Selected Work
All projects
14 projects across machine learning, computer vision, and full-stack engineering.
ML Shale Shaker Cutting Estimations
Internship Machine Learning Engineer
This project involved developing a computer vision system to monitor and analyze rock cuttings from shale shakers in real-time using CCTV footage. The system was designed to improve the efficiency and accuracy of drilling process monitoring by providing real-time data on rock coverage and composition, thereby supporting operational decision-making in the oil and gas industry.
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ML Aerial Image Segmentation
Computer Vision Engineer
This research project explores aerial image segmentation techniques using computer vision and deep learning to map geographic features from satellite or drone imagery for my UAV Team's research at the University. The focus was on developing segmentation models to detect and classify objects such as buildings, roads, and vegetation, providing insights for geospatial analysis.
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ML Tomato Leaf Disease Detection
Machine Learning Engineer
Developed a lightweight deep learning model using TensorFlow Lite to detect diseases in tomato leaves from images. The model, based on transfer learning with MobileNetV2, achieves high accuracy with a compact size, suitable for deployment on resource-constrained devices.
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ML Prototype Chicken Detection Model
Computer Vision Engineer
Computer vision system to detect and count chickens in real-time for poultry monitoring. Built using Python, Detectron2, and PyTorch, this prototype employs a RetinaNet model with a ResNet-50 FPN backbone, optimized through dynamic quantization and structured pruning.
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DE Forex Data Monitoring Dashboard
Data Engineer
A real-time dashboard for monitoring forex price fluctuations with automated Telegram bot notifications for price updates. Built using Python for data processing, Grafana for visualization, Docker for containerization, and PostgreSQL for data storage.
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DE AI - Sentiment Hub
Data Engineer
Real-time sentiment analysis dashboard with ETL pipeline for scraping raw news data from News API, focusing on AI, blockchain, finance, Forex, and investment topics. Utilizes BERT and VADER models for sentiment analysis, Python for data processing, React JS for the frontend, FastAPI for the backend, Swagger for API documentation, PostgreSQL and Supabase for data storage, and Render for API deployment.
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ML Road Line Detection
Machine Learning Engineer
This project developed a model to detect road lane markings from image and video inputs at the Samsung Innovation Campus Batch 5 competition. The system was deployed using Streamlit, providing an interactive web interface for users to upload inputs and visualize detected lane lines in image and video processing, with potential applications in navigation and autonomous driving systems.
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IoT SleepSense IoT Device for Sleep Apnea Monitoring
IoT Engineer
Developed SleepSense, an end-to-end IoT solution for affordable, at-home early detection and rehabilitation of Obstructive Sleep Apnea (OSA). The system integrates an ergonomic belt-thorax sensor for real-time ECG and respiratory pattern monitoring, and a wireless pulse oximeter for continuous tracking of blood oxygen levels and heart rate. Data is processed on a web-based platform with AI-driven analysis, clinical reporting, and direct access for doctors.
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IoT IoT Football Movement Tracker
IoT Engineer
Developed an IoT device to track football players' movement patterns during matches. The device, attached to the back of players' jerseys, records real-time movement data and stores it locally on an SD card in Excel format for subsequent analysis on a dedicated web platform.
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Mobile BIN-GO! Waste Management App
Android Developer
Developed BIN-GO!, a mobile application to address the waste crisis in Yogyakarta. The app integrates Google Maps to locate nearby recycling centers, provides a community forum for waste management discussions, includes a reporting feature for environmental issues, and incorporates gamification to promote sustainable behaviors.
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PM Broiler Monitoring v.1
Project Manager
Led the development of Broiler Monitoring (BroMo) v.1, a web-based information system designed to monitor poultry farms effectively. The application enables real-time monitoring of farm conditions for owners and workers, enhancing operational efficiency.
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PM Broiler Monitoring v.2
Project Manager
Managed the development of Broiler Monitoring v.2, focusing on enhancing the user interface with a cleaner design and improved functionality. The project involved migrating the frontend framework from Laravel to Next.js while maintaining Laravel for the database API, ensuring a modern and efficient application.
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QA BWA Web Testing
Quality Assurance
Conducted quality assurance testing for a web application as part of a course, focusing on creating and executing test cases for two case studies to ensure functionality and reliability of the BuildWithAngga platform.
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QA Tokopedia Web Testing
Quality Assurance
Conducted quality assurance testing for the Tokopedia e-commerce platform, focusing on creating and executing three test cases (positive and negative scenarios) to validate the functionality of adding items to the wishlist, adding items to the cart, and performing checkout.
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