print(X_trains.shape, X_tests.shape, len(y_test))\n","\n","sc = StandardScaler()\n","X_train_baru = sc.fit_transform(X_trains)\n","X_test_baru = sc.transform(X_tests)\n","\n","svmLinear1= svm.SVC(kernel='linear', C=1)\n","svmLinear1.fit(X_train_baru, y_train_baru)\n","y_train2 = svmLinear1.predict(X_train_baru)\n","y_pred = svmLinear1.predict(X_test_baru)\n","print('acc train' + str(accuracy_score(y_train_baru, y_train2)))\n","print('acc test' + str(accuracy_score(y_test_baru, y_pred)))\n","print(confusion_matrix(y_test_baru, y_pred))\n","print(classification_report(y_test_baru, y_pred))\n","print(cross_val_score(svmLinear1, X_train_baru, y_train_baru, cv=10))\n","cv_svmSMOTE = cross_val_score(svmLinear1, X_train_baru, y_train_baru, cv=10)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":21920,"status":"ok","timestamp":1609926249961,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"_lf182_s6CvT","outputId":"cc8f88e0-4d75-445b-e0a9-a641f6129d00","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["array([[ 1.6854108 ,  0.40222026,  0.76137156, -0.07061094, -0.83859455,\n","         0.28607114, -0.1037252 , -0.12057226, -0.30895178, -0.54026284,\n","        -0.34003745, -0.59285787,  0.60843241,  0.09883667]])"]},"execution_count":53,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["svmLinear1.coef_"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":21918,"status":"ok","timestamp":1609926249962,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"3ubWhUrL6Mpc","outputId":"e23f9386-c415-440b-b0ff-f1b674519a6c","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["array([ True,  True,  True, False,  True, False, False, False,  True,\n","        True, False, False,  True, False])"]},"execution_count":54,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["from sklearn.feature_selection import RFE\n","rfe = RFE(svmLinear1)\n","rfe.fit(X_train_baru,y_train_baru)\n","rfe.support_"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":21915,"status":"ok","timestamp":1609926249963,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"n7fdA44v6T5L","outputId":"81db1b41-6de1-47d6-d5f3-ad2e3326827d","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["Index(['ssc_p', 'hsc_p', 'degree_p', 'mba_p', 'hse_com', 'hse_sci', 'work_ex'], dtype='object')"]},"execution_count":55,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["X.columns[rfe.support_==True]"]},{"cell_type":"markdown","metadata":{"id":"gFpQdbEuL1W7"},"source":["### Logistic Regression"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Mmku1yMaLAkC","vscode":{"languageId":"python"}},"outputs":[],"source":["from sklearn.linear_model import LogisticRegression"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":22396,"status":"ok","timestamp":1609926250459,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"O0m_ASdLMD1m","outputId":"5e0d2425-017b-44cc-cfc4-43594fc6c01b","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["(129, 14) (86, 14) 86\n","acc train0.8449612403100775\n","acc test0.9418604651162791\n","[[22  4]\n"," [ 1 59]]\n","              precision    recall  f1-score   support\n","\n","           0       0.96      0.85      0.90        26\n","           1       0.94      0.98      0.96        60\n","\n","    accuracy                           0.94        86\n","   macro avg       0.95      0.91      0.93        86\n","weighted avg       0.94      0.94      0.94        86\n","\n","[0.76923077 0.84615385 0.92307692 0.76923077 0.76923077 0.84615385\n"," 0.69230769 0.92307692 0.76923077 0.83333333]\n"]}],"source":["X_trains, X_tests, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=1)\n","print(X_trains.shape, X_tests.shape, len(y_test))\n","\n","sc = StandardScaler()\n","X_train = sc.fit_transform(X_trains)\n","X_test = sc.transform(X_tests)\n","\n","lr = LogisticRegression(C=1)\n","lr.fit(X_train, y_train)\n","y_train2 = lr.predict(X_train)\n","y_pred = lr.predict(X_test)\n","print('acc train' + str(accuracy_score(y_train, y_train2)))\n","print('acc test' + str(accuracy_score(y_test, y_pred)))\n","print(confusion_matrix(y_test, y_pred))\n","print(classification_report(y_test, y_pred))\n","print(cross_val_score(lr, X_train, y_train, cv=10))\n","cv1 = cross_val_score(lr, X_train, y_train, cv=10)"]},{"cell_type":"markdown","metadata":{"id":"0wn4bSRtll9O"},"source":["### Logistic Regression dengan SMOTE"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":22393,"status":"ok","timestamp":1609926250460,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"u0y8OoRDlrrs","outputId":"880a0a9d-115f-436b-dd41-b925739d9bc5","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["(177, 14) (119, 14) 86\n","acc