Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Bulletin of Network Engineer and Informatics (BUFNETS) Jurnal Informatika: Jurnal Pengembangan IT
M Ilham Yusuf Gumai
Institut Informatika dan Bisnis Darmajaya
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
SentryNap: Sistem Peringatan dan Monitoring Kantuk Operator Industri Menggunakan YOLOv5 dan CCTV M Ilham Yusuf Gumai; Yohana Christy Relyana Sembiring; Sri Lestari
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10111

Abstract

This study aims to develop SentryNap, a real-time drowsiness warning and monitoring system for industrial control-room operators based on YOLOv5s using CCTV/webcam image input. Reduced alertness caused by long shift work and operator drowsiness can increase the risk of operational errors, while many previous approaches still rely on intrusive physiological sensors or visual methods that are sensitive to changes in lighting and head pose. The proposed system uses a YOLOv5s model fine-tuned on a Roboflow dataset with two classes, namely normal and sleeping, and integrates the inference results with a Node.js backend for JSON logging. Model training was conducted for 50 epochs at a resolution of 640 x 640 pixels using the SGD optimizer, while evaluation was carried out through static validation and real-time testing scenarios. The model achieved a precision of 0.986, recall of 1.000, mAP@0.5 of 0.995, and mAP@0.5:0.95 of 0.621. Real-time testing showed that detection results could be recorded by the backend in less than one second. These findings indicate that SentryNap has potential as a non-invasive operator safety monitoring prototype, although larger datasets and broader field validation are still required.
AURA: ADAPTIVE UI RECOVERY ARCHITECTURE FOR ANDROID TEST AUTOMATION M Ilham Yusuf Gumai; Suhendro Yusuf Irianto; RZ Abdul Aziz; Rahmalia Syahputri
Bulletin of Network Engineer and Informatics Vol. 4 No. 1 (2026): BUFNETS (Bulletin of Network Engineer and Informatics) April 2026
Publisher : PT. GWEX NET PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59688/738290

Abstract

User interface (UI) test automation on Android frequently breaks when developers rename element attributes during refactoring, rendering previously valid locators unresolvable and imposing significant maintenance overhead. Existing self-healing approaches predominantly target web DOM and lack post-action validation, risking false healing where a wrong element is silently accepted. This study introduces AURA, a runtime self-healing layer for Appium-WebdriverIO that chains five deterministic recovery strategies, a widget-family post-action validator, and an optional machine-learning reranker. A controlled benchmark comprising 490 refactoring scenarios across five synthetic Android applications and six mutator types demonstrates that AURA achieves a 99.39% correct action rate with only 0.61% false-healing rate, significantly outperforming the adapted Similo baseline (95.71% / 4.29%) at p < 0.0001 (McNemar exact test). External validation on six production Google Android applications (130 scenarios) confirms a 100% correct rate with a bounds-IoU enhanced validator. Cache learning reduces per-find latency by 95.1% from the second session onward.
Co-Authors Rahmalia Syahputri RZ Abdul Aziz Suhendro Yusuf Irianto Yohana Christy Relyana Sembiring