🏢 AI-Powered HRMS & Employee Attrition Predictor

📌 Overview

This project is a comprehensive Full-Stack Human Resources Management System (HRMS) integrated with a Data Mining and AI model. It is designed to predict employee attrition (turnover) and help HR departments make data-driven decisions to retain top talent.

🚀 Key Features

• Employee Attrition Prediction: Utilizes a machine learning model trained on an expanded HR dataset (3170 records, 35 features) to predict whether an employee is likely to leave the company.
• Modern HR Dashboard: A responsive and interactive frontend built with React (Vite), featuring pages for Employee Management, Recruitment (İşe Alım), and Settings.
• Robust Backend: A Node.js/Express server handling API requests and serving the AI predictions.
• Data-Driven Insights: Analyzes factors like Job Satisfaction, Monthly Income, Overtime, and Distance From Home to provide actionable HR insights.

🛠️ Tech Stack

• Frontend: React, Vite, CSS Modules
• Backend: Node.js, Express.js (server.js)
• Data Mining & AI: Python, Pandas, Scikit-learn (Model training phase)
• Dataset: Expanded HR Employee Attrition Dataset (3170 rows)

📂 Project Structure

HRMS-AI-Attrition-Predictor/
│
├── client/                     # Frontend React Application
│   ├── src/                    # Components (EmployeePage, LoginPage, etc.)
│   └── package.json            
│
├── server/                     # Backend Node.js API
│   └── server.js               
│
└── data_and_docs/              # Datasets and Academic Documents
    ├── HR_Dataset_Expanded.csv # 35-feature employee dataset
    ├── makale_turkce.docx      # Academic research paper (TR)
    └── afis.jpg                # Project poster

    cd server
npm install
node server.js

cd client
npm install
npm run dev