Analisis Spasial Titik Rawan Kecelakaan Lalu Lintas (Blackspot) Di Kabupaten Banyuasin Menggunakan Kernel Density - Amaliasari, Fitri; Buchari, Erika; Kadarsa, Edi (Syntax Literate, 2025)
The increase in population and mobility in Banyuasin Regency has a direct impact on traffic safety risks. Throughout 2023, 162 traffic accidents were recorded, exhibiting a fluctuating pattern. This study aims to identify and map the spatial distribution of accident-prone points (black spots) and measure the validity of the vulnerability model. The method employed is Geographic Information System (GIS)-based Kernel Density Estimation (KDE), utilizing 2023 incident data as the training set and January 2024 data for validation. The analysis integrates parameters of victim fatality, time of occurrence, and vehicle type. The results indicate the formation of a "Very High" risk zone covering 75.67 km² (0.60% of the total area), concentrated along the East Trans-Sumatra Road (Palembang–Jambi) at KM 24.5–32.5 in Sembawa District and KM 63–77 in Betung District. Model validation demonstrated an accuracy rate of 90.91%. The reliability of the model was confirmed through statistical tests, where the Binomial Test yielded a p-value of 0.0002 < α = 0.05, and the Chi-Square Test showed a calculated value χ² of 25.74 (greater than the table value of 9.488). These results prove that the distribution of accidents is significantly concentrated in the predicted high-risk zones and is not randomly distributed. This study validates the effectiveness of the KDE method as a strategic tool for prioritizing road safety infrastructure improvements in Banyuasin Regency.