INTERNATIONAL JOURNAL ON ADVANCED TECHNOLOGY, ENGINEERING, AND INFORMATION SYSTEM

Factors Influencing Traffic Accidents on the Cipularang Toll Road: An Analysis Using Multiple Linear Regression

Dedi Kurniawan — 2026-06-02

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.

Traffic Management Analysis and Mitigation of Counter-Flow Violations Using Traffic Conflict Techniques in Alam Sutera, Tangerang

Reza Doris Perdana — 2026-06-02

Wrong-Way Driving (WWD) by motorcycle riders is a critical safety issue in urban Indonesia, with the Alam Sutera area, Tangerang, recording 1,126 violators in a single peak‑hour observation. This study formulates an integrated traffic management and mitigation strategy for the phenomenon of Wrong-Way Driving (WWD) in the Alam Sutera area. The primary issue is driven by the inefficiency of the legal route (1,800 m) compared to the WWD route (270.1 m), which creates a justification for speculative behavior. Proactive safety analysis using the Swedish Traffic Conflict Technique (TCT) identified an extreme fatality risk with an average Time-to-Accident (TA) value of 0.7 seconds, with 80% of interactions categorized as serious conflicts. Questionnaire analysis based on the Theory of Planned Behavior (TPB) confirmed a critical detour distance threshold at >1,000 m, which serves as a trigger point for driving violations. Evaluation through VISSIM microsimulation (validated with GEH value < 5 and MAPE value < 50% ) shows that Scenario 3 is the most optimal mitigation. By implementing a 1.20 km alternative route via the roundabout, installing permanent physical barriers, and optimizing the traffic signal cycle time from 143 seconds to 90 seconds, the traffic volume load at the conflict point was significantly redistributed. This strategy effectively enhancing operational performance by reducing average delay to 20.34 seconds/vehicle at Level of Service (LOS) C.

Understanding Traffic Accident Patterns on the Jakarta-Cikampek Toll Road: An Integrated Approach Combining Blackspot Analysis and Human Factors

Relif Karnadi — 2026-06-03

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.

Spatial Analysis of Factors Affecting Traffic Accident Frequency in Jakarta Using a Geographically Weighted Regression Approach

Gamas Gagah Pangestu — 2026-06-03

Traffic accidents are a complex issue influenced by road network characteristics, demographics, land use, and traffic conditions. This study analyzes the effects of these factors on accident frequency in DKI Jakarta and examines their spatial variation at the sub-district level. Using secondary data on accidents, road networks, population, land use, traffic, and regional activity, analysis was conducted using global regression (Ordinary Least Squares/OLS) and spatial regression (Geographically Weighted Regression/GWR), considering variations by severity, time period, and lighting. Results show that all factor groups significantly influence accident frequency, with effect magnitudes varying across areas. The GWR model captures local variations better than OLS, reflected by higher R² values in most conditions, while OLS remains effective for explaining global patterns. Findings indicate accident variations are more influenced by differences in the strength of factor effects across regions rather than the types of factors themselves, and are also affected by traffic operational conditions. This confirms that traffic accident characteristics are inherently spatial and contextual. The study highlights the importance of area-specific transportation safety planning, with tailored policy approaches to enhance intervention effectiveness in reducing urban accident rates.

Analysis of the Causes and Impacts of Traffic Congestion (Case Study of Jl. MH Thamrin, Sentul)

Muhammad Hibban Yanhasdin — 2026-06-03

Traffic congestion is a complex problem that has wide-ranging impacts on various aspects of community life, particularly in rapidly urbanizing suburban areas such as Sentul, a satellite city located in the Bogor Regency of West Java, Indonesia. This study aims to identify the main causes of congestion and analyze its impacts on social, economic, and environmental aspects. The research focuses on MH Thamrin Street in Sentul, a strategic corridor with high traffic intensity. A mixed-methods approach was used, incorporating field observations, questionnaire surveys, and in-depth interviews. The research findings indicate that the primary causes of congestion at the site include high vehicle volume, ineffective traffic management, roadside obstacles, and undisciplined road user behavior. The resulting impacts include increased travel time, fuel waste, commuter stress, and reduced local economic productivity. As such, these findings are expected to inform the formulation of more responsive and sustainable urban transport policies in similar areas.

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 — 2026-06-22

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.

Integrating Cycling with MRT Jakarta for First-Mile and Last-Mile Accessibility: A Stated Preference Approach

Lidya Hotma Silaen — 2026-06-22

Urban mobility in Greater Jakarta is characterized by high commuter volumes between suburban and urban core areas, with daily MRT Jakarta ridership averaging 124,397 passengers in 2025, yet first-mile and last-mile station accessibility remains a persistent challenge. This study evaluates the potential for improving MRT Jakarta accessibility through bicycle integration as first-mile and last-mile modes, and estimates acceptable pricing for public bike-sharing and private bicycle parking. A Stated Preference (SP) approach was employed with 385 respondents within a 3 km radius of Lebak Bulus MRT Station, where the existing access mode was disaggregated into seven categories and compared against private bicycle and bike-sharing alternatives, generating twenty-one utility equations estimated through logistic regression. Each alternative's systematic utility was specified as a function of cost, distance, and travel time, with resulting coefficients translated into a generalized cost function and a mode choice probability and sensitivity analysis. Results indicate strong mode-shift potential across all seven existing-mode groups, with the probability of retaining the existing access mode falling to roughly 2-4% while the combined shift probability to cycling exceeds 95% under improved conditions. Cost exerts a consistently negative and statistically significant effect on cycling choice, confirming that higher fares reduce adoption likelihood, while distance and travel time generally lower utility as expected. Private bicycles show higher selection probability than bike-sharing, though the latter remains a viable complementary alternative. Overall, cycling integration with MRT Jakarta holds strong potential to enhance accessibility, driven by affordable pricing and supportive infrastructure.