Penerapan Algoritma K-Means Untuk Menentukan Kelas Besar Tunggakan Pajak Kendaraan Bermotor Pada SAMSAT Parigi Moutong

Abstract

Tax is a mandatory contribution imposed on citizens and serves as a significant source of state revenue, used for development as mandated by law. One major tax type in Indonesia is the motor vehicle tax, managed by the One-Stop Administrative System (SAMSAT) at the district level. Each district, including Parigi Moutong (Parimo), has a SAMSAT office responsible for managing motor vehicle tax, including arrears. The high number of registered vehicles at SAMSAT Parimo corresponds to the large volume of data managed, including tax arrears data. Motor vehicle tax arrears vary for each taxpayer and influence policy decisions by SAMSAT. To address the variation in tax amounts and required actions, data classification based on tax arrears is necessary. The advancement of technology and computational algorithms allows large data sets to be processed effectively through data mining methods. This research explores the application of data mining techniques to classify motor vehicle tax arrears and assist SAMSAT Parimo in optimizing tax management.