PENGELOMPOKAN WILAYAH INDONESIA BERDASARKAN KOMPONEN INDEKS PEMBANGUNAN MANUSIA DENGAN PENDEKATAN ALGORITMA K-MEANS CLUSTERING
DOI:
https://doi.org/10.36080/skanika.v8i1.3318Keywords:
clustering, indeks pembangunan manusia, IPM, K-MeansAbstract
The Human Development Index (HDI) plays a crucial role in measuring the well-being of a region's population, offering a comprehensive perspective through various indicators, including economic factors such as Gross Domestic Product (GDP). This study focuses on clustering regions in Indonesia based on HDI components using the K-Means Clustering method. The clustering divides the regions into three groups: low, medium, and high clusters, considering dimensions of education, health, and standard of living. The data used includes indicators such as expected years of schooling, mean years of schooling, life expectancy, average monthly income, and per capita expenditure. The Davies-Bouldin Index (DBI) is employed as an evaluation method to measure the quality of cluster separation. The study reveals that K-Means successfully categorizes the regions into three clusters with a DBI value of 1.17, reflecting good cluster separation. This clustering provides valuable insights into the distribution of human development across Indonesia and is expected to assist policymakers in devising effective strategies to improve well-being in each identified cluster.
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References
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[2] N. Alvariqati, V. Ansori, A. Muhaimin, A. Terza, P. Studi, and S. Data, “Pembentukan Klaster terhadap Indeks Pembangunan Manusia di Wilayah Jawa Timur,” J. Ilm. Pendidik. Mat. Mat. dan Stat., vol. 5, no. 1, pp. 514–519, 2024.
[3] A. Hakiki, Yulmardi, and Zulfanetti, “Estimasi Model Indeks Pembangunan Manusia di Kabupaten/Kota Provinsi Jambi,” Aug. 2020. [Online]. Available: www.journal.uta45jakarta.ac.id
[4] B. Rozak, D. Febriawan, and F. N. Hasan, “Implementasi Business Intelligence untuk Visualisasi Laju Indeks Pembangunan Manusia Kota Cirebon Menggunakan Google Collab,” Sainteks, vol. 21, no. 1, pp. 33-45, 2024.
[5] Rahmati1 R and Wijayanto A, “Analisis Cluster Dengan Algoritma K-Means, Fuzzy C-Means Dan Hierarchical Clustering (Studi Kasus Indeks Pembangunan Manusia tahun 2019),” JIKO (Jurnal Inform. dan Komputer), vol. 5, no. 2, pp. 73-80, 2021.
[6] A. M. Sikana and A. W. Wijayanto, “Comparison Analysis of Human Development Index Grouping in Indonesia in 2019 using Partitioning and Hierarchical Clustering Methods,” J. Ilmu Komput. , vol. 14, no. 2, pp. 66–78, 2021.
[7] B. T. Kristanti, A. Junaidi, and E. P. Mandyartha, “Implementasi K-Means Clustering Dalam Segmentasi Pelanggan Berdasarkan Usia, Pendapatan, Dan Model RFM (Studi Kasus: Lantikya Store Jombang),” J. Inform. dan Tek. Elektro Terap., vol. 12, no. 3, pp. 2099-2112, 2024.
[8] E. Widodo, S. N. Mashita, and Y. G. Prasetyowati, “Perbandingan Metode Average Linkage, Complete Linkage, dan Ward’S pada Pengelompokan Kabupaten/Kota di Provinsi Jawa Tengah Berdasarkan Indikator Indeks Pembangunan Manusia,” Fakt. Exacta, vol. 13, no. 2, pp. 81-87, 2020.
[9] A. Nugraha, O. Nurdiawan, and G. Dwilestari, “Penerapan Data Mining Metode K-Means Clustering Untuk Analisa Penjualan Pada Toko Yana Sport,” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 6, no. 2, pp. 849-855, 2022.
[10] A. Maulidin, et al., “Implementasi K-Means untuk Clustering Kepuasan Mahasiswa Teknik Informatika Terhadap Layanan Akademik,”, Jurnal Genta Mulia, vol. 15, no. 2, pp. 124-133, 2024.
[11] J. Hutagalung, and F. Sonata, “Penerapan Metode K-Means Untuk Menganalisis Minat Nasabah,” Jurnal Media Informatika Budidarma, vol. 5, no. 3, pp. 1187-1194, 2021.
[12] R. S. Wicaksana, D. Heksaputra, T. A. Syah, and F. F. Nur’aini, “Pendekatan K-Means Clustering Metode Elbow Pada Analisis Motivasi Pengunjung Festival Halal JHF#2,” J. Ilmu Ekonomi Islam, vol. 9, no. 3, pp. 4162-4176, 2023.
[13] L. S. Riza, R. A. Rosdiyana, A. Wahyudin, and A. R. Pérez, “The k-means algorithm for generating sets of items in educational assessment,” Indonesian Jurnal Science Technology, vol. 6, no. 1, pp. 93–100, 2021.
[14] N. Tri, S. Saptadi, P. Chyan, and V. P. Taga, “Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City,” International Journal on Advanced Science Engineering and Information Technology, vol. 11, no. 4, pp. 1455-1462, 2021.
[15] F. D. Rahman, M. I. Zulfa, and A. Taryana, “Clustering Dan Klasifikasi Data Cuaca Cilacap Dengan Menggunakan Metode K-Means Dan Random Forest,” Jurnal SINTA Sistem Informasi dan Teknologi Komputasi, vol. 1, no. 2, pp. 90-97, 2024.
[16] T. Terttiaavini, “A Hybrid Approach Using K-Means Clustering and the SAW Method for Evaluating and Determining the Priority of SMEs in Palembang City,” Journal of Intelligent System and Computation, vol. 6, no. 1, pp. 46–53, 2024.
[17] M. I. Zuhendra, R. Hidayat, and H. Hendrawaty, “Penerapan Data Mining Untuk Klasterisasi Tingkat Kemiskinan Berdasarkan Data Terpadu Kesejahteraan Sosial (Dtks),” SKANIKA: Sistem Komputer dan Teknik Informatika, vol. 7, no. 1, pp. 32–41, 2024.
[18] R. Anggara, S. Defit, and B. Hendrik, “Implementasi K-Means Clustering Dalam Analisa Soal Ujian CBT Universitas Baiturrahmah,” KESATRIA: Jurnal Penerapan Sistem Informasi (Komputer & Manajemen), vol. 5, no. 2, pp. 577–586, 2024.
[19] S. Suraya, M. Sholeh, and D. Andayati, “Penerapan Metode Clustering Dengan Algoritma K-Means Pada Pengelompokan Indeks Prestasi Akademik Mahasiswa,” SKANIKA: Sistem Komputer dan Teknik Inforfmatika, vol. 6, no. 1, pp. 51–60, 2023.
[20] Y. Imam T. Umagapi, Basirung Umaternate, Hazriani, “Uji Kinerja K-Means Clustering Menggunakan Davies-Bouldin Index Pada Pengelompokan Data Prestasi Siswa,” Prosiding Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK), vol. 7, no. 1, pp. 303–308, 2023.
[21] F. Fathurrahman, S. Harini, and R. Kusumawati, “Evaluasi Clustering K-Means Dan K-Medoid Pada Persebaran Covid-19 Di Indonesia Dengan Metode Davies-Bouldin Index (Dbi),” Jurnal Mnemon., vol. 6, no. 2, pp. 117–128, 2023.
[22] S. Ramadhani, D. Azzahra, and T. Z, “Comparison of K-Means and K-Medoids Algorithms in Text Mining based on Davies Bouldin Index Testing for Classification of Student’s Thesis,” Digital Zone Jurnal Teknologi Infomasi dan Komunikasi, vol. 13, no. 1, pp. 24–33, 2022.
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Published
2025-01-30
How to Cite
[1]
N. R. Saputra and G. Z. Muflih, “PENGELOMPOKAN WILAYAH INDONESIA BERDASARKAN KOMPONEN INDEKS PEMBANGUNAN MANUSIA DENGAN PENDEKATAN ALGORITMA K-MEANS CLUSTERING”, SKANIKA, vol. 8, no. 1, pp. 156–167, Jan. 2025.
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