train0.8757062146892656\n","acc test0.907563025210084\n","[[61  6]\n"," [ 5 47]]\n","              precision    recall  f1-score   support\n","\n","           0       0.92      0.91      0.92        67\n","           1       0.89      0.90      0.90        52\n","\n","    accuracy                           0.91       119\n","   macro avg       0.91      0.91      0.91       119\n","weighted avg       0.91      0.91      0.91       119\n","\n","[0.77777778 0.88888889 0.88888889 0.77777778 0.94444444 0.77777778\n"," 0.83333333 0.88235294 0.88235294 0.76470588]\n"]}],"source":["X_trains, X_tests, y_train_baru, y_test_baru = train_test_split(X_baru, y_baru, test_size=0.4, random_state=1)\n","print(X_trains.shape, X_tests.shape, len(y_test))\n","\n","sc = StandardScaler()\n","X_train_baru = sc.fit_transform(X_trains)\n","X_test_baru = sc.transform(X_tests)\n","\n","lr1 = LogisticRegression(C=1)\n","lr1.fit(X_train_baru, y_train_baru)\n","y_train2 = svmLinear1.predict(X_train_baru)\n","y_pred = svmLinear1.predict(X_test_baru)\n","print('acc train' + str(accuracy_score(y_train_baru, y_train2)))\n","print('acc test' + str(accuracy_score(y_test_baru, y_pred)))\n","print(confusion_matrix(y_test_baru, y_pred))\n","print(classification_report(y_test_baru, y_pred))\n","print(cross_val_score(lr1, X_train_baru, y_train_baru, cv=10))\n","cv_lrSMOTE = cross_val_score(lr1, X_train_baru, y_train_baru, cv=10)"]},{"cell_type":"markdown","metadata":{"id":"v1O4qKk0OoOI"},"source":["### Kesimpulan Hasil Klasifikasi"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"23rtxJ5899-s","vscode":{"languageId":"python"}},"outputs":[],"source":["from sklearn.naive_bayes import GaussianNB\n","from sklearn import tree\n","from sklearn.ensemble import RandomForestClassifier"]},{"cell_type":"markdown","metadata":{"id":"boXRm0bccB4E"},"source":["Akan dibandingkan beberapa model untuk mengklasifikasi data SMOTE dengan parameter default "]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":432},"executionInfo":{"elapsed":23833,"status":"ok","timestamp":1609926251905,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"ViGDAUrB9qF4","outputId":"98d5e89c-9e5a-4d8f-ab58-f5efb70731e0","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["Regresi Logistik [0.8333333333333334, 0.8888888888888888, 0.8333333333333334, 0.7777777777777778]\n","Naive Bayes [0.9444444444444444, 0.7222222222222222, 0.5555555555555556, 0.7777777777777778]\n","Decision Tree [0.8333333333333334, 0.6666666666666666, 0.7777777777777778, 0.8888888888888888]\n","Random Forest [0.8888888888888888, 0.9444444444444444, 0.7222222222222222, 0.8333333333333334]\n","SVM [0.8333333333333334, 0.9444444444444444, 0.8333333333333334, 0.7777777777777778]\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 576x396 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["clf = LogisticRegression(solver='liblinear')\n","gnb = GaussianNB()\n","dt = tree.DecisionTreeClassifier()\n","rf = RandomForestClassifier()\n","svm_ = svm.SVC()\n","\n","Models = [('Regresi Logistik', clf), ('Naive Bayes',gnb), ('Decision Tree', dt), ('Random Forest', rf), ('SVM', svm_)]\n","Scores = {}\n","for model_name, model in Models:\n","    Scores[model_name] = cross_val_score(model, X_train_baru, y_train_baru, cv=10, scoring='accuracy')\n","\n","dt = pd.DataFrame.from_dict(Scores)\n","ax = sns.boxplot(data=dt)\n","for m, s in Scores.items():\n","    print(m, list(s)[:4])"]},{"cell_type":"markdown","metadata":{"id":"hsnfX98TccrA"},"source":["Terlihat bahwa logistic regression dan support vector machine menghasilkan *worst case* hasil akurasi terbaik di antara beberapa model."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":381},"executionInfo":{"elapsed":25200,"status":"ok","timestamp":1609926253278,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"SzVRgrlB-bLD","outputId":"d236f0dd-98e2-4859-85ea-9bb066fe9d33","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["Regresi Logistik [0.7777777777777778, 0.8888888888888888, 0.8888888888888888, 0.7777777777777778]\n","SVM [0.8333333333333334, 0.8333333333333334, 0.8888888888888888, 0.7777777777777778]\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 576x396 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["#Dengan C=1\n","Models = [('Regresi Logistik', lr1), ('SVM', svmLinear1)]\n","Scores = {}\n","for model_name, model in Models:\n","    Scores[model_name] = cross_val_score(model, X_train_baru, y_train_baru, cv=10, scoring='accuracy')\n","\n","dt = pd.DataFrame.from_dict(Scores)\n","ax = sns.boxplot(data=dt)\n","for m, s in Scores.items():\n","    print(m, list(s)[:4])"]},{"cell_type":"markdown","metadata":{"id":"VDqFHBdtr40e"},"source":["Hasil *cross validation 10-folds* yang terbaik dihasilkan oleh Support vector Machines. Akan dicari *feature importance* dengan *recursive feature elimination*."