Analysis of Property Tax Payment Compliance Classification in Tebing Tinggi City Using the C4.5 Decision Tree Algorithm
DOI:
https://doi.org/10.61306/jitcse.v1i2.59Keywords:
Property Tax Payment Compliance, C4.5 Decision Tree, Data MiningAbstract
This research analyzes property tax payment compliance in Tebing Tinggi City using the C4.5 Decision Tree algorithm. With the rapid advancement of data mining technology, this analysis utilizes classification techniques to identify compliance patterns based on property tax payment data. The research methodology involves data collection, preprocessing, and building the Decision Tree model using RapidMiner. The results indicate that the Decision Tree model can effectively predict compliance levels based on attributes such as Total_Payment and Total_Bill. Individuals with higher payment and bill values tend to be compliant, while those with lower values show less compliance. These findings provide insights for authorities to design more effective strategies to improve tax compliance and identify areas that require special attention in Tebing Tinggi City.
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