Analysis of Property Tax Bill Classification Using the C4.5 Algorithm - Andysah Putera Utama Siahaan; Ami Abdul Jabar; Sugeng Pranoto; Sulis Sutiono; Desy Ramatika (Yayasan Sinergi Multidimensi Kreatif, 2024)
This study analyzes the classification of Property Tax (Pajak Bumi dan Bangunan, PBB) bills in Tebing Tinggi City using the C4.5 algorithm to improve tax management efficiency. The secondary data used consists of 56,332 entries related to PBB for the 2022-2023 tax year. Using data mining methods and decision tree modeling, the C4.5 algorithm successfully classified taxpayers based on their total bill amount into five categories of tax books. The analysis results show that the majority of taxpayers are classified into categories with lower bills (Books I and II), while high-bill taxpayers (Book V) represent only a small portion of the data. These findings can help local governments design more efficient tax collection policies and adjust resource allocation. Although the study is limited to a single tax year and a specific region, these results contribute to data mining-based PBB management and can serve as a foundation for further research.