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All Journal International Journal on Advanced Technology, Engineering, and Information System (IJATEIS)
R Jachrizal Sumabrata
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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Analysis of the Effect of Road Geometric Factors on Accident Frequency and Safety Level on the Sungai Duren-Sungai Buluh Road Section in Jambi Province Ilfandri Hagia; Sutanto Soehodho; R Jachrizal Sumabrata
INTERNATIONAL JOURNAL ON ADVANCED TECHNOLOGY, ENGINEERING, AND INFORMATION SYSTEM Vol. 5 No. 3 (2026): AUGUST
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/ijateis.v5i3.2254

Abstract

Road infrastructure conditions, particularly geometric characteristics, are important factors that may influence traffic accident risk on provincial road sections. This study examines the effect of road geometric factors on traffic accident frequency and evaluates the road safety level of the Sungai Duren-Sungai Buluh Road section in Jambi Province, Indonesia. A quantitative explanatory design was applied to a 13 km road section divided into 130 segments of 100 m. Accident data were obtained from the Integrated Road Safety Management System of the Jambi Regional Police for the 2019-August 2025 period, while geometric and road safety attribute data were collected from as-built drawings, field surveys, and video-based road inventory. Poisson regression was used to identify factors affecting accident frequency, and the iRAP Star Rating method was applied to assess infrastructure-related safety risk. The results show that hilliness, bendiness, and operating speed have significant positive effects on accident frequency, with significance values of 0.007, 0.042, and 0.038, respectively. Segments without berms were more vulnerable to accident risk, particularly due to hilliness, operating speed, and pavement condition. The iRAP assessment showed that 84.6% of the segments were classified as 1-star and 2-star roads, indicating a low safety level. The improvement simulation increased the Star Rating from 1 Star to 4 Stars through targeted infrastructure interventions. These findings imply that integrating Poisson regression and iRAP assessment can support data-driven prioritization of road safety improvements on high-risk provincial road segments.
Co-Authors Ilfandri Hagia Sutanto Soehodho