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":25170,"status":"ok","timestamp":1609926253295,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"AZDPcn9_OypW","outputId":"dc8cb300-b2d0-4fc9-9f16-0a8a082c22ee","vscode":{"languageId":"python"}},"outputs":[{"name":"stdout","output_type":"stream","text":["[[ 1.6854108   0.40222026  0.76137156 -0.07061094 -0.83859455  0.28607114\n","  -0.1037252  -0.12057226 -0.30895178 -0.54026284 -0.34003745 -0.59285787\n","   0.60843241  0.09883667]]\n"]},{"data":{"text/plain":["Index(['ssc_p', 'hsc_p', 'degree_p', 'mba_p', 'hse_com', 'hse_sci', 'work_ex'], dtype='object')"]},"execution_count":71,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["from sklearn.feature_selection import RFE\n","print(svmLinear1.coef_)\n","rfe = RFE(svmLinear1)\n","rfe.fit(X_train_baru, y_train_baru)\n","rfe.support_\n","X.columns[rfe.support_==True]"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":25165,"status":"ok","timestamp":1609926253296,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"kAr2gJb203pR","outputId":"13f6fb36-4fc7-4370-874f-5060946051ed","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["array([1, 1, 1, 8, 1, 2, 7, 5, 1, 1, 4, 3, 1, 6])"]},"execution_count":72,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["rfe.ranking_"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":25163,"status":"ok","timestamp":1609926253298,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"HJz2GjQ816X1","outputId":"630470f0-5152-4227-d5bc-3d1eb8d651d3","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["array([ 1.6854108 ,  0.40222026,  0.76137156, -0.07061094, -0.83859455,\n","        0.28607114, -0.1037252 , -0.12057226, -0.30895178, -0.54026284,\n","       -0.34003745, -0.59285787,  0.60843241,  0.09883667])"]},"execution_count":73,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["svmLinear1.coef_[0]"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1758,"status":"ok","timestamp":1609931440158,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"-LUWv67i1HTp","outputId":"705dd3b5-1edb-4aac-8b17-348bbd205320","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/plain":["[1.6854107959243692,\n"," 0.40222025930044486,\n"," 0.7613715608250955,\n"," 0.07061093618725711,\n"," 0.8385945508090834,\n"," 0.28607113641765813,\n"," 0.10372519907285316,\n"," 0.12057225740670374,\n"," 0.30895177704897936,\n"," 0.5402628361136723,\n"," 0.34003744750542897,\n"," 0.5928578692798798,\n"," 0.6084324063698552,\n"," 0.09883666711440531]"]},"execution_count":145,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["feature_importance = []\n","for i in range(14):\n","  a = np.abs((svmLinear1.coef_[0][i]))\n","  feature_importance.append(a)\n","feature_importance"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":483},"executionInfo":{"elapsed":1113,"status":"ok","timestamp":1609931446444,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"XkyBRudj2C-L","outputId":"1e8b354a-4ab9-4203-8398-6442e3550826","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>0</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1.685411</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0.402220</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.761372</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.070611</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.838595</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>0.286071</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>0.103725</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>0.120572</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>0.308952</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>0.540263</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>0.340037</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>0.592858</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>0.608432</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>0.098837</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["           0\n","0   1.685411\n","1   0.402220\n","2   0.761372\n","3   0.070611\n","4   0.838595\n","5   0.286071\n","6   0.103725\n","7   0.120572\n","8   0.308952\n","9   0.540263\n","10  0.340037\n","11  0.592858\n","12  0.608432\n","13  0.098837"]},"execution_count":146,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["f_i = pd.DataFrame(feature_importance)\n","f_i"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"aXKnP87f0gLi","vscode":{"languageId":"python"}},"outputs":[],"source":["kolom = pd.DataFrame(['ssc_p', 'hsc_p', 