{
"name" : "Wisnu Alfian Nur Ashar",
"nickname" : "wi5nuu",
"location" : "Bekasi Kota, West Java",
"education" : "B.IT Student, President University",
"role" : "Full-Stack Engineer",
"currently" : ["Ashar Grosir Parfum (ERP/POS)", "GAOTEK INC (Intern)"],
"interests" : ["Enterprise Systems", "AI/ML", "Cybersecurity"],
"available" : true
}- Architecting an enterprise ERP/POS platform serving 15,000+ users at Ashar Grosir Parfum
- Interning remotely as a Web Development Intern at GAOTEK INC (New York)
- Exploring AI/ML integration and applied cybersecurity as an OWASP Foundation member
- Mastering cloud infrastructure on AWS & GCP
Go · Laravel · Next.js · Java/Spring · Docker · PostgreSQL · Cybersecurity
"Any fool can write code that a computer can understand. Good programmers write code that humans can understand." — Martin Fowler
🏆 Ashar Grosir Parfum — Enterprise ERP/POS Platform (Production)
Unified business management system for a 20-year-old perfume wholesaler — inventory, purchasing, payroll, attendance, BI dashboards, an AI Copilot, and role-based access control in one platform.
- Serving 15,000+ users, 6 admins, 600+ products, 50+ active resellers
- 1.34s average page load, 91% Good LCP via Cloudflare CDN + query optimization
- Automated wholesale ops end-to-end, cutting manual financial reconciliation time by 60%
- Supports 100+ daily transactions
Laravel Next.js PostgreSQL Cloudflare AI Copilot RBAC
🛰️ SENTINEL-X — Multi-Domain Threat Intelligence Platform (Proof of Concept)
Integrated situational-awareness and fusion platform for real-time, AI-correlated incident response across Aviation, Maritime, Cyber, Space, Seismic, and RF/SIGINT domains.
- Multi-modal AI correlation engine across six intelligence domains
- Real-time event pipeline with Kafka + TimescaleDB
- Blockchain-backed audit integrity, containerized with Docker
FastAPI React PyTorch Kafka TimescaleDB Blockchain Docker
🔬 ColonyAI — Automated Plate Count Reader (Production)
AI-powered microbiology tool that converts agar plate images into standardized CFU/ml lab reports, fine-tuned on a custom YOLOv8 model.
- 94.1% mAP@0.5, 94.7% precision, 92.5% recall across 56,124 annotated bounding boxes
- Reduces inter-analyst variability by 92.5%, report generation under 2 minutes
- SHA-256 chained audit trail for ISO 17025 compliance; BPOM/SNI-compliant PDF/CSV output
YOLOv8 FastAPI Next.js PostgreSQL OpenCV AWS S3 Railway
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