Analisis Kepuasan Masyarakat Terhadap Proses Pengurusan Sertipikat Analog Ke Elektronik Menggunakan Metode Naïve Bayes
DOI:
https://doi.org/10.47065/bulletincsr.v5i5.758Keywords:
Naïve Bayes; Satisfaction Level; Electronic Certificate; Digital Public Services; ClassificationAbstract
The certificate media conversion program from analog to electronic implemented by the Ministry of ATR/BPN in Sejati Village requires evaluation to ensure its effectiveness. The main problem faced is the limited use of quantitative, data-driven analysis in identifying the factors that influence public satisfaction. This study aims to analyze the level of public satisfaction using the Naïve Bayes method to classify and predict the influence of related variables. Data were obtained from 250 respondents through questionnaires based on digital public service indicators, covering demographic variables, perceived benefits, obstacles, support, service speed, and procedural simplicity. The results show that the level of public satisfaction is in the high category, with procedural simplicity and service speed proven to be the most significant variables influencing satisfaction prediction. The Naïve Bayes model achieved an accuracy of 94%, demonstrating its effectiveness in predicting satisfaction levels. These findings serve as a basis for improving policies and strategies to enhance the quality of digital public services, particularly in the implementation of electronic certificate media conversion in the future.
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References
T. H. Salsabila, T. M. Indrawati, and R. A. Fitrie, “Meningkatkan Efisiensi Pengambilan Keputusan Publik melalui Kecerdasan Buatan,” J. Internet Softw. Eng., vol. 1, no. 2, p. 21, 2024, doi: 10.47134/pjise.v1i2.2401.
H. Maulana, N. Nugraha, R. Arinda, M. Fikri, and R. Wahanisa, “Urgensi Sertifikat Elektronik dengan Pemantauan Berbasis AI untuk Efisiensi Pendaftaran Tanah dan Mitigasi Mafia Tanah di Indonesia,” J. Cust. Law, vol. 2, no. 1, p. 9, 2024, doi: 10.47134/jcl.v2i1.3304.
A. Adekamwa, M. Mursalim, and I. Indrayanti, “Tren Penelitian Pelayanan Publik Di Indonesia: Suatu Tinjauan Sistematis Literatur,” J. Adm. Negara, vol. 30, no. 3, pp. 240–263, 2024, doi: 10.33509/jan.v30i3.3420.
Dini Oktaviani, Syarifah Putri Agustini Alkadri, and Sucipto Sucipto, “Klasifikasi Tingkat Kepuasan Pelayanan Pembuatan Paspor Menggunakan Algoritma Naïve Bayes,” Jural Ris. Rumpun Ilmu Tek., vol. 4, no. 1, pp. 129–144, 2025, doi: 10.55606/jurritek.v4i1.4572.
V. No, M. N. Romadhoni, N. Anisa, and S. Winarsih, “Edumatic?: Jurnal Pendidikan Informatika Kinerja Naive Bayes dan SVM pada Data Survei Tidak Seimbang?: Studi Klasifikasi Kepuasan Masyarakat,” vol. 9, no. 2, pp. 382–391, 2025, doi: 10.29408/edumatic.v9i2.30185.
C. Paramita, F. A. Rafrastara, and L. I. Kencana, “Pengembangan Sistem Klasifikasi Karakteristik Siswa Berbasis Website dengan menggunakan Algoritma C4.5,” J. Inform. J. Pengemb. IT, vol. 8, no. 1, pp. 17–21, 2023, doi: 10.30591/jpit.v8i1.4678.
A. Pemerintah and D. Di, “The Jure: Journal of Islamic Law, Vol. 2, No. 2, Juli 2025 Ahmad Nurun, Ira Nova Yuniar,” vol. 2, no. 2, pp. 193–199, 2025.
Heliyanti Susana, “Penerapan Model Klasifikasi Metode Naive Bayes Terhadap Penggunaan Akses Internet,” J. Ris. Sist. Inf. dan Teknol. Inf., vol. 4, no. 1, pp. 1–8, 2022, doi: 10.52005/jursistekni.v4i1.96.
C. Dewi, R. C. Chen, H. J. Christanto, and F. Cauteruccio, “Multinomial Naïve Bayes Classifier for Sentiment Analysis of Internet Movie Database,” Vietnam J. Comput. Sci., vol. 10, no. 4, pp. 485–498, 2023, doi: 10.1142/S2196888823500100.
J. W. D. Wang, “Naïve Bayes is an interpretable and predictive machine learning algorithm in predicting osteoporotic hip fracture in-hospital mortality compared to other machine learning algorithms,” PLOS Digit. Heal., vol. 4, no. 1, pp. 1–22, 2025, doi: 10.1371/journal.pdig.0000529.
