Hybrid Telco • AI/ML LeadHands-on • Management • Pre-Sales • Testing
23+ years in telecom × applied AI/ML. This site is more than a portfolio—it’s the central hub of ARTS (Allan & Ray Techno-Spiritual Hub). I design projects that mirror real-world constraints, then document the journey (dashboards, repos, carousels) so stakeholders can audit progress quickly.

Snapshot: dashboards, embeddings, and PMO visuals
About
Projects
Interactive dashboard for PCAP analysis with anomaly detection, responsive UI, and automated insights.
End-to-end text pipeline: tokenization → embedding visualization → quick model comparison and projection video.
Playbook covering site list analysis, NE dependencies, progress monitoring, war room ops, and exec reporting.
Weekly executive report untuk NPI Transport PA4: highlights, KPI delta, isu & next actions.
Open Repositories
Ringkasan repositori publik yang relevan untuk telco × AI/ML; dikelompokkan agar mudah dipetakan ke skill. Klik judul repo untuk membuka GitHub.
- Tokenisasi, vectorization, dan visualisasi ruang embedding.
- Eksperimen model: LSTM/bi-LSTM, baseline vs tuned.
- Storytelling hasil (grafik proyeksi) untuk stakeholder.
- TL pipeline (augmentations, fine-tuning, early stopping).
- Dasar CNN: conv → pooling → normalization → classifier.
- PCAP parsing (PyShark), PCA/DBSCAN untuk anomali.
- Analitik OTDR fiber: fitur sinyal, deteksi event.
- Dashboards yang audit-friendly untuk stakeholder telco.
- Latihan supervised/unsupervised, EDA, feature engineering.
- CI/CD dasar untuk proyek ML (build, test, lint).
- Best practices via repo tugas terstruktur.
- Starter untuk dashboard React data-heavy.
- Latihan TensorFlow (optimizers, callbacks, input pipeline).
Live Repo Explorer
Tarik langsung dari GitHub (Milzon1010) dengan metadata (stars, bahasa, last updated), plus pencarian & filter. Perlu internet saat runtime.
Vision & Mission
Mendorong transformasi telco → data-driven enterprise: jaringan dipantau AI real-time, keputusan berbasis evidence, dan productization ML yang bisa diaudit & dipelihara.
- Merancang solusi ujung-ke-ujung: data → model → dashboard → adopsi.
- Membawa rigor PMO ke proyek AI/ML (ritme, metrik, audit trail).
- Mengangkat talenta lokal/regional via dokumentasi, repo terbuka, dan demo.