Non-Compliance Level of Motor Vehicle Taxpayer Classification

Motor vehicle taxes play a significant role in generating revenue for local governments, making it imperative to prioritize the collection of these taxes. In order to achieve the predetermined targets for motor vehicle tax revenue, it becomes necessary to closely monitor taxpayers who fail to comply with their tax payment obligations. This study focuses on classifying taxpayers into three distinct categories using the Objects and Subjects Data Collection Letter (SPOS), Tax Calculation Note (NPP), and Tax Bill Note (NTP) as classification criteria. To compare the performance of different Machine Learning algorithms, the classification process is conducted. The evaluation of algorithm performance is carried out using the 10 Folds Cross Validation method with a data split of 60:40, and metrics such as Accuracy, Precision, Recall, and F1-score are employed to assess algorithm effectiveness.