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Andini, Tyas Fitria
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Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Engineering Environmental Science Physics

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Traffic Accident Spatial Modeling Using Adaptive Kernel Density Estimation Method Based on Geographical Information Systems For Road Sections In Brebes District, Brebes Regency Andini, Tyas Fitria; Awaluddin, Moehammad; Nugraha, Arief Laila
Journal of Applied Geospatial Information Vol. 9 No. 2 (2025): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v9i2.8404

Abstract

Based on information from the Satlantas Polres Bebes, in 2022 the number of accidents in the Brebes Regency area reached 1.088 incidents that cause fatality damage and material losses. Data shows that in the last three years, Brebes District has recorded as the district with the highest accident statistics in this region. These incidents have a tendency to occur in certain sections. This research  using a Geographic Information System (GIS) based approach using the Adaptive Kernel Density Estimation method to analyze the density of accidents on the road sections. The road network is divided into segments of 1000 meters and sub-segments iterated every 20 meters to obtain more accurate results. Vulnerability maps are classified based on the weighting of accident frequency, blackspot maps are classified based on Equivalent Accident Number (EAN) calculation. The results of the accuracy test comparison show that the Adaptive Kernel Density Estimation method can produce a vulnerability maps model with suitability level accuracy of 71,13%. In blackspot modeling, the CPAI calculation results show that the Adaptive Kernel Density Estimation method can produce a CPAI index of 71,73%.
Co-Authors Arief Laila Nugraha Moehammad Awaluddin