'degree_p', 'etest_p', 'mba_p', 'M', 'bse', 'bhse',\n","       'hse_com', 'hse_sci', 'deg_com', 'deg_sci', 'work_ex',\n","       'master_jurusan'])"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"U5QGdOO32QFA","vscode":{"languageId":"python"}},"outputs":[],"source":["fitur_penting = pd.concat([kolom, f_i], axis=1)\n","fitur_penting.columns = ['feature', 'score']"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":204},"executionInfo":{"elapsed":700,"status":"ok","timestamp":1609931452785,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"IDa90y_X2iG6","outputId":"1809cc6a-b9d5-4d2e-9fff-1e2a236011b1","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>feature</th>\n","      <th>score</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>ssc_p</td>\n","      <td>1.685411</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>hsc_p</td>\n","      <td>0.402220</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>degree_p</td>\n","      <td>0.761372</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>etest_p</td>\n","      <td>0.070611</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>mba_p</td>\n","      <td>0.838595</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["    feature     score\n","0     ssc_p  1.685411\n","1     hsc_p  0.402220\n","2  degree_p  0.761372\n","3   etest_p  0.070611\n","4     mba_p  0.838595"]},"execution_count":149,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["fitur_penting.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"CecLPXBH2s7c","vscode":{"languageId":"python"}},"outputs":[],"source":[" fp = fitur_penting.sort_values(by=['score'], ascending=False)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":266},"executionInfo":{"elapsed":1115,"status":"ok","timestamp":1609931571383,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"mOqH3eaO3cSP","outputId":"e3fece96-4fff-40e8-9dfb-e5f27def3fd1","vscode":{"languageId":"python"}},"outputs":[{"data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>feature</th>\n","      <th>score</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>ssc_p</td>\n","      <td>1.685411</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>mba_p</td>\n","      <td>0.838595</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>degree_p</td>\n","      <td>0.761372</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>work_ex</td>\n","      <td>0.608432</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>deg_sci</td>\n","      <td>0.592858</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>hse_sci</td>\n","      <td>0.540263</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>hsc_p</td>\n","      <td>0.402220</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["     feature     score\n","0      ssc_p  1.685411\n","4      mba_p  0.838595\n","2   degree_p  0.761372\n","12   work_ex  0.608432\n","11   deg_sci  0.592858\n","9    hse_sci  0.540263\n","1      hsc_p  0.402220"]},"execution_count":153,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["fp.iloc[0:7]"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":371},"executionInfo":{"elapsed":1185,"status":"ok","timestamp":1609931592314,"user":{"displayName":"Muhammad Ilham Randi","photoUrl":"","userId":"14623713417543616408"},"user_tz":-420},"id":"JSnYUmXl3N-d","outputId":"f0ab23e1-3e0f-42f6-997a-f2dfdbb6f3a5","vscode":{"languageId":"python"}},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 576x396 with 1 Axes>"]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["p = sns.barplot(x='feature', y='score', data=fp.iloc[0:7])"]},{"cell_type":"markdown","metadata":{"id":"cwRSghXrQa3z"},"source":["Setelah melakukan *recursive feature elimination* menggunakan model terbaik dari klasifikasi sebelumnya, didapatkan dari SVM *Classifier* bahwa:"]},{"cell_type":"markdown","metadata":{"id":"d8oygqcyQgYf"},"source":["Faktor - faktor yang paling mempengaruhi klasifikasi diterima kerja atau tidak adalah sebagai berikut:\n","* Persentase Nilai setelah lulus dari Secondary Education 10th\n","* Persentase Nilai setelah lulus dari High Secondary Education 12th\n","* Persentase Nilai setelah lulus dari Undergraduate Education\n","* Persentase Nilai setelah lulus dari Master Business Academy\n","* Peminatan saat 12th grade\n","* Jurusan yang diambil saat Undergraduate Education\n","* Pengalaman Kerja\n"]}],"metadata":{"colab":{"collapsed_sections":["9ONTM-d_KBDW","1ci6yJvim4dJ","JiSuembVn4bA","70V8hkiaoSzB","W7yYVFVLBZfX","9YtO_49jszhv","-7h2fnAPLAWX","XLGSa9b5wYVh","HlRpCQH5ZajC","w2IIcOcn3ykY","gFpQdbEuL1W7","0wn4bSRtll9O"],"name":"campus_recruitment_kaggle.ipynb","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"}},"nbformat":4,"nbformat_minor":0}