M. Romano, G. Zammarchi, and C. Conversano, Iterative threshold-based Naïve bayes classifier, vol. 33, no. 1. Springer Berlin Heidelberg, 2024. doi: 10.1007/s10260-023-00721-1.
M. W. Khoiriyah, I. H. Santi, and R. D. Romadhona, “Analisis Algoritma C4.5 dan Naïve Bayes dalam Menentukan Tingkat Kepuasan Publik di RUPBASAN Kelas 2 Blitar,” J. Inform. Polinema, vol. 11, no. 1, pp. 13–18, 2024, doi: 10.33795/jip.v11i1.5831.
S. A. Habibi, G. S. Prambudi, T. Trisnawati, and R. Wulandari, “Transformasi Digital Administrasi Pertanahan?: Implementasi Dan Tantangan Sertipikat Elektronik Di Indonesia,” 2025.
P. Degodona, B. J. Gulo, and L. K. Simanjorang, “Suatu Kajian Tentang Kepuasan Masyarakat Terhadap Pelayanan Publik Berdasarkan UU No. 25 Tahun 2009,” J. Ilmu Sos. Dan Polit., vol. 3, no. 1, pp. 35–53, 2023, doi: 10.51622/jispol.v3i1.1341.
S. Wirma, “Data Mining Dengan Metode Naïves Bayes Classifer dalam Memprediksi Tingkat Kepuasan Pelayanan Dokumen Kependudukan,” J. Inform. Ekon. Bisnis, vol. 4, no. 3, pp. 156–160, 2022, doi: 10.37034/infeb.v4i3.155.
R. R. Aliyyah, D. I. Sukmayanti, G. Rahayu, S. Habibah, E. Faridah, and V. Oktaviany, “Community Service in the Form of Academic Writing Training,” JCES (Journal Character Educ. Soc., vol. VI, no. 2, pp. 324–335, 2023, [Online]. Available: http://journal.ummat.ac.id/index.php/JCES/article/view/9865
N. K. L. A. Santi, P. I. Rahmawati, and T. Trianasari, “Analisis Kepuasan Masyarakat Terhadap Pelayanan Publik (Studi Tentang Pelayanan Administratif, Pelayanan Barang Dan Pelayanan Jasa Pemerintah Desa Siakin Kecamatan Kintamani Kabuaten Bangli),” Cakrawala Repos. IMWI, vol. 6, no. 6, pp. 2643–2661, 2024, doi: 10.52851/cakrawala.v6i6.576.
Hartatik and D. Lestari, “Implementasi Algoritma Naive Bayes Untuk Menentukan Tingkat Kepuasan Masyarakat Terhadap Pelayanan Publik (Studi Kasus?: Balai Pengkajian Teknologi Pertanian Daerah Istimewa Yogyakarta),” J. Inform. Komputer, Bisnis dan Manaj., vol. 17, no. 2, pp. 37–46, 2023, doi: 10.61805/fahma.v17i2.95.
Hizbul Izzi, Arief Setyanto, and Anggit Dwi Hartanto, “Optimalisasi Akurasi Algoritma Naïve Bayes Dengan Metode Syntetic Minority Oversampling Technique (Smote) Pada Data Numerik,” Infotek J. Inform. dan Teknol., vol. 8, no. 1, pp. 217–227, 2025, doi: 10.29408/jit.v8i1.28340.
M. R. Fanani and D. S. Sintia, “Klasifikasi Kesiapan Anak Masuk Sekolah Dasar menggunakan Algoritma Naïve Bayes dan Algoritma C4.5,” Innov. J. Soc. Sci. Res., vol. 4, no. 3, pp. 10547–10555, 2024, doi: 10.31004/innovative.v4i3.10425.
L. Kusbudiyanto, D. Kurniawan, and P. L. Samputra, “Evaluasi Tingkat Kepuasan Masyarakat Terhadap Pelayanan Publik Di Dinas Kependudukan Dan Pencatatan Sipil Kota Bekasi,” JANE - J. Adm. Negara, vol. 15, no. 1, p. 55, 2023, doi: 10.24198/jane.v15i1.20958.
R. Syahputra, “Identifikasi Kerusakan PC (Personal Computer) dengan Metode Teorema Bayes Pada Laboratorium Komputer STMIK Triguna Dharma,” J-SISKO TECH (Jurnal Teknol. Sist. Inf. dan Sist. Komput. TGD), vol. 4, no. 1, p. 20, 2021, doi: 10.53513/jsk.v4i1.2607.
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