Analisis Sentimen Pelayanan Pembayaran Pajak Menggunakan Metode Algoritma Naïve Bayes Pada Kantor Badan Pendapatan Daerah Labuhanbatu Utara Dengan Menggunakan RapidMiner

Mhd. Rafly Purba, Syaiful Zuhri Harahap, Fitri Aini Nasution, Budianto Bangun

Abstract


Improving the quality of Public Services is a major need in the era of digitalization, including in the local taxation sector related to the sentiment of services provided in tax payments. The purpose of this study was to analyze public sentiment towards tax payment services in the Office of the regional Revenue Agency (Bapenda) Labuhanbatu Utara by applying Naïve Bayes algorithm using Rapid Miner software. Data analysis through text preprocessing, feature selection, and sentiment classification into positive, negative, and neutral categories. The Data obtained consisted of 225 community comments from the SIMPATDA application and 612 tweets with the hashtag #pajakLabura from Twitter, which reflected people's opinions directly. The analysis process is carried out through the stages of text preprocessing, feature selection, to the classification of sentiments into positive, negative, and neutral categories. The results showed that the Naïve Bayes algorithm is able to classify public opinion with a high degree of accuracy and establish similarities/differences in the aspects of service that are most complained about or appreciated by the public. This study also contributes to the development of data-based evaluation system in the scope of public services.


Full Text:

PDF

References


Abei, F. S. (2025, Januari). Twitter Sentiment Towards 2024 Jakarta Governor Candidates With Naïve Bayes Algorithm. Journal of Computer Networks, Architecture and, Volume 7, Number 1, 265-277. DOI : 10.47709/cnahpc.v7i1.5358

Afuan, L. K. (2025). Peningkatan Analisis Sentimen Pelantikan Presiden RI 2024 pada X Menggunakan Klasifikasi Naïve Bayes yang Dioptimalkan SMOTE. Jurnal Teknik Informatika (Jutif), 6(1), 16-25. DOI : 10.52436/1.jutif.2025.6.1.4290

Amini, T. &. (2024). Application of the Naïve Bayes Algorithm in Twitter Sentiment Analysis of 2024 Vice Presidential Candidate Gibran Rakabuming Raka using RapidMiner. International Journal Software Engineering and Computer Science, 4(1), 234–246. DOI : 10.35870/ijsecs.v4i1.2236

Bahtiar, S. A. (2023, agustus). Perbandingan Naïve Bayes dan Regresi Logistik dalam Analisis Sentimen pada Ulasan Marketplace Menggunakan Pelabelan Berbasis Peringkat. Journal of Information Systems and Informatics, 5(3), 915–927. DOI : 10.51519/journalisi.v5i3.539

Br Sembiring, B. S. (2023, Agustus). Naïve Bayes Classifier and Decision Tree Algorithms for Classifying Payment Data. KLIK: Journal of Information Technology, 15-16. DOI : 10.30865/klik.v4i1.963.

Cahya, L. D. (2023, Juli). Analisis Sentimen pada Teknologi Kecerdasan Buatan Menggunakan Klasifikasi Naïve Bayes. Inovasi Pembangunan: Jurnal Kelitbangan, 12(3). DOI : 10.35450/jip.v12i03.637

Calvin Suoth, et.al. (2022). ANALISIS EFEKTIVITAS PENERIMAAN PAJAK DAERAH DI KABUPATEN MINAHASA. Jurnal EMBA, 10 (1). https://ejournal.unsrat.ac.id/v2/index.php/emba/article/view/38488/35109

Danyal, M. M. (2023). Sentiment Analysis Based on Performance of Linear SVM and Multinomial Naïve Bayes Using Movie Reviews with Baseline Techniques. Journal on Big Data, 1–18. DOI : 10.32604/jbd.2023.041319

Dinov, I. (2023). Data Science and Predictive Analytics: Biomedical and Health Applications Using R (2nd ed.). Springer. DOI : 10.1007/978-3-031-17483-4

