Traffic Accident Spatial Modeling Using Adaptive Kernel Density Estimation Method Based on Geographical Information Systems For Road Sections In Brebes District, Brebes Regency

Authors

  • Tyas Fitria Andini Departement of Geodetic Engineering, Faculty of Engineering, Diponegoro University Jl. Prof. Soedarto No. 13, Tembalang, Telp.(024)76480785, 76480788, Indonesia
  • Moehammad Awaluddin Departement of Geodetic Engineering, Faculty of Engineering, Diponegoro University Jl. Prof. Soedarto No. 13, Tembalang, Telp.(024)76480785, 76480788, Indonesia
  • Arief Laila Nugraha Departement of Geodetic Engineering, Faculty of Engineering, Diponegoro University Jl. Prof. Soedarto No. 13, Tembalang, Telp.(024)76480785, 76480788, Indonesia

DOI:

https://doi.org/10.30871/jagi.v9i2.8404

Keywords:

Traffic Accidents, Density Analysis, Adaptive Kernel Density Estimation, Equivalent Accident Number (EAN), Crash Predictive Accuracy Index (CPAI).

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%.

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References

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Published

2025-12-26

Issue

Vol. 9 No. 2 (2025): Journal of Applied Geospatial Information (JAGI)

Section

Articles

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