• 🎯 About Cakradana
• 🏆 TrackAML 2.0 Achievement
• 📚 Repository Overview
• 🛠️ Tech Stack
• ❌ Problems Solved
• ✅ Cakradana Solution
• 🚀 Quick Start
• 🤝 Contributing
• 📞 Contact

Cakradana is an artificial intelligence (AI) system specifically designed to enhance transparency and detect risks in election financing in Indonesia. This platform uses advanced technology to analyze, process, and visualize political donation data in real-time.

The name "Cakradana" is derived from Sanskrit meaning "wheel of giving" - symbolizing the cycle of transparency in a healthy democratic system.

Cakradana was submitted for TrackAML 2.0 Hackathon hosted by PPATK (Pusat Pelaporan dan Analisis Transaksi Keuangan), Indonesia's Financial Transaction Reports and Analysis Center and achieved 🥉 3rd Winner in the Open Sector category.

💰 Prize Awarded: IDR 20,000,000 (~USD 1,200) for our innovative AI-powered solution for election finance transparency.

This recognition validates our commitment to building innovative solutions for financial transparency and anti-money laundering in Indonesia's electoral system.

Cakradana consists of three main repositories, each serving a specific purpose in the ecosystem:

AI/ML Engine for Risk Detection

• Purpose: Core machine learning system for detecting risky political donations
• Features:
  • LightGBM-based risk scoring model
  • Feature engineering (temporal, network, behavioral)
  • Rule-based compliance checks
  • FastAPI service for real-time predictions
• Tech Stack: Python, FastAPI, LightGBM, scikit-learn, pandas
• Model Performance: ROC-AUC 0.84, optimized for recall of risky transactions

Backend API & Data Processing

• Purpose: Central API service handling data ingestion and processing
• Features:
  • Multi-format data input (digital forms, OCR, web scraping)
  • Authentication & user management
  • Network analysis and entity tracking
  • RESTful API with OpenAPI documentation
• Tech Stack: Node.js, Express.js, MongoDB, Tesseract.js, JWT
• Live API: https://api.cakradana.org

Frontend Web Application

• Purpose: User interface for donation monitoring and analytics
• Features:
  • Real-time dashboard with interactive visualizations
  • Network graph visualization
  • Risk analysis reports
  • User authentication and role-based access
• Tech Stack: Next.js, React, TypeScript, Tailwind CSS, Chart.js
• Live Website: https://cakradana.org

• Python 3.10+ - Core programming language
• FastAPI - High-performance API framework
• LightGBM - Gradient boosting for risk detection
• scikit-learn - Machine learning utilities
• pandas - Data manipulation and analysis
• joblib - Model serialization

• Node.js 18+ - Runtime environment
• Express.js - Web application framework
• MongoDB - NoSQL database with Mongoose ODM
• Tesseract.js - OCR for document processing
• JWT - Stateless authentication
• Multer - File upload handling
• Nodemailer - Email service integration

• Next.js 15.4.2 - React framework with App Router
• React 18.3.1 - UI library
• TypeScript 5.0 - Type safety
• Tailwind CSS 3.4.17 - Utility-first CSS framework
• Chart.js - Interactive data visualization
• D3.js - Advanced data visualization
• GSAP - Smooth animations

• Docker - Containerization
• Cloudflare R2 - Object storage
• OpenRouter API - LLM integration
• GitHub - Version control and CI/CD

• Untraceable political donations by conventional systems
• Difficulty accessing information about campaign financing in real-time
• Limitations in analyzing complex donation patterns

• Donation data scattered across various formats (digital, paper, website)
• Slow manual processes in data collection and verification
• Difficulty identifying networks and connections between entities

• Weak early detection of suspicious donation patterns
• Lack of network analysis to identify potential conflicts of interest
• Minimal automated tools for monitoring campaign financing

Cakradana uses AI for:

• Automatic extraction of donation data from various sources
• Pattern analysis and anomaly detection in financing
• Risk prediction based on historical data and network analysis

This platform unifies data from:

• 📱 Digital Forms - Manual input via API
• 📄 Physical Documents - OCR for data extraction from scanned documents
• 🌐 Web Scraping - Automatically collecting data from public websites

• Real-time dashboard for donation monitoring
• Network visualization to see connections between entities
• Automatic risk scoring based on various parameters
• Comprehensive reports in easily understandable formats

• Website: https://cakradana.org
• API Documentation: https://api.cakradana.org

# Clone all repositories
git clone https://github.com/cakradana-app/cakradana-ai.git
git clone https://github.com/cakradana-app/cakradana-api.git
git clone https://github.com/cakradana-app/cakradana-web.git

# Run AI service
cd cakradana-ai
pip install -r requirements.txt
uvicorn app_fastapi:app --host 0.0.0.0 --port 8000

# Run API service
cd ../cakradana-api
npm install
npm run dev

# Run Web application
cd ../cakradana-web
npm install
npm run dev

# Test risk prediction
curl -X POST "http://localhost:8000/predict" \
  -H "Content-Type: application/json" \
  -d '{
    "instances": [{
      "sender_type": "individual",
      "receiver_type": "political-party",
      "amount": 2000000
    }]
  }'