| dc.description.abstract | This study aims to identify traffic accident-prone areas (black spots) along the Letjen Jamin Ginting National Road in North Sumatra Province, Indonesia. Traffic accident data from the period 2021 to 2024 were analyzed using a combination of several methods: Equivalent Accident Number (EAN), Upper Control Limit (UCL), Batas Kontrol Atas (BKA), Cumulative Sum (CUSUM), and the Bina Marga method. Each method provides different perspectives and levels of sensitivity in identifying locations with high accident frequencies. The analysis considered not only the number of accidents but also their severity, classification of accident locations, and geometric characteristics of the road such as curvature, slope, and surface condition. The findings revealed that most black spots were located on straight and flat road segments with good surface conditions, yet had high accident frequencies. This suggests that driver behavior—such as speeding and negligence—plays a significant role in traffic accidents. The CUSUM method was found to be more sensitive in detecting trends in accident increases over time, while the Bina Marga method provided more conservative results in line with national standards. Based on the identification results, several mitigation strategies are recommended, including the installation of additional road markings, improved road lighting, enhanced traffic signs, and speed monitoring systems. Furthermore, the implementation of a Geographic Information System (GIS)-based accident monitoring system is proposed as a long-term strategy to facilitate the mapping and management of black spot locations in the future | en_US |
