Systems built to last.
Full-stack web applications architected from data model to deployment — role-based access, structured PostgreSQL schemas, RESTful APIs, and cloud infrastructure. Each project solves a real institutional or environmental problem with production-grade tooling.
3
Projects
2
Live in production
3+
Tech stacks
LiveFull Stack
LPPM Research Management System
Full Stack Web Developer
May 2025 – Oct 2025- Developed a full-stack institutional data management system for the university's LPPM with role-based access (Admin & Faculty) and an approval workflow — mirroring structured financial approval processes.
- Designed and managed a PostgreSQL database schema using Prisma ORM, supporting 5+ modules for research and community service data with strict data integrity.
- Implemented data export to Excel for institutional reporting — a pattern directly applicable to financial reporting and audit-trail workflows.
Key highlights
- Role-based access control with Admin & Faculty permission tiers
- 5+ data modules with full CRUD and multi-step approval workflow
- Excel export for institutional audit-trail reporting
Tech stack
Next.jsPostgreSQLTypeScriptPrisma ORMNextAuth.jsExcel Export
LiveFull Stack
Geopark Merangin Information System
Full Stack Web Developer — Final Thesis (Skripsi)
Feb 2025 – Oct 2025- Built a web-based information system with structured location and environmental data management using PostgreSQL — demonstrating end-to-end data lifecycle handling.
- Deployed via Vercel with Next.js and TypeScript, ensuring reliable and scalable data access for public-facing reporting.
Key highlights
- Geospatial data management for Merangin Geopark locations
- Public-facing system deployed on Vercel with PostgreSQL backend
- Final thesis project with end-to-end data lifecycle design
Tech stack
Next.jsTypeScriptPostgreSQLVercel
ArchivedCloud
Eco Sense Smart Environmental App
Cloud Computing Lead — Bangkit Academy Capstone
Nov 2024 – Dec 2024- Led cloud architecture (GCP) for a geospatial data processing system serving real-time satellite datasets, applying data pipeline principles transferable to financial data flows.
- Built a RESTful API (Flask) integrating Random Forest and K-Means models, demonstrating quantitative data analysis capabilities relevant to financial forecasting.
Key highlights
- Led GCP cloud architecture for real-time satellite data processing
- RESTful API with Random Forest & K-Means ML model integration
- Bangkit Academy capstone — graded by Google, GoTo & Traveloka engineers
Tech stack
PythonFlaskGCPTensorFlowScikit-learnPandasNumPy
New projects get added here as they ship — internal tools, data dashboards, and API services join this same page once they're production-ready.