Eka Putri Adamansyah1, A. Y. (2025, Maret). Evaluasi Opini Publik di Media Sosial X terhadap Kebijakan Pajak Pertambahan Nilai 12% di Indonesia Menggunakan Naive Bayes dan Decision Tree. Jurnal Pengembangan Teknologi Informasi (JPTI), Vol.5, No. 3, 831-843. DOI : https://doi.org/10.52436/1.jpti.710

Endang Winarsih. (2022). EVALUASI PERHITUNGAN, PEMOTONGAN, PENYETORAN DAN PELAPORAN PAJAK PENGHASILAN (PPh) PASAL 21 ATAS KARYAWAN TETAP (STUDI KASUS PADA KANTOR WILAYAH VI PT PEGADAIAN MAKASSAR). RESTITUSI : Jurnal Riset Perpajakan, 1 (2). DOI : https://doi.org/10.33096/restitusi.v1i02.406

Fachri Zaini, F. S. (2023). ANALYSIS OF PUBLIC SENTIMENT RELATED TO THE FAILURE OF INDONESIA TO HOST U-20 USING MULTINOMIAL NAÏVE BAYES CLASSIFIER. Jurnal Teknik Informatika, VOL. 4 NO. 6 . DOI : https://doi.org/10.52436/1.jutif.2023.4.6.1209

Hijrah. (2022, Juni). Analisis Perbandingan Aplikasi Data Mining Dalam Memprediksi Kualitas Kinerja Karyawan Menggunakan Metode Algoritma C4.5. JATISI (Jurnal Teknik Informatika dan Sistem Informasi), 9(2), 1655-1665. DOI : 10.35957/jatisi.v9i2.1992

Khaira, U. A. (2023). Komparasi Algoritma Naïve Bayes dan Support Vector Machine (SVM) pada Analisis Sentimen Kebijakan Kuota Internet Kemdikbudristek. Jurnal Processor, 18(2), 897. DOI : 10.33998/processor.2023.18.2.897

Leandro, J. O. (2023). Evaluasi Metode Analisis Sentimen untuk Aplikasi Media Sosial: Perbandingan SVM dan Naïve Bayes. JOIV, 9(2), 796–807. DOI : 10.62527/joiv.9.2.2905

Martiti, . J. (2021). Implementation of Naive Bayes Algorithm on Sentiment Analysis Application. Atlantis Press. DOI : 10.2991/aer.k.211106.030

Maskur, M. A. (2024, JULI). Taxpayer Awareness Classification Using Decision Tree and Naïve Bayes Methods. Journal of Applied Informatics and Computing, 8(1), 47-54. DOI : 10.30871/jaic.v8i1.6654.

Maulana, B. A. (2024). Analisis Sentimen Terhadap Aplikasi Pluang Menggunakan Algoritma Naive Bayes dan Support Vector Machine (SVM. MALCOM Indonesian Journal of Machine Learning and Computer Science, 4(2), 375–384. DOI : 10.57152/malcom.v4i2.1206

Murni, M. &. (2024). Pengaruh Pengetahuan Perpajakan, Kesadaran Wajib Pajak... terhadap Kepatuhan Wajib Pajak Orang Pribadi. jurnal Akuntansi dan Pajak, 24(2), 17–27. DOI : https://doi.org/10.32815/ristansi.v3i2.1232

Normawati, N. &. (2022). mplementasi Naïve Bayes Classifier dan Confusion Matrix pada Analisis Sentimen Berbasis Teks pada Twitter. JSAKTI, 5(2), 19–25. DOI : 10.30645/jsakti.v5i2.428

Pasaribu, N. A. (2023, Desember). The Shopee Application User Reviews Sentiment Analysis Employing Naïve Bayes Algorithm. IJSECS, 3(3), 194–204. DOI : 10.35870/ijsecs.v3i3.1699

Permadi. (2020). Analisis Sentimen Menggunakan Algoritma Naive Bayes Terhadap Review Restoran di Singapura. Jurnal Buana Informatika, 11(2), 87–93. DOI : 10.24002/jbi.v11i2.3950

Permadi, V. A. (2020). Analisis Sentimen Menggunakan Algoritma Naive Bayes Terhadap Review Restoran di Singapura. Jurnal Buana Informatika, 11(2), 87–93. DOI : 10.24002/jbi.v11i2.3950

