Skripsi Arip - Web Application for Thesis Process

Project Description: PharmaTrend - Predicting Medicine Stock using K-Means and Trend Moment

PharmaTrend is an innovative web application developed using PHP, Tailwind CSS, and HTML, aimed at addressing the challenges faced by Pharmaceutical Wholesale Distributors (PBF) in accurately forecasting medicine demand and managing stock efficiently. In the highly competitive business landscape, the timely processing and delivery of information are critical factors for a company's success, and PharmaTrend aims to provide a reliable solution to enhance efficiency in data processing.

Objectives: The primary objective of PharmaTrend is to implement the K-Means clustering method and Trend Moment technique to predict medicine stock at PT. Lestari Jaya Farma. Through K-Means clustering, the application categorizes data into high, medium, and low clusters, enabling a better understanding of medicine demand patterns. The Trend Moment method is then applied to forecast demand trends based on historical sales data, facilitating effective inventory management.

Methodology: The project involves two key methodologies:

1. K-Means Clustering: This method is utilized to cluster the data, classifying 100 medicine items into high, medium, and low-demand categories. The clustering results in 42 high-demand, 32 medium-demand, and 24 low-demand medicine items, allowing PT. Lestari Jaya Farma to prioritize their inventory and respond to customer needs efficiently.

2. Trend Moment Prediction: The Trend Moment technique is employed to predict demand trends based on historical sales data. By analyzing past sales patterns, PharmaTrend provides accurate forecasts, helping the company optimize their inventory levels and minimize stockouts.

Results and Impact: The data processing results in PharmaTrend have been impressive. The Trend Moment predictions were evaluated, revealing a Mean Absolute Percentage Error (MAPE) of 1.30% and an accuracy rate of 98.70%. These remarkable results demonstrate the effectiveness and reliability of the predictive capabilities of the application.

Conclusion: PharmaTrend showcases the successful implementation of advanced data processing techniques to predict medicine stock and demand trends for PT. Lestari Jaya Farma. By utilizing K-Means clustering and Trend Moment prediction, the application empowers the company to make informed decisions, streamline inventory management, and ensure a seamless supply chain. It revolutionizes the way pharmaceutical distributors handle their stock and contributes significantly to PT. Lestari Jaya Farma's success in the highly competitive market.

Join PharmaTrend today to stay ahead in the pharmaceutical industry and revolutionize your inventory management!

Preparation for the project

1. Install NodeJS, website: https://nodejs.org/en/
2. Install XAMPP, website: https://www.apachefriends.org/download.html
3. Install Git, website: https://git-scm.com/downloads
4. Install Visual Studio Code, website: https://code.visualstudio.com/download
5. Install Extensions Taiwind CSS IntelliSense, website: https://marketplace.visualstudio.com/items?itemName=bradlc.vscode-tailwindcss
6. Install Extensions Live Server, website: https://marketplace.visualstudio.com/items?itemName=ritwickdey.LiveServer
7. Install Extensions PostCSS Language Support, website: https://marketplace.visualstudio.com/items?itemName=csstools.postcss

How to clone the project

1. Open the terminal

2. Change the current working directory to the location where you want the cloned directory.

3. Write the command git clone https://github.com/ikimukti/skripsi-arip.git.

4. Change the current working directory to the cloned directory cd skripsi-arip.

5. Open the project in Visual Studio Code with the command code ..

6. npm install -D tailwindcss@latest postcss@latest autoprefixer@latest to install tailwindcss

   added 92 packages, and audited 93 packages in 2s
   
   19 packages are looking for funding
   run `npm fund` for details
   
   found 0 vulnerabilities
   

7. npx tailwindcss init -p to create tailwind.config.js

   tailwindcss 2.2.7
   
   ✅ Created Tailwind config file: tailwind.config.js
   ✅ Created PostCSS config file: postcss.config.js
   

   or

   tailwind.config.js already exists.
   postcss.config.js already exists.
   

8. npx tailwindcss build src/css/input.css -o public/css/output.css to create public/styles.css

   tailwindcss 2.2.7
   
   ✅ Generated public/css/output.css successfully.
   

   or

   public/css/output.css already exists.
   

9. npm run build to create public/bundle.js or npm run dev to create public/bundle.js and watch for changes

10. Open the project in Visual Studio Code with the command code .

11. Run XAMPP and start Apache and MySQL

12. Open the browser and go to http://localhost/phpmyadmin/

13. Create a database with the name skripsi-arip

14. import the database file skripsi-arip.sql in the database folder

15. Open web browser icognito mode and go to http://localhost/skripsi-arip/public/