Integration of Human Factors Analysis and Classification System (HFACS) and Failure Mode and Effects Analysis (FMEA) In Fleet Traffic Accident Risk Analysis At PT Semen Indonesia Logistik
DOI:
10.46729/ijstm.v7i5.1500Published:
2026-10-23Downloads
Abstract
Traffic accidents involving distribution fleets are a safety concern that can be influenced by human factors, environmental conditions, supervision, and organizational factors. This study aims to identify the factors contributing to traffic accidents and determine risk priorities as a basis for developing recommendations to improve fleet safety at PT Semen Indonesia Logistik. The methods used are the Human Factors Analysis and Classification System (HFACS) and Failure Mode and Effects Analysis (FMEA). HFACS is used to classify factors contributing to accidents, while FMEA is used to prioritize risks based on the Risk Priority Number (RPN). The integration of these methods enables the study not only to identify accident causation factors but also to determine which risks require the most immediate attention. The HFACS analysis shows that Adverse Mental States is the most dominant category, with 35 occurrences (18.92%), followed by Decision Errors with 33 occurrences (17.84%) and Perceptual Errors with 28 occurrences (15.14%). Meanwhile, the FMEA results indicate that driver fatigue has the highest RPN of 504, followed by failure to maintain a safe following distance with an RPN of 378 and failure to detect objects in blind spots with an RPN of 324. Based on these findings, the recommended improvements include implementing fatigue management, regulating working hours and rest periods, providing defensive driving training, increasing blind-spot awareness, and optimizing driving behavior monitoring. The integration of HFACS and FMEA can support the systematic identification of accident causation factors and the prioritization of risk control measures.
References
[1] MN Fauzan, L. Yuliana, D. Adhitama, and I. Zulfikar, “Socialization of human error factors on mixer truck transportation safety using the HFACS approach at PT. XYZ,” EUNOIA: Jurnal Pengabdian Masyarakat, vol. 5, no. 1, pp. 12–20, 2026, doi: 10.36277/eunoia.v5i1.884.
[2] ENF Suwandi, B. Suhardi, and E. Muslimah, “Analysis of human error factors on the probability of accidents in bus drivers using the Human Factors Analysis and Classification System approach,” Ranah Research: Journal of Multidisciplinary Research and Development, vol. 8, no. 4, 2026, doi: 10.38035/rrj.v8i4.2198.
[3] AF Musyaffa, MAFA, AAR Cindy, BR Hutabalian, and BS Nugroho, “Analysis of occupational accident causes using the Human Factor Analysis and Classification System method in the coal industry, West Virginia,” Jurnal Migasian, vol. 8, no. 2, 2024.
[4] D. Kurniasih, A. Maharani, and ML Ashari, "Human Factors Analysis and Classification System (HFACS) on accidents due to tilting ships," Indonesian Journal of Innovation Multidisciplinary Research, vol. 2, no. 2, 2024, doi: 10.69693/ijim.v2i2.134.
[5] IZ Sutalaksana, “Preliminary study of occupational safety systems in accident cases at SBU ITS PT. X using the Human Factors Analysis and Classification System (HFACS) methodology,” Journal of Ergonomics and K3, vol. 3, no. 1, pp. 11–17, 2018, doi: 10.5614/j.ergo.2018.3.1.3.
[6] W. Budiawan and H. Iridiastadi, “Designing a computer aided system to analyze human error in Indonesian railways,” J@TI Undip: Jurnal Teknik Industri, vol. 8, no. 2, p. 89, 2013, doi: 10.12777/jati.8.2.89-89.
[7] B. Mardikawati, DO Mulyaningtyas, and Y. Fitasari, “Analysis of the contribution of human error to traffic accidents in Bali: A mixed-method approach with convergent triangulation design,” Journal of Road Transportation Safety, vol. 12, no. 1, pp. 47–57, 2025, doi: 10.46447/ktj.v12i1.693.
[8] FV Rahmadani and BYS Nugroho, “The relationship between driving hours, blood pressure, and driving aggressiveness with fatigue in AKDP bus drivers: A cross-sectional study,” Journal of Road Transportation Safety, vol. 13, no. 1, pp. 1–14, 2026, doi: 10.46447/ktj.v13i1.779.
[9] MLS Zainy, GB Pratama, RR Kurnianto, and H. Iridiastadi, "Fatigue among Indonesian commercial vehicle drivers: A study examining changes in subjective responses and ocular indicators," International Journal of Technology, vol. 14, no. 5, pp. 1039–1048, 2023, doi: 10.14716/ijtech.v14i5.4856.
