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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Kurniawan D. Irianto
Universitas Islam Indonesia, Yogyakarta
Computer Science & IT Decision Sciences, Operations Research & Management

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Deteksi Kantuk Pengemudi Berbasis Eye Aspect Ratio dan Head Pose Estimation dengan Integrasi IoT Rama Amirul Ramadhan; Kurniawan D. Irianto
Journal of Information System Research (JOSH) Vol 7 No 4 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i4.10598

Abstract

This study proposes a real-time driver drowsiness detection system integrating computer vision with Internet of Things (IoT) technology on an affordable embedded platform. The system uses a Camera Module 3 Wide NoIR connected to a Raspberry Pi 3 Model B+ to capture driver facial images. Two visual indicators are computed in parallel from 68 facial landmarks extracted using dlib: Eye Aspect Ratio (EAR) for detecting prolonged eye closure, and Head Pose Estimation using solvePnP for detecting head nodding. An OR-logic decision mechanism triggers an audio alarm when EAR falls below 0.25 for five consecutive frames or Pitch angle exceeds 15 degrees for ten consecutive frames. Events are classified as KANTUK_MATA, KANTUK_KEPALA, or KEDUANYA and sent to firebase Realtime Database for remote monitoring. Black Box testing with 11 scenarios confirms all core functions operate correctly. Average response times of 2.00 seconds via EAR and 2.70 seconds via Head Pose are within acceptable ranges for early drowsiness warning. The multi-indicator approach demonstrates that head nodding is detected earlier than eye closure in gradual drowsiness scenarios, providing earlier warning than single-indicator systems. Under high CPU load conditions (>80%), the frame rate drops to 5 fps, resulting in a total system latency of 2.8–4.2 seconds; this condition is still adequate for early warning but not for sub-second responses. Across the 11 Black Box testing scenarios, the system achieved 100% precision (no false alarms during normal blinking) and 100% recall (all drowsiness conditions detected), although the testing was conducted under controlled laboratory conditions, necessitating further generalization to real-world environments.
Perancangan Antarmuka Aplikasi BCA Mobile Berbasis Heuristic Evaluation Muhammad Rizqi Setyawan; Kurniawan D. Irianto
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7926

Abstract

This study aims to evaluate the quality of the user interface (UI) and user experience (UX) of the BCA Mobile application using the Heuristic Evaluation method. The primary objective is to develop a design solution that is more effective, intuitive, and aligned with users’ needs in conducting digital banking activities. The evaluation focuses on key features such as fund transfers, balance information, transaction history, and transaction notifications. The results reveal several issues related to readability, navigation efficiency, and visual data security. By applying a heuristic-based approach, the study proposes improvements including the addition of Face ID for access code authentication, enhanced text contrast, and the replacement of the virtual account feature. The proposed UI/UX redesign aims to improve user comfort, efficiency, and security in accessing BCA Mobile's digital banking services.
Co-Authors Muhammad Rizqi Setyawan Rama Amirul Ramadhan