Prediksi Capaian Bulanan Pajak Daerah Kabupaten Bandung Barat Menggunakan Metode Logistic Regression

Muhammad Ramdhani; Fajri Rakhmat Umbara; Ridwan Ilyas

doi:10.47065/josh.v5i4.5330

Muhammad Ramdhani * Universitas Jenderal Achmad Yani, Cimahi, Indonesia
Fajri Rakhmat Umbara Universitas Jenderal Achmad Yani, Cimahi, Indonesia
Ridwan Ilyas Universitas Jenderal Achmad Yani, Cimahi, Indonesia

(*) Corresponding Author

DOI: https://doi.org/10.47065/josh.v5i4.5330

Keywords: Data Mining; Taxes; Classification; Logistic Regression; Economy

Abstract

Tax is the main source of income for the state, so that tax revenue is the biggest contributor to government agencies. However, the Regional Revenue Agency (BAPENDA) sometimes has difficulties in predicting regional monthly income. The data owned by BAPENDA is very important for estimating tax increases every month, but often these estimates are wrong. Therefore, research on predicting monthly tax ACHIEVEMENT is very helpful. Researchers consider the data mining method approach is a technique that can help BAPENDA find predictive patterns that are important for making tax increase decisions. sebumnya has predicted the results of the Ann method where for neurons 20 it produces an rmse prediction of 0.12. In this study, the logistic regression algorithm approach was used to predict regional tax achievements in West Bandung Regency. In addition, experiments were carried out to evaluate which variables affect the probability value.

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