Shortest Path Clustering Dalam Menyaring Tingkat Kepadatan Arus Lalu Lintas - Noni Selvia; Erlin Windia Ambarsari; Nurfidah Dwitiyanti (STMIK Budi Darma, 2023)
This study explores the application of graph clustering in identifying and analyzing the shortest traffic-related routes. Graph clustering groups points (vertices) based on road attributes. The DBSCAN method and ant algorithm are applied to classify vertices based on traffic intensity and find the optimal shortest path. This case study focuses on the Tangerang Selatan region, resulting in three clusters and identifying seven noises. Two of the three clusters are selected to calculate the shortest distance, resulting in the sequence [7, 6, 0, 1, 2, 3, 4, 8, 5] and a distance of 0.2526. This research provides insights into how to graph clustering can be used to optimize traffic routes and is expected to serve as a foundation for further exploration