Vol. 3 No. 2 (2025): June

This study aims to identify traffic accident prone points (black spots) on the Letjen Jamin Ginting National Road section, North Sumatra Province, Indonesia. Traffic accident data in the period 2021 to 2024 was analyzed using a combination of several methods, namely the Equivalent Accident Number (EAN), Batas Kontrol Atas (BKA), Upper Control Limit (UCL), Cumulative Sum (CUSUM) method, and Bina Marga method. The analysis was carried out by considering the severity of the accident, the classification of the location based on the accident rate, and the comparison of the results between the black spot identification methods. In addition, road characteristics such as geometric shape, slope, and road surface conditions were also analyzed to see the correlation with the number of accidents. The results showed that black spots tend to be on straight and flat roads with good road surface conditions, but still have a high frequency of accidents, showing that road user behavior factors play a big role in the occurrence of accidents. The CUSUM method is able to identify the trend of increasing accidents more sensitively than other methods, while the Bina Marga method provides conservative results according to national standards. Based on the results of the identification, a number of mitigation measures are recommended, including the installation of additional road markings, improving street lighting, improving traffic signs, and monitoring vehicle speeds. The application of a GIS-based accident monitoring system is also recommended to facilitate mapping and black spot analysis in the future.