Application of the K-Means Algorithm in Traffic Violations In Langkat District (Case Study: Langkat Police) - Elisa Puspita Sari; Yani Maulita; Milli Alfhi Syari (PT. INOVASI TEKNOLOGI KOMPUTER, 2023)
Societal activities are intertwined with traffic, and people prefer using vehicles. The lack of education and limited understanding of traffic regulations have led to numerous violations. The increasing number of traffic violations has resulted in a rise in traffic violation data. The abundance of traffic violation data has led to data accumulation within institutions. Therefore, data processing through data mining utilizing the K-Means Algorithm is deemed necessary. Research findings have unveiled a cluster of traffic violation data that stands out as the highest and most frequent during processing: the age group of 17 to 25 years, involving Honda Vario 150 vehicles, and evidence of violations related to driver's licenses (SIM) and vehicle registration certificates (STNK). Test results on three clusters from a dataset of 502 traffic violation records reveal the following: Cluster 1 comprises traffic violation data pertaining to individuals aged 26 to 45 years, using Honda CBR 250 vehicles, and violations tied to driver's licenses (SIM) and vehicle registration certificates (STNK). Cluster 2 includes traffic violation data concerning individuals aged 26 to 45 years, utilizing Suzuki Nex vehicles, and violations involving driver's licenses (SIM) as well as carrying more than one passenger. Cluster 3 involves traffic violation data associated with individuals aged 17 to 25 years, employing Honda Vario 150 vehicles, and violations linked to driver's licenses (SIM