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A Sustainability-Based Occupational Safety Risk Prioritization Model for High-Rise Building Maintenance Using HIRARC and AHP Emma Budi Sulistiarini; Evi Yuliawati; Diky Siswanto; M. Ashlyzan Bin Razik; Bambang Suhardi
JTI: Jurnal Teknik Industri Vol 12 No 1 (2026): June 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jti.v12i1.39282

Abstract

High-rise building maintenance involving work at height presents significant occupational safety risks, particularly fall-related incidents that may result in severe injuries, operational disruptions, and financial losses. Conventional risk assessment approaches such as Hazard Identification, Risk Assessment, and Risk Control (HIRARC) primarily rely on technical likelihood–severity scoring and do not explicitly incorporate sustainability consequences into risk prioritization. This study develops a sustainability-based occupational safety risk prioritization model for high-rise building maintenance by introducing a Sustainability Risk Priority Index (SRPI) that integrates HIRARC-based technical risk scores, Triple Bottom Line (TBL) weighting derived from the Analytic Hierarchy Process (AHP), and hazard-level sustainability impact assessment. Unlike conventional approaches that prioritize hazards primarily based on technical risk magnitude, the proposed SRPI provides a composite prioritization framework that also captures People, Planet, and Profit consequences in measurable terms. The model was demonstrated through a case study of a three-story laboratory building that identified six hazards. The results show that falls from the rooftop edge and falls from a narrow canopy platform remain the highest technical risks (R = 20). The AHP weighting yielded People = 0.60, Profit = 0.25, and Planet = 0.15, with a Consistency Ratio (CR) of 0.07. The proposed model differentiates medium-level hazards more clearly by incorporating sustainability consequences while preserving the dominance of hazards with potentially fatal outcomes. Sensitivity analysis with ±10% variation in the People weight indicates that the highest-priority hazards remain stable across scenarios. Keywords: Occupational safety; Sustainability risk prioritization; HIRARC; AHP; High-rise building maintenance
Sistem Deteksi Alat Pelindung Diri Berbasis YOLOv8n pada Jetson Nano untuk Industri Migas Amien Thohari Yudhistira; Sabar Setiawidayat; Istiadi; Diky Siswanto
JASEE Journal of Application and Science on Electrical Engineering Vol. 7 No. 1 (2026): JASEE-March
Publisher : Program Studi Teknik Elektro - Fakultas Teknik - Universitas Widyagama Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31328/jasee.v7i1.04

Abstract

Occupational safety in the oil and gas industry requires strict compliance with Personal Protective Equipment (PPE); however, manual inspection is prone to human error and lacks effectiveness. This research designs and implements a PPE Smart Station based on the YOLOv8n algorithm on an NVIDIA Jetson Nano A02 embedded system to automatically and in real-time detect the completeness of three main PPE types—helmet, coverall, and gloves—within the industrial environment of PT Husky-CNOOC Madura Limited. The system employs a state machine with PASS/DENIED output, a real-time 2D visualization of missing PPE on the worker’s anatomical regions, and Indonesian-language text alerts with automatic audio warnings. Results are reported at two levels: (i) model evaluation on a limited test batch yielded 99.0% precision and 100% recall under near-ideal capture conditions; and (ii) field system evaluation on 30 samples at a single installation point, assessed with a confusion matrix at the PASS/DENIED decision level, yielded 93.3% accuracy, 96.0% precision, 96.0% recall, 96.0% F1-measure, and a 6.7% error rate. The results indicate the system’s initial feasibility as an AI-based occupational-safety monitoring solution under the evaluated conditions, while larger-scale, multi-site validation remains necessary.