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All Journal E-Jurnal Matematika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Sains Matematika dan Statistika Format : Jurnal Imiah Teknik Informatika EIGEN MATHEMATICS JOURNAL International Journal of Engineering, Technology and Natural Sciences (IJETS) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Ilmu Komputer dan Informatika Jurnal Eurekamatika UPGRADE: Jurnal Pendidikan Teknologi Informasi Diophantine Journal of Mathematics and Its Applications
Moch Anjas Aprihartha
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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Journal : Format : Jurnal Imiah Teknik Informatika

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Studi Tentang Algoritma C5.0 Dalam Memprediksi Kepatuhan Nasabah Dalam Membayar Pajak Pertambahan Nilai Aprihartha, Moch Anjas; Husniyadi, M.; Alam, Taufik Nur
FORMAT Vol 13, No 1 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2024.v13.i1.001

Abstract

Data mining is the process of extracting valuable patterns, information, and knowledge from large data sets. Data mining has an important role in identifying and minimizing risks in various lives. One of the algorithms of data mining is the decision tree type C5.0. The C5.0 algorithm is an algorithm used to solve classification problems. The C5.0 method can be applied in various sectors such as the taxation sector. Paying taxes is an obligation by an individual or entity paid to the State. The value added tax is the highest contributory tax because it is collected several times to companies. Factors that affect customer compliance in paying value added tax are income, entity form, and reporting status. This study aims to predict public compliance in paying value added tax using the C5.0 method. This research aims to produce a classification model that can be a potential solution for dealing with prediction problems in customer compliance with paying taxes. The results of the study obtained an average accuracy of the C5.0 model of 66,5%. Based on this accuracy value, the model can be categorized as still weak in predicting the status of value added tax payments.
Co-Authors Achmad Wahid Kurniawan Ahardika Nurfaizal, Fatma Akrom, Muhamad Alam, Taufik Nur Andrianza, Muhammad Rafly Ayu Pertiwi Azizah, Rahmatul Azzahro, Salwa Paramita Budi, Setyo Dicky Zulhan Fatma Ahardika Nurfaizal Fitri Astutik Hady Rasikhun Harun Al Azies Herowati, Wise Hidayat, Novianto Nur Husniyadi, M. Idham Idham Ignatius Moses Setiadi, De Rosal JUS PRASETYA Jus Prasetya Muhammad Naufal, Muhammad Muljono Muljono Nani Sulistianingsih Noor Ageng Setiyanto, Noor Ageng Nurfaizal, Fatma Ahardika Prabowo, Wahyu Aji Eko Prasetya, Jus Putrawan, Zulhandi Safitri, Aprilyani Nur Sefri Imanuel Fallo Sudibyo, Usman Supriadi Rustad T. Sutojo Trisnapradika, Gustina Alfa Zulhan , Dicky Zulhan, Dicky Zulhandi Putrawan