Comparison of k-means clustering with hierarchical agglomerative clustering for the analysis of food security of rice sector in Indonesia
Main Article Content
Abstract
Indonesia's food security depends on the availability and distribution of rice as a staple food. To support data-driven policies, this study applies K-Means Clustering and Hierarchical Agglomerative Clustering (HAC) to cluster 38 provinces based on rice consumption and production patterns. Data is sourced from BPS with attributes: rice consumption per capita, rice production, rice price per kg, and population. These variables were chosen because they reflect the balance of demand, supply, affordability, and food needs. The optimal number of clusters was determined as three, based on Elbow Method and Silhouette Score for K-Means, and Dendrogram and Cophenetic Correlation Coefficient (CCC) for HAC. The clustering results identify regional characteristics related to food security and support the formulation of more targeted rice distribution policies. This study also compares the effectiveness of both methods in supporting equitable and sustainable food distribution strategies.
Downloads
Download data is not yet available.
Article Details
How to Cite
Sinaga, R. F., M Azhar Prabukusumo, & Manurung, J. (2025). Comparison of k-means clustering with hierarchical agglomerative clustering for the analysis of food security of rice sector in Indonesia. Journal of Intelligent Decision Support System (IDSS), 8(1), 22-33. https://doi.org/10.35335/idss.v8i1.290
References
Adriani, D., & Yustini, T. (2021). Anticipating the demographic bonus from the perspective of human capital in Indonesia. International Journal of Research in Business and Social Science (2147-4478), 10(6), 141–152.
Ahmad, A., & Khan, S. S. (2021). initKmix-A novel initial partition generation algorithm for clustering mixed data using k-means-based clustering. Expert Systems with Applications, 167, 114149. https://doi.org/https://doi.org/10.1016/j.eswa.2020.114149
Ay, M., Özbakır, L., Kulluk, S., Gülmez, B., Öztürk, G., & Özer, S. (2023). FC-Kmeans: Fixed-centered K-means algorithm. Expert Systems with Applications, 211, 118656.
BPS. (2024, June 28). Jumlah Penduduk Pertengahan Tahun (Ribu Jiwa), 2022-2024. BPS. https://www.bps.go.id/id/statistics-table/2/MTk3NSMy/jumlah-penduduk-pertengahan-tahun--ribu-jiwa-.html
BPS. (2025, February 3). Pada 2024, luas panen padi mencapai sekitar 10,05 juta hektare dengan produksi padi sebanyak 53,14 juta ton gabah kering giling (GKG). BPS. https://www.bps.go.id/id/pressrelease/2025/02/03/2414/pada-2024--luas-panen-padi-mencapai-sekitar-10-05-juta-hektare-dengan-produksi-padi-sebanyak-53-14-juta-ton-gabah-kering-giling--gkg--.html
Chhabra, A., & Mohapatra, P. (2022). Fair Algorithms for Hierarchical Agglomerative Clustering. 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 206–211. https://doi.org/10.1109/ICMLA55696.2022.00036
Dwi Ariyanti, S., Nabila, U., & Rahmawati, L. (2024). Pemenuhan Kebutuhan Produksi Beras Nasional Dalam Meningkatkan Kesejahteraan Masyarakat Menurut Perspektif Ekonomi Islam. Jurnal Ekonomi Syariah Dan Bisnis, 7(1). https://doi.org/10.31949/maro.v7i1.9121
Kasote, D., Sreenivasulu, N., Acuin, C., & Regina, A. (2022). Enhancing health benefits of milled rice: current status and future perspectives. Critical Reviews in Food Science and Nutrition, 62(29), 8099–8119.
Marzani, Y., & Juliannisa, I. A. (2024). ASSESSMENT KETERSEDIAAN BERAS PADA 34 PROVINSI DI INDONESIA Assessment Of Rice Availability In 34 Provinces In Indonesia. 8(2), 700–711. https://doi.org/10.21776/ub.jepa.2024.008.02.25
Mavroeidis, A., Roussis, I., & Kakabouki, I. (2022). The role of alternative crops in an upcoming global food crisis: A concise review. Foods, 11(22), 3584.
Mohidem, N. A., Hashim, N., Shamsudin, R., & Che Man, H. (2022). Rice for Food Security: Revisiting Its Production, Diversity, Rice Milling Process and Nutrient Content. Agriculture, 12(6), 741. https://doi.org/10.3390/agriculture12060741
Monath, N., Dubey, K. A., Guruganesh, G., Zaheer, M., Ahmed, A., McCallum, A., Mergen, G., Najork, M., Terzihan, M., & Tjanaka, B. (2021). Scalable hierarchical agglomerative clustering. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 1245–1255.
Oti, E. U., Olusola, M. O., Eze, F. C., & Enogwe, S. U. (2021). Comprehensive Review of K-Means Clustering Algorithms. International Journal of Advances in Scientific Research and Engineering, 07(08), 64–69. https://doi.org/10.31695/ijasre.2021.34050
Ratnasari, V., & Dani, A. T. R. (2023). Mapping the Provincial Food Security Conditions in Indonesia Using Cluster Ensemble-Based Mixed Data Clustering-Robust Clustering with Links (CEBMDC-ROCK). International Journal on Advanced Science, Engineering and Information Technology, 13(2), 611–617. https://doi.org/10.18517/ijaseit.13.2.16457
Rozaki, Z. (2021). Food security challenges and opportunities in Indonesia post COVID-19. Advances in Food Security and Sustainability, 6, 119–168.
Rusadi Akhmad, G. (2023). Proyeksi Kebutuhan dan Ketersediaan Beras di Provinsi DIY Tahun 2045. Jurnal Pendidikan Geografi Undiksha, 11(2), 94–104. https://doi.org/10.23887/jjpg.v11i2.66394
Saefudin. (2023). STRATEGI PERENCANAAN MENGHADAPI KRISIS PANGAN DAN EL NINO. WARTA BSIP PERKEBUNAN, 1(3).
Setiani, S. Y., Pratiwi, T., & Fitrianto, A. R. (2021). Tenaga Muda Pertanian dan Ketahanan Pangan di Indonesia. CAKRAWALA, 15(2), 95–108. https://doi.org/10.32781/cakrawala.v15i2.386
Sintiya, E. S. (2023). Analisis Ketersediaan Beras Menggunakan Sistem Dinamik Sebagai Pendukung Kebijakan Ketahanan Pangan Endah Septa Sintiya. TECNOSCIENZA, 7(2).
Tuslaela, T., Rusdiansyah, R., Supendar, H., & Suharyanti, N. (2024). Implementation of K-Means Clustering in Food Security by Regency in East Java Province in 2022. Sinkron, 9(1), 54–60. https://doi.org/10.33395/sinkron.v9i1.13169
United States Department of Agriculture. (2024). Grain and Feed Update.
Yu, H., & Hou, X. (2022). Hierarchical clustering in astronomy. Astronomy and Computing, 41, 100662.
Zubair, M., Iqbal, M. D. A., Shil, A., Chowdhury, M. J. M., Moni, M. A., & Sarker, I. H. (2024). An improved K-means clustering algorithm towards an efficient data-driven modeling. Annals of Data Science, 11(5), 1525–1544.
Ahmad, A., & Khan, S. S. (2021). initKmix-A novel initial partition generation algorithm for clustering mixed data using k-means-based clustering. Expert Systems with Applications, 167, 114149. https://doi.org/https://doi.org/10.1016/j.eswa.2020.114149
Ay, M., Özbakır, L., Kulluk, S., Gülmez, B., Öztürk, G., & Özer, S. (2023). FC-Kmeans: Fixed-centered K-means algorithm. Expert Systems with Applications, 211, 118656.
BPS. (2024, June 28). Jumlah Penduduk Pertengahan Tahun (Ribu Jiwa), 2022-2024. BPS. https://www.bps.go.id/id/statistics-table/2/MTk3NSMy/jumlah-penduduk-pertengahan-tahun--ribu-jiwa-.html
BPS. (2025, February 3). Pada 2024, luas panen padi mencapai sekitar 10,05 juta hektare dengan produksi padi sebanyak 53,14 juta ton gabah kering giling (GKG). BPS. https://www.bps.go.id/id/pressrelease/2025/02/03/2414/pada-2024--luas-panen-padi-mencapai-sekitar-10-05-juta-hektare-dengan-produksi-padi-sebanyak-53-14-juta-ton-gabah-kering-giling--gkg--.html
Chhabra, A., & Mohapatra, P. (2022). Fair Algorithms for Hierarchical Agglomerative Clustering. 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 206–211. https://doi.org/10.1109/ICMLA55696.2022.00036
Dwi Ariyanti