Road Safety Study in Accident-Prone Areas on the Gading - Playen and Yogyakarta - Barongan Road Sections

Raafi Widyaputra Yulianyahya; Ghefra Rizkan Gaffara; Ansadilla Niar Sitanggang; Irma Damayantie

doi:10.59261/jequi.v8i3.338

Authors

Raafi Widyaputra Yulianyahya Universitas Esa Unggul
Ghefra Rizkan Gaffara Universitas Esa Unggul
Ansadilla Niar Sitanggang Universitas Esa Unggul
Irma Damayantie Universitas Esa Unggul

DOI:

https://doi.org/10.59261/jequi.v8i3.338

Keywords:

Road safety, Accident-prone areas, Infrastructure, Education, Driver behavior

Abstract

Background: The background of this research stems from the high number of accidents occurring on this road section, which endangers the safety of road users.

Objective: This study aims to analyze traffic safety on two road sections with high accident rates, namely the Gading–Playen Road and the Yogyakarta–Barongan Road.

Methods: The research methods employed include field surveys, collection of primary and secondary data, and statistical analysis using the CUSUM method and the V/C (volume-to-capacity) ratio.

Results: The analysis revealed Gading–Playen Road section has a capacity of 3,354 pcu/hour with a V/C ratio of 0.196, indicating stable traffic conditions, while the Yogyakarta–Barongan Road section has a capacity of 3,444 pcu/hour with a V/C ratio of 0.771, reflecting near-saturated traffic conditions and a higher-risk situation. Z-score analysis of accident data from 2016 to 2019 showed a sharp spike on the Yogyakarta–Barongan section in the third period (z = +1.55), while the Gading–Playen section recorded a significant decline (z = −1.13). Accidents on both sections predominantly involve motorcycle users and male victims aged 16–25 years, and are primarily caused by undisciplined driving behavior. Key recommendations include geometric road improvements, installation of adequate traffic signs, improved road lighting, and strengthened enforcement of traffic regulations.

Conclusion: The integration of CUSUM, Z score, and V/C ratio methods provides an effective framework for identifying and assessing traffic accident risks. The findings reveal distinct risk characteristics between road sections, requiring targeted interventions based on geometric conditions, traffic intensity, and behavioral factors.

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