Petik Sendiri
Empowering agricultural yield through on-device machine learning and smart harvesting workflows.
Product Engineer
Product Engineering × Computer Vision × AgriTech
Translating technology into business solutions and integrating the product with Flutter.
2024
Hackathon — DINACOM 11.0
Agricultural yield loss often stems from subjective ripeness assessment and inefficient harvest schedules. Serving as Product Engineer for Petik Sendiri, I spearheaded the translation of machine learning and computer vision into accessible business solutions for farmers and agronomists. We built a high-performance Flutter mobile application featuring real-time on-device machine learning models for crop health analysis, ripeness grading, and optimized harvest logistics.
Lectura Edu
CSR — Tanoto Foundation