Penerapan Algoritma K-Means Dalam Pengelompokan Kepadatan Penduduk Menurut Kecamatan di Kabupaten Simalungun
Abstract
One of the problems related to population that still has to be faced by Simalungun is the problem of the imbalance in the distribution of the population. Incomplete division of the population brings problems to population density and population pressure in an area. This study uses data sources from the Central Statistics Agency (BPS) Simalungun. The data used in this study is data from 2015-2019 which consists of 32 Districts. Therefore, the researchers used the K-Means algorithm in clustering 32 sub-districts in Simalungun Regency. The data will be processed by clustering in 3 clusters, namely clusters with high population levels, clusters with moderate population levels and clusters with low population levels. The iteration process takes 5 times so that the results obtained are 4 sub-districts with high population level clusters (C1), 11 cluster sub-districts with moderate population level (C2) and 17 cluster sub-districts with low population level (C3)
Downloads
References
BPS Kabupaten Simalungun, “Indikator Kesejahteraan Rakyat Kabupaten Simalungun,” vol. 44102004, no. 1209, p. 22, 2019.
I. G. M. Y. Antara and I. G. P. E. Suryana, “Pengaruh Tingkat Kepadatan Penduduk Terhadap Indeks Pembangunan Manusia di Provinsi Bali,” Media Komun. Geogr., vol. 21, no. 1, p. 63, 2020, doi: 10.23887/mkg.v21i1.22958.
Y. H. Susanti and E. Widodo, “Perbandingan K-Means dan K-Medoids Clustering terhadap Kelayakan Puskesmas di DIY Tahun 2015,” Pros. SI MaNIs (Seminar Nas. Integr. Mat. dan Nilai Islam., vol. 1, no. 1, pp. 116–122, 2017.
R. Rosmini, A. Fadlil, and S. Sunardi, “Implementasi Metode K-Means Dalam Pemetaan Kelompok Mahasiswa Melalui Data Aktivitas Kuliah,” It J. Res. Dev., vol. 3, no. 1, pp. 22–31, 2018, doi: 10.25299/itjrd.2018.vol3(1).1773.
R. M. Sabiq and N. Nurwati, “Pengaruh Kepadatan Penduduk Terhadap Tindakan Kriminal,” J. Kolaborasi Resolusi Konflik, vol. 3, no. 2, pp. 161–167, 2021.
S. Handoko, F. Fauziah, and E. T. E. Handayani, “Implementasi Data Mining Untuk Menentukan Tingkat Penjualan Paket Data Telkomsel Menggunakan Metode K-Means Clustering,” J. Ilm. Teknol. dan Rekayasa, vol. 25, no. 1, pp. 76–88, 2020, doi: 10.35760/tr.2020.v25i1.2677.
A. N. Khomarudin, “Teknik Data Mining : Algoritma K-Means Clustering,” pp. 1–12, 2016.
A. A. Fajrin and A. Maulana, “Penerapan Data Mining Untuk Analisis Pola Pembelian Konsumen Dengan Algoritma Fp- Growth Pada Data Transaksi Penjualan,” vol. 05, no. 01, pp. 27–36, 2018.
T. R. Rivanthio, “Penerapan Metode Clustering K-Means Untuk Pengelompokan Prestasi Mahasiswa Di Politeknik LP3I Bandung,” vol. 8, no. 1, pp. 1–13, 2021.
R. W. Sari and D. Hartama, “Data Mining : Algoritma K-Means Pada Pengelompokkan Wisata Asing ke Indonesia Menurut Provinsi,” pp. 322–326, 2018.
D. Triyansyah and D. Fitrianah, “Analisis Data Mining Menggunakan Algoritma K-Means Clustering Untuk Menentukan Strategi Marketing,” J. Telekomun. dan Komput., vol. 8, no. 3, p. 163, 2018, doi: 10.22441/incomtech.v8i3.4174.
R. W. Sari, A. Wanto, and A. P. Windarto, “Implementasi Rapidminer Dengan Metode K-Means (Study Kasus: Imunisasi Campak Pada Balita Berdasarkan Provinsi),” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 2, no. 1, pp. 224–230, 2018, doi: 10.30865/komik.v2i1.930.
D. Yanto, L. Probolinggo, C. Loyal, and K. Loyal, “Analisis RFM dan Algoritma K-Means untuk Clustering Loyalitas Customer,” vol. 9, no. 1, pp. 0–8, 2019.
P. V. M., I. Gunawan, B. E. Damanik, I. Parlina, and W. Saputra, “Penerapan Data Mining Menggunakan Algoritma C4.5 Dalam Menentukan Kelayakan Penerimaan Bantuan Bedah Rumah Pada Desa Tiga Dolok,” vol. 1, pp. 396–409, 2021.
W. Muslehatin and M. Ibnu, “Penerapan Naïve Bayes Classification untuk Klasifikasi Tingkat Kemungkinan Obesitas Mahasiswa Sistem Informasi UIN Suska Riau,” pp. 18–19, 2017.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Penerapan Algoritma K-Means Dalam Pengelompokan Kepadatan Penduduk Menurut Kecamatan di Kabupaten Simalungun
Pages: 622-628
Copyright (c) 2022 Devi Gultom, Indra Gunawan, Ika Purnamasari, Sundari Retno Andani, Zulia Almaida Siregar

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).