[10] R. Zuraida and BS Abbas, "The factors influencing fatigue related to the accident of intercity bus drivers in Indonesia," International Journal of Technology, vol. 11, no. 2, pp. 342–352, 2020, doi: 10.14716/ijtech.v11i2.3792.
[11] E. Purwanto, H. Hidayat, and E. Pranoto, “Fatigue levels in Trans Semarang and Trans Jateng Bus Rapid Transit (BRT) drivers,” Journal of Road Transportation Safety, vol. 5, no. 2, pp. 53–64, 2018, doi: 10.46447/ktj.v5i2.49.
[12] R. Aprianto, A. Rokhim, A. Basuki, and Sugiyarto, “The Effect of Driver Characteristics and Rest Area Utilization on Driver Fatigue: A Case Study of the Pejagan–Solo Toll Road,” Journal of Road Transportation Safety, vol. 8, no. 1, pp. 92–103, 2021, doi: 10.46447/ktj.v8i1.310.
[13] AA Mauludi, Z. Djunaidi, and LS Arif, “Risky behavior as a causal factor in accidents among commercial motorcycle drivers: A systematic review,” Journal of Road Transportation Safety, vol. 8, no. 1, pp. 12–25, 2021.
[14] G. Guritnaningsih, T. Tjahjono, and D. Maulina, “Human error in traffic accidents: Analysis based on information processing,” Journal of Indonesia Road Safety, vol. 1, no. 1, 2018, doi: 10.19184/korlantas-jirs.v1i1.14772.
[15] YYN Adlina and S. Nurlaela, “Analysis of traffic accident factors in Surabaya based on spatial planning perspective through spatial modeling,” Jurnal Teknik ITS, vol. 10, no. 1, pp. E13–E20, 2021, doi: 10.12962/j23373539.v10i1.59782.
[16] D. Kusmayadi and U. Fariz, “Identification of accident-prone locations (blackspots) in Bekasi Regency,” Journal of Road Transportation Safety, vol. 10, no. 1, 2023, doi: 10.46447/ktj.v10i1.520.
[17] IB Prastiyo, “Analysis of traffic accident incidence and costs (case study of Jambi City),” Journal of Road Transportation Safety, vol. 10, no. 2, 2023, doi: 10.46447/ktj.v10i2.561.
[18] EAT Aji, R. Firdaus, C. Sanggalangi, and MR Irfani, “Analysis of accident-prone areas on the Becakayu Toll Road using the Equivalent Accident Number (EAN) method,” Journal of Road Transportation Safety, vol. 11, no. 1, 2024, doi: 10.46447/ktj.v11i1.575.
[19] S. Hadi, SI Wahyudi, K. Wibowo, Y. Oktopianto, AE Fahmadi, and IW Anggraeni, “Analysis of accident-prone locations on flat and hilly roads,” Journal of Road Transportation Safety, vol. 12, no. 1, pp. 36–46, 2025, doi: 10.46447/ktj.v12i1.686.
[20] B. Imawan, ED Priyana, and YP Nugroho, “Analysis of occupational accident risks in PT. XYZ workshop using the Failure Mode and Effect Analysis method,” SIGMA TEKNIKA, vol. 6, no. 1, 2023.
[21] H. Hardiansah, Y. Sukmono, and WWE Saptaningtyas, “Analysis of occupational accident risks using the Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) methods: A case study of the Dynamic Workshop,” Jurnal Teknik Industri (JATRI), vol. 1, no. 1, pp. 1–9, 2023, doi: 10.30872/jatri.v1i1.493.
[22] VE Ateng, R. Rahmahwati, and YE Prawatya, “Proposed improvement of the OHS system using FMEA and RCA methods at PT. XYZ,” Journal of Industrial Engineering, Tanjungpura University, vol. 5, no. 1, 2021.
[23] MF Kurnianto, Kusnadi, and FN Azizah, “Proposed improvement of occupational accident risk using Failure Mode and Effect Analysis (FMEA) and Fishbone Diagram methods,” SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan, vol. 6, no. 1, 2022, doi: 10.31764/jpmb.v6i1.6627.
[24] MAY Verdiansyah and AW Rizqi, “Analysis of work accidents at PT Ravana Jaya using FMEA and FTA methods,” INTECOMS: Journal of Information Technology and Computer Science, vol. 8, no. 6, pp. 2008–2013, 2025, doi: 10.31539/pe4p8324.
[25] GAB Fadillah, YH Haerudin, and RF Ramdhani, “Occupational safety risk analysis using Job Safety Analysis (JSA) and Failure Mode and Effects Analysis (FMEA) methods in the waste processing process at CV. Dea Ayu Lestari Purwakarta,” Journal of School Leadership and Management, vol. 11, no. 4, 2026, doi: 10.34125/jkps.v11i4.3196.
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