Machine Learning Bangkit Academy Capstone

BADI: Building a Business Analytics Solution with Machine Learning

July 20, 2022 • 6 min read

During my time at Bangkit Academy, Google's premier machine learning program in Indonesia, I had the opportunity to lead the development of BADI (Business Analytics Daily Income)—a product-based capstone project that applied machine learning to solve real business problems.

The Problem

Small and medium businesses often struggle with understanding their income patterns and making data-driven decisions. Many lack the technical expertise or resources to implement sophisticated analytics solutions. We wanted to create an accessible tool that could help businesses:

  • Track and visualize their daily income patterns
  • Predict future income trends
  • Identify factors affecting their business performance
  • Make informed decisions based on data insights

Our Solution

BADI is a comprehensive business analytics platform that combines data visualization with machine learning-powered predictions. The system includes:

  1. Data Collection: Easy-to-use interface for recording daily sales and income data
  2. Analytics Dashboard: Visual representations of business trends over time
  3. ML Prediction Engine: Income forecasting using regression models
  4. Insights Generator: Actionable recommendations based on data analysis

Technical Implementation

The project was built using a modern tech stack:

  • Backend: Python with Flask for API development
  • ML Pipeline: Scikit-learn for model training and inference
  • Data Processing: Pandas and NumPy for data manipulation
  • Model Deployment: TensorFlow for production-ready models

Key Features

BADI includes several innovative features that set it apart:

  • Time Series Forecasting: Predict income trends for the next 7-30 days
  • Anomaly Detection: Automatically flag unusual income patterns
  • Seasonal Analysis: Identify peak and low-performing periods
  • Comparative Analytics: Compare performance across different time periods

Team Collaboration

As the ML lead, I coordinated with team members across three learning paths:

  • Machine Learning: Model development and optimization
  • Mobile Development: Android app interface
  • Cloud Computing: Backend infrastructure and deployment

Results & Learnings

The project was successfully completed and presented as part of the Bangkit Academy graduation. Key achievements include:

  • Working prototype with functional ML predictions
  • User-friendly mobile application
  • Scalable cloud infrastructure
  • Comprehensive documentation

This experience taught me valuable lessons about team collaboration, product development lifecycle, and applying ML to real-world problems.

View Project

View Project on GitHub