Penerapan Algoritma K-Means Pada Pengelompokan Kabupaten Dan Kota Berdasarkan Jumlah Kendaraan Bermotor Wilayah Provinsi Jawa Barat

Abstract

The vehicle is a tool that helps humans in completing work in daily activities. In the current digital era, the number of motorized vehicles is increasing rapidly, of various types and types of vehicles, which are currently developing a lot of digital technology in their features. With the increase in the number of vehicles, the impact on the number of motor vehicle users has increased dramatically, especially for land needs which we can find in big cities in Indonesia, this has an impact on traffic jams, West Java Province which has 27 administrative regions divided into 18 Regencies and 9 Cities are not spared from these traffic jams. Based on the latest data from the West Java Regional Revenue Agency (Bapenda.Jabar) in 2021 there were recorded data of 16,397,644 motorized vehicles. From the results of these data records, data mining methods with the K-Means algorithm can be used to find patterns that contain information that is useful for supporting decision making by parties who need it, such as regional financial institutions in channeling budgets in the infrastructure sector as well as by investors in determining areas to invest in. set up a business. By using the Clustering and Rapid Miner methods, the grouping of regions into 3 regions will result, namely high, medium and small potential areas based on the high mobility of the number of vehicles in the regency and city areas of West Java Province.

Keywords: Vehicles, Clustering, K-Means, Rapid Miner