Prayudani, S. S. (2024, Oktober). Sentiment Analysis of Social Media X in the 2024 Indonesian Presidential Election Using the Naive Bayes Algorithm: Candidates’ Backgrounds and Political Promises. ournal of Applied Informatics and Computing, 8(2), 291–295. DOI : 10.30871/jaic.v8i2.7580

Ratnawati, F. (2018). Implementasi Algoritma Naive Bayes Terhadap Analisis Sentimen Opini Film Pada Twitter. Jurnal Inovtek Polbeng, 3(1), 499–507. DOI : 10.35314/inovtek.v3i1.649

Sri Mulyani Anugerah, R. W. (2024, April). Sentimen Analysis Social Media for Disaster using Naïve Bayes and IndoBERT. INTEK: Jurnal Penelitian. DOI : 10.31963/intek.v11i1.4771

Srijanti & Tobing, F. A. (2023, November). Implementation of Naïve Bayes Algorithm in Sentiment Analysis of Twitter Social Media Users Regarding Their Interest to Pay the Tax. International Journal of Science, Technology & Management, 55-56. DOI : 10.46729/ijstm.v4i6.1015

Trisnawati, N. N. (2023). Analisis Sentimen Terhadap Direktorat Jenderal Pajak Menggunakan Algoritma Naive Bayes dengan Hbrid Adaptive Boosting. In T. Akhir. Manado: Universitas Katolik De La Salle . Skripsi.

Wibowo, M. R. (2024, Juli). Taxpayer Awareness Classification Using Decision Tree and Naive Bayes Methods. Journal of Applied Informatics and Computing(Vol. 8 No. 1 (2024): July 2024), 51-55. DOI : https://doi.org/10.30871/jaic.v8i1.6654

Widyanto, T. R. (2023). Komparasi Naïve Bayes dan SVM Analisis Sentimen RUU Kesehatan di Twitter. SINTECH (Science and Information Technology) Journal, 6(3), 147–161. DOI : 10.31598/sintechjournal.v6i3.1433

Zulfikar, W. B. (2023). Sentiment Analysis on Social Media Against Public Policy Using Multinomial Naïve Bayes. Scientific Journal of Informatics, 10(1), 90. DOI : 10.15294/sji.v10i1.39952

Zulfikar, W. B. (2023). Sentiment Analysis on Social Media Against Public Policy Using Multinomial Naïve Bayes. Scientific Journal of Informatics, 1-12. DOI : 10.15294/sji.v10i1.39952




DOI: https://doi.org/10.36987/jcoins.v6i3.7959

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Hasil gambar untuk committee on publication ethics logo

Jurnal ini mengikuti pedoman dari Committee on Publication Ethics (COPE) dalam menghadapi semua aspek etika publikasi dan, khususnya, bagaimana menangani kasus penelitian dan kesalahan publikasi. Pernyataan ini menjelaskan etika perilaku semua pihak yang terlibat dalam proses penerbitan artikel di jurnal ini, termasuk Penulis, Pemimpin Redaksi, Dewan Redaksi, Mitra Bebestari, dan Penerbit (Akademi Kepolisian Republik Indonesia). Journal of Computer Science and Information System(JCoInS) berkomitmen untuk mengikuti praktik terbaik tentang masalah etika, kesalahan, dan pencabutan. Pencegahan malpraktek publikasi merupakan salah satu tanggung jawab penting dewan redaksi. Segala jenis perilaku tidak etis tidak dapat diterima, dan jurnal tidak mentolerir plagiarisme dalam bentuk apa pun.


Journal of Computer Science and Information System(JCoInS)

Journal URL: https://jurnal.ulb.ac.id/index.php/JCoInS/index
Journal DOI: 10.36987/jcoins
E-ISSN: 2747-2221

Alamat Redaksi :
Fakultas Sains dan Teknologi, Universitas Labuhanbatu
Gedung Fakultas Sains dan Teknologi,
Jalan Sisingamangaraja No.126 A KM 3.5 Aek Tapa, Bakaran Batu, Rantau Sel., Kabupaten Labuhan Batu, Sumatera Utara 21418