Spatial Analysis of Factors Affecting Traffic Accident Frequency in Jakarta Using a Geographically Weighted Regression Approach
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Gamas Gagah Pangestu*
Sutanto Soehodo
Martha Leni Siregar
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.
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