IMPLEMENTASI METODE GAUSSIAN NAIVE BAYES UNTUK SEGMENTASI TAGIHAN PAJAK PIUTANG PERUSAHAAN STUDI KASUS (KPP PRATAMA JAKARTA KALIDERES)

EVARDO, WIGI JULIO (2024) IMPLEMENTASI METODE GAUSSIAN NAIVE BAYES UNTUK SEGMENTASI TAGIHAN PAJAK PIUTANG PERUSAHAAN STUDI KASUS (KPP PRATAMA JAKARTA KALIDERES). S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

This research focuses on the application of the Gaussian Naive Bayes method to classify company receivable tax bills at KPP Pratama Jakarta. classifying company receivable tax bills at KPP Pratama Jakarta Kalideres. The background of this research is the existence of taxpayers who are not fully compliant in paying taxes, which results in a decrease in tax revenue. not fully compliant in paying taxes, which results in a decrease in state revenue. revenue. To improve the efficiency of tax collection, this study uses the uses the Gaussian Naive Bayes algorithm to classify the accounts receivable of companies that are often in arrears of tax payments. companies that often default on tax payments. The dataset used in This research was obtained from KPP Pratama Jakarta Kalideres. Implementation implementation is done using the Python programming language in the Google Colab environment. Colab environment. Performance evaluation of the classification method is done using confusion matrix to assess the accuracy and effectiveness of the prediction. Research results The results show that the Gaussian Naive Bayes method is able to provide accurate and useful predictions in improving the efficiency of tax collection at the KPP Pratama. accurate and useful in improving tax collection efficiency at KPP Pratama Jakarta Kalideres. Jakarta Kalideres. This research is expected to help increase state revenue from the tax sector as well as providing guidance for tax officers in determining collection priorities. in determining collection priorities. Keywords: Gaussian Naive Bayes, segmentation, tax bill, company receivables, KPP Pratama Jakarta Kalideres, data mining, classification, confusion matrix. Penelitian ini berfokus pada penerapan metode Gaussian Naive Bayes untuk mengelompokkan tagihan pajak piutang perusahaan di KPP Pratama Jakarta Kalideres. Latar belakang penelitian ini adalah adanya wajib pajak yang belum sepenuhnya patuh dalam membayar pajak, yang mengakibatkan penurunan penerimaan negara. Untuk meningkatkan efisiensi penagihan pajak, penelitian ini menggunakan algoritma Gaussian Naive Bayes guna mengklasifikasikan piutang perusahaan yang sering menunggak pembayaran pajak. Dataset yang digunakan dalam penelitian ini diperoleh dari KPP Pratama Jakarta Kalideres. Implementasi dilakukan dengan menggunakan bahasa pemrograman Python di lingkungan Google Colab. Evaluasi kinerja metode klasifikasi dilakukan menggunakan confusion matrix untuk menilai akurasi dan efektivitas prediksi. Hasil penelitian menunjukkan bahwa metode Gaussian Naive Bayes mampu memberikan prediksi yang akurat dan berguna dalam meningkatkan efisiensi penagihan pajak di KPP Pratama Jakarta Kalideres. Penelitian ini diharapkan dapat membantu meningkatkan penerimaan negara dari sektor pajak serta memberikan panduan bagi petugas pajak dalam menentukan prioritas penagihan. Kata kunci: Gaussian Naive Bayes, segmentasi, tagihan pajak, piutang perusahaan, KPP Pratama Jakarta Kalideres, data mining, klasifikasi, confusion matrix.

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 24 122
Call Number:	SIK/15/24/086
NIM/NIDN Creators:	41520110020
Uncontrolled Keywords:	Gaussian Naive Bayes, segmentasi, tagihan pajak, piutang perusahaan, KPP Pratama Jakarta Kalideres, data mining, klasifikasi, confusion matrix
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma 600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 657 Accounting/Akuntansi > 657.4 Specific Fields of Accounting/Bidang Akuntansi Tertentu > 657.46 Tax Accounting/Akuntansi Pajak
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	khalimah
Date Deposited:	02 Aug 2024 06:00
Last Modified:	02 Aug 2024 06:00
URI:	http://repository.mercubuana.ac.id/id/eprint/90001

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