Segmentation Of Vehicle Delivery Test Services Using K-Means Clustering Case Study Of West Pasaman District Transportation Services - Azwar, Meiriza; Azwar , Tasrika; Heikal, Jerry (Jurnal Ekonomika Dan Bisnis (JEBS), 2024)
This research aims to segment services using the K-Means Clustering method in the case of Vehicle KIR Test services. Service segmentation is important to understand the time, place and type of vehicle to be tested, so that the West Pasaman Regency Transportation Service can direct service efforts more effectively. The K-Means Clustering method is used to group customers based on certain attributes, such as test location, test time, vehicle type and test status. KIR test service data is collected, including variables such as test location, test time, test status and type of vehicle to be tested. Research data was analyzed using K-Means Clustering analysis. The research results are categorized into 3 clusters, namely: 1. First cluster: KIR services with work as a trader, income around Rp. 3,473,882, located in the Ranah Batahan District area, the average visit time is 13.18 WIB which is also influenced by the distance traveled by KIR officers from Simpang Empat to Ranah Batahan ±82.3Km, 2. Second Cluster: KIR services with traders earning Rp. . 2,606,324, with the aim of KIR services to Koto Balingka District with a distance of ±56.3 Km and an average visiting hour of 10.37 WIB, the type of vehicle that is often tested is goods cars.3. Third Cluster: KIR services with self-employed work earning Rp. 4,544,071, with the aim of the KIR service to Pasaman District and the average visiting time is 11.05 WIB, the type of vehicle that is often tested is the trailer/outboard carriage.