Claim Missing Document
Check
Articles

Found 32 Documents
Search

Evaluasi Deteksi Posisi Kereta Menggunakan Radio Ranging di CBTC Rivabillah, Copa; Wahyu Kusuma Raharja
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 6 No 4 (2025)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.6.4.497

Abstract

This study analyzes the performance of Radio Ranging technology in improving train position detection accuracy within the Communications-Based Train Control (CBTC) system of MRT Jakarta. The simulation-based experimental method was carried out using MATLAB, with the comparison of Radio Ranging and Tachogenerator (TG) across three operational conditions: open area, tunnel, and dense urban environment. Evaluation metrics include position deviation and Root Mean Square Error (RMSE). The results show that Radio Ranging provides better accuracy compared to TG, particularly in tunnel and dense areas, where TG tends to accumulate errors. These findings indicate that Radio Ranging can serve as a complementary method to enhance CBTC reliability and operational safety of MRT Jakarta.
Pre-driving fatigue screening from short-term heart rate variability with subject-independent validation Tia Haryanti; Eri Prasetyo Wibowo; Wahyu Kusuma Raharja; Rossi Septy Wahyuni; Imliyati Sari
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i3.pp2885-2895

Abstract

This study evaluates fatigue screening from 30-second electrocardiogram (ECG) recordings using short-term heart rate variability (HRV) features in a pre-driving context. The dataset comprises 99 participants (one session each) with fatigue labels derived from the Karolinska sleepiness scale (KSS), where the primary label (K1) defines non-fit as KSS ≥ 7. A subject-independent logistic-regression model was trained under a leave-one-subject-out (LOSO) scheme. Probabilities were calibrated using Platt scaling and evaluated through threshold-free metrics (receiver operating characteristic (ROC)-area under the curve (AUC), precision-recall (PR)-AUC) as well as calibration performance using the Brier score. The model achieved ROC-AUC =0.687 (95% confidence interval: 0.591–0.776), PR-AUC =0.621, and a Brier score of 0.200. At the operating threshold t = 0.255, the model achieved sensitivity of 1.000 with no false negatives, while specificity remained 0.091 (95% confidence interval: 0.030–0.140). Reliability analysis indicated reasonable calibration in the operational probability range. These findings support short-term HRV derived from ECG as a screening tool that prioritizes avoiding missed non-fit cases, paired with a triage scheme (fit/review/non-fit) to manage uncertainty near the decision threshold. Future work should incorporate ECG morphology and signal quality cues and aim to improve specificity without sacrificing sensitivity.