PENERAPAN ALGORITMA K-MEANS CLUSTERING PADA ANALISIS POLA PENDAFTARAN CALON JAMAAH HAJI DI KANTOR WILAYAH KEMENTERIAN AGAMA PROVINSI JAMBI
DOI:
https://doi.org/10.53564/ewcdte47Keywords:
Clustering, Data Mining, Hajj Registration, K-Means, Ministry of Religious AffairsAbstract
This study aims to analyze the registration patterns of prospective hajj pilgrims at the Regional Office of the Ministry of Religious Affairs of Jambi Province using the K-Means Clustering algorithm. The main issue addressed is the high volume of hajj applicants each year without adequate pattern analysis, which complicates quota planning and pilgrim guidance. The dataset includes the number of hajj applicants per regency/city from 2018 to 2024, with attributes such as applicant count, age, and gender. The clustering process was carried out using K-Means with k = 3, resulting in three main clusters: high, medium, and low registration rates. The results show that Batanghari Regency and Jambi City belong to the high cluster, while Tebo and Sarolangun are in the low cluster. These findings provide better insights for policymakers in managing hajj quotas and improving outreach strategies.
References
[1] Z. M. et al., “Efektivitas Sistem Komputerisasi Haji Terpadu (SISKOHAT),” J. Adm. Publik, 2019.
[2] L. Hakim, “Analisis tren pendaftaran jamaah haji di Indonesia,” J. Keagamaan dan Data Stat., vol. 4, no. 1, 2019.
[3] “PENERAPAN SISTEM INFORMASI KOMPUTERISASI HAJI TERPADU DALAM MENINGKATKAN KEPUASAN CALON JAMA’AH HAJI DI KANTOR KEMENTERIAN AGAMA,” 2023.
[4] R. A. Harahap, “PENERAPAN SISTEM INFORMASI KOMPUTERISASI HAJI TERPADU DALAM MENINGKATKAN KEPUASAN CALON JAMA’AH HAJI DI KANTOR KEMENTERIAN AGAMA,” 2023, [Online]. Available: https://repository.iainpare.ac.id/id/eprint/1673/1/15.3300.019.pdf
[5] T. Hidayat, “Klasifikasi Data Jamaah Umroh Menggunakan Metode K-Means Clustering,” J. Sistim Inf. dan Teknol., vol. 4, pp. 19–24, 2022, doi: 10.37034/jsisfotek.v4i1.115.
[6] L. Rokach and O. Maimon, “Clustering methods,” Data Min. Knowl. Discov. Handb., 2005.
[7] D. M. Shella, “Implementasi Algoritma K-Means untuk Clustering Wilayah Jamaah Haji KBIH Jabal Nur Pendahuluan,” 2025.
[8] M. Yunitasari, T. Maharani, and B. Hikmahwan, “Implementasi Metode K-Means Untuk Pengelompokan Data Jamaah,” Kumpul. J. Ilmu Komput., vol. 09 No. 1, no. 1, pp. 1–9, 2022.
[9] W. Lestari, “Clustering Data Mahasiswa Menggunakan Algoritma K-Means Untuk Menunjang Strategi Promosi (Studi Kasus : STMIK Bina Bangsa Kendari),” Simkom, vol. 4, no. 2, pp. 35–48, 2019, doi: 10.51717/simkom.v4i2.37.
[10] T. Humaira Mufidah, M. Risky, Z. Anshori, and D. Jenderal Penyelenggaraan Haji dan Umrah Kementerian Agama, “IMPLEMENTASI ALGORITMA K-MEANS DALAM MENENTUKAN CLUSTERING PADA PENILAIAN VERIFIKASI PPIU,” J. Media Infotama, vol. 19, no. 1, pp. 3–4, 2023.
[11] Kementerian Agama Republik Indonesia, “Kebijakan Penyelenggaraan Ibadah Haji di Indonesia,” Kementeri. Agama RI, 2020.
[12] T. I. Berikut et al., “visualisasi Data 2.1,” pp. 9–32, 2018.
[13] Y. Darmi and A. Setiawan, “PENERAPAN METODE CLUSTERING K-MEANS DALAM,” vol. 12, no. 2, pp. 148–157, 2016.
[14] E. H. Wisanta and Y. N. Marlim, “Analisis Algoritma K-Means Untuk Clustering Kepuasan Pelayanan: Mall Pelayanan Publik Pekanbaru,” Semin. Nas. Inform. Pros. Senat. 2021, pp. 223–228, 2021.
[15] M. Yunitasari and others, “Implementasi metode K-Means untuk pengelompokan data jamaah pada Biro Umroh Jabal Rahmah Pacitan,” KLIK, 2022, [Online]. Available: https://klik.ulm.ac.id/index.php/klik/article/view/402
[16] R. Saputra, “Clustering Data Kependudukan Menggunakan K-Means,” J. Ilm. Inform., 2022.
[17] M. Darul and F. Pati, “EFEKTIVITAS SISTEM INFORMASI DAN KOMPUTERISASI HAJI TERPADU ( SISKOHAT ) DALAM PENYELENGGARAAN IBADAH HAJI Zahrotun Munawaroh , M . Mudhofi , Dedy Susanto berhaji .,” pp. 225–248.
[18] N. N. Alyarahma and C. Sormin, “Analisis Cluster Metode K-Means untuk Indikator Kependudukan pada Kabupaten/Kota di Provinsi Jambi,” Multi Prox. J. Stat., vol. 2, no. 2, pp. 136–6, 2023.
[19] Y. Darmi and A. Setiawan, “Penerapan Metode Clustering K-Means dalam Pengelompokan Data,” J. Media Infotama, vol. 12, no. 2, pp. 148–157, 2016.
[20] S. Amalia and H. Hidayatullah, “Pengelompokan data antrian pelayanan menggunakan algoritma K-Means,” J. Komputasi, vol. 18, no. 2, 2021.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 FORTECH (Journal of Information Technology)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
