Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
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All Journal International Journal on Advanced Technology, Engineering, and Information System (IJATEIS)
Sutanto Soehodho
Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Factors Influencing Traffic Accidents on the Cipularang Toll Road: An Analysis Using Multiple Linear Regression Dedi Kurniawan; Sutanto Soehodho; R. Jachrizal Sumabrata
INTERNATIONAL JOURNAL ON ADVANCED TECHNOLOGY, ENGINEERING, AND INFORMATION SYSTEM Vol. 5 No. 1 (2026): JANUARY
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/ijateis.v5i1.2235

Abstract

Traffic accidents remain a critical issue in road safety, particularly on toll roads with high traffic intensity such as the Cipularang Toll Road. This study aims to analyze the factors influencing traffic accidents by applying a multiple linear regression approach, with a focus on human-related factors represented by driver physical condition. Data spanning 2023–2025 from the Cipularang Toll Road corridor were collected through structured interview surveys and supported by secondary data from official accident records. The variables examined include driver characteristics, vehicle conditions, traffic and environmental factors, and behavioral aspects. The results show that estimated speed and driving license type have a statistically significant effect on the dependent variable at the 5% significance level. Estimated speed is identified as the most influential factor, indicating that higher speeds are associated with a decline in driver physical condition, which may increase accident risk. The selection of physical condition as the dependent variable is supported by police reports indicating that a substantial number of accidents are caused by driver fatigue, drowsiness, and reduced alertness, especially on long-distance toll roads. Other variables, although not statistically significant, demonstrate relationships consistent with theoretical expectations. These findings highlight the importance of addressing both speed management and driver fatigue in reducing accident risk. The study contributes to evidence-based road safety strategies by providing a comprehensive analysis of accident-related factors, helping policymakers and toll road operators design more effective safety interventions, especially on high-risk segments like the Cipularang Toll Road.
Understanding Traffic Accident Patterns on the Jakarta-Cikampek Toll Road: An Integrated Approach Combining Blackspot Analysis and Human Factors Relif Karnadi; Sutanto Soehodho; R. Jachrizal Sumabrata
INTERNATIONAL JOURNAL ON ADVANCED TECHNOLOGY, ENGINEERING, AND INFORMATION SYSTEM Vol. 5 No. 1 (2026): JANUARY
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/ijateis.v5i1.2237

Abstract

Traffic accidents on toll roads remain a major safety concern, particularly on high-traffic corridors such as the Jakarta-Cikampek Toll Road in Indonesia. This study aims to identify accident-prone locations (blackspots) and analyze contributing factors, with a focus on human-related aspects such as fatigue and rest adequacy. An integrated approach combining spatial analysis and multiple linear regression was employed to better understand accident patterns and their determinants. The study utilizes historical accident data from the Indonesian National Police Traffic Corps and toll road operators for the period 2021-2023, complemented by interview-based behavioral data. Blackspots were identified using a severity-based weighting method, while regression analysis examined the relationship between rest adequacy and variables such as gender, driving experience, travel characteristics, fatigue indicators, sleep duration, and risk perception. The results indicate that no variables are statistically significant at the 5 percent level. However, gender shows the strongest relationship with rest adequacy (β = -0.313; Sig. = 0.060), while sleep duration (β = 0.156) and risk perception (β = 0.102) exhibit positive tendencies. Fatigue indicators show mixed results, suggesting that fatigue is a complex and multidimensional factor. Spatial analysis also reveals several high-risk segments associated with traffic density and road conditions. These findings highlight the need for integrated safety strategies that address both location-based risks and human factors. The study contributes to evidence-based approaches for improving toll road safety.
Co-Authors Dedi Kurniawan R. Jachrizal Sumabrata Relif Karnadi