https://github.com/gdapriana/kelayakan-pinjaman-backend
Sisi backend untuk sistem penentu keputusan kelayakan seseorang mendapatkan pinjaman dengan metode fuzzy tsukamoto
https://github.com/gdapriana/kelayakan-pinjaman-backend
fuzzy-logic python tsukamoto
Last synced: about 2 months ago
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Sisi backend untuk sistem penentu keputusan kelayakan seseorang mendapatkan pinjaman dengan metode fuzzy tsukamoto
- Host: GitHub
- URL: https://github.com/gdapriana/kelayakan-pinjaman-backend
- Owner: gdapriana
- Created: 2024-11-22T13:38:01.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-12-22T15:53:18.000Z (5 months ago)
- Last Synced: 2025-02-08T12:46:34.423Z (4 months ago)
- Topics: fuzzy-logic, python, tsukamoto
- Language: Python
- Homepage: https://kelayakan-pinjaman-backend.vercel.app
- Size: 196 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Loan Eligibility Backend
## 🏦 Project Overview
This backend application determines loan eligibility using the Fuzzy Tsukamoto method. It provides intelligent loan assessment based on multiple financial parameters.
### Fuzzy Preparation [Here](/fuzzy-information.md)
## 🚀 Project Demo
- **Backend Server:** [kelayakan-pinjaman-backend.vercel.app](https://kelayakan-pinjaman-backend.vercel.app)
- **Frontend Application:** [kelayakanpinjaman.vercel.app/](https://kelayakanpinjaman.vercel.app/)
- **Frontend Repository:** [github/gdapriana/kelayakan-pinjaman-frontend](https://github.com/gdapriana/kelayakan-pinjaman-frontend)
## 📂 Project Structure
```
kelayakan-pinjaman-backend/
│
├── dataset/ # Contains project datasets
├── resources/
│ ├── fuzzy.py # Fuzzy Tsukamoto logic implementation
│ ├── member.py # Project team information
│ └── preprocessing.py # Data preprocessing utilities
└── app.py # Main application entry point
```
## 🔍 API Endpoints
### 1. Predict Loan Eligibility
- **URL:** `/predict`
- **Method:** `POST`
- **Request Body:**
```json
{
"pendapatan": float,
"usia": int,
"tanggungan": int,
"pengeluaran": float,
"aset": float
}
```
### 2. Dataset Information
- **URL:** `/dataset`
- **Method:** `GET`
- **Description:** Provides details about the dataset used for loan eligibility prediction
### 3. Team Members
- **URL:** `/member`
- **Method:** `GET`
- **Description:** Returns information about the project team
## 🧠 Methodology
The application uses the Fuzzy Tsukamoto method to assess loan eligibility. This approach allows for intelligent and nuanced decision-making by:
- Converting crisp input values to fuzzy input
- Applying fuzzy inference rules
- Defuzzifying results to determine loan eligibility
## 🛠️ Technologies Used
- Python
- Flask
- Fuzzy Logic
- Vercel (Deployment)
## 👥 Team
For detailed team information, please check the `/member` endpoint or contact the repository maintainers.
## 🤝 Contributing
Interested in contributing? Please read our contributing guidelines and feel free to submit pull requests.