My Projects
A collection of projects I've worked on, from full-stack applications to open-source contributions. Each project represents my passion for building impactful digital experiences.
FeaturedOilPalmVision.ai : Automating Oil Palm Census
OilPalmVision is an AI SaaS platform designed to automate oil palm tree census and Management. By leveraging YOLOv8 computer vision and geospatial processing, it transforms drone and satellite imagery into actionable plantation insights, including precise tree counts, GPS coordinates, and Stand Per Hectare (SPH) metrics
FeaturedFINARA: Integrated Retail & Warehouse Management System with Automated Accounting
FINARA is a comprehensive business management platform that unifies retail operations (Point of Sale), multi-location inventory management, and a professional accounting suite into a single integrated ecosystem. Developed using Next.js 15, React 19, and PostgreSQL, the system is designed to automate financial recording from every business transaction in real-time
FeaturedIndoDoc Vision: Automated Kartu Keluarga Extraction with State-of-the-Art A
IndoDoc Vision is a pipeline designed to extract structured JSON data from Indonesian Family Card (Kartu Keluarga) documents. By integrating YOLOv8, U-Net, and Gemini VLM, the system achieves >95% field-level accuracy.
FeaturedTrafficSense: AI-Powered Smart Traffic Analytics for Urban Area
A real-time traffic density analysis system for Malang City intersections that integrates Edge Intelligence (YOLOv11 & ByteTrack) with Kappa Architecture (Apache Spark & Kafka) to deliver high-precision insights on resource-constrained hardware
FeaturedCourtsight - Indonesia Supreme Court AI Agent
CourtSight is a revolutionary AI-powered legal intelligence platform designed to democratize access to legal information in Southeast Asia. The platform transforms complex Supreme Court decision documents into searchable and understandable insights, making justice more transparent and inclusive.
Sistem Klasifikasi Sampah Cerdas Berbasis Deep Learning dengan Integrasi Mekanisme Atensi
Proyek ini mengimplementasikan solusi Deep Learning mutakhir untuk klasifikasi sampah otomatis, membedakan antara sampah Organik dan Daur Ulang. Inti dari solusi ini adalah arsitektur ResNet-34 yang dimodifikasi dengan Convolutional Block Attention Module (CBAM). Integrasi CBAM memungkinkan model untuk memfokuskan "perhatian" pada fitur visual yang relevan (seperti bentuk dan tekstur objek) sambil menekan noise dari latar belakang yang kompleks. Hasilnya adalah model yang lebih akurat dan robust dibandingkan arsitektur CNN standar.
6
Projects Completed
3+
Years Experience
20+
Technologies Used
20+
GitHub Stars
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