Analisis Kepuasan Pelayanan Publik Menggunakan Metode Naïve Bayes Pada Dinas Kependudukan Dan Pencatatan Sipil Kabupaten Agam
Article Sidebar
Main Article Content
Abstract
This study aims to analyze public satisfaction with services provided by the Department of Population and Civil Registration (Disdukcapil) of Agam Regency using the Naïve Bayes method. The research data were collected from 252 respondents through a public satisfaction survey covering nine service indicators based on the Ministry of Administrative Reform Regulation No.16 of 2014. The Naïve Bayes algorithm was applied to classify satisfaction levels into four categories: very dissatisfied, dissatisfied, satisfied, and very satisfied. The results indicate that the developed web-based system can accurately predict public satisfaction levels, with the highest probability value of 0.1127 falling under the “very satisfied” category. These findings demonstrate that the service quality at Disdukcapil Agam Regency has been well implemented, and the application of the Naïve Bayes method is effective in supporting the evaluation and continuous improvement of public service performance.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Wirma, S. (2022). Data mining dengan metode Naïves Bayes classifier dalam memprediksi tingkat kepuasan pelayanan dokumen kependudukan. *Jurnal Informatika Ekonomi Bisnis*, 4(3), 119–123. http://www.infeb.org
Rahman, R., & Sutanto, F. A. (2023). Data mining untuk memprediksi tingkat kepuasan konsumen Gojek menggunakan algoritma Naive Bayes. *Jurnal Komtek: Jurnal Publikasi Ilmiah Bidang Teknologi.
Anis, et al., "Pelayanan Administrasi Kependudukan Sebagai Kebutuhan Dasar," Jurnal Pelayanan Publik, vol. 5, no. 2, pp. 90–101, 2021.
Saragih, R., Mardiah, & Deni Apriadi. (2024). Sentiment Analysis of Social Media Towards Public Services Using Naive Bayes and Text Mining. Journal of Computer Science Artificial Intelligence and Communications, 1(2), 30–34. DOI:10.62712/jocsaic.v1i2.18
Nasrulloh, W. K. U. (2025). Public Complaint Management Information System Based on Complaint Topic Classification Using the Naive Bayes Model. Journal of Management and Engineering, 1(1), 1–10.
Alannsary, M. O. (2025). Evaluating Citizen Satisfaction with Saudi Arabia's E-Government Services: A Standards-Based, Theory-Informed Approach. arXiv:2508.17912
Chen, Y. (2024). Can e-government online services offer enhanced governance capacity? Journal of Public Affairs, 24(1), e2599. DOI:10.1002/pa.2599
Fahr, M. C. (2024). Improving the use of public e-services through explainability. Information Systems Management, 41(1), 1–15. DOI:10.1080/10580530.2024.1851323
Hristova, G. (2022). Data mining of public opinion: An overview. AIP Conference Proceedings, 2505(1), 020004. DOI:10.1063/5.0081379
Liu, Y., & Zhang, Y. (2024). The impact of e-service quality on public trust and satisfaction: Evidence from China. International Journal of Digital and Network Sciences, 8(2), 45–58. DOI:10.1007/s42101-024-00123-4
Morgeson, F. V., & D'Innocenzo, L. (2024). Public satisfaction with government services hits highest level since 2017. Federal Employee Viewpoint Survey Results.
Kumar, S. S., & Chaubey, A. (2025). CHCs launch feedback system to improve health services in Jhansi. Times of India.
Sweeney, J., & Chung, E. (2025). Government digital services in need of overhaul, report finds. The Australian.
Purnandes, B., Chofa, F., & Farda, N. F. (2024). Efektivitas pelaksanaan pelayanan kependudukan dan pencatatan sipil Kabupaten Agam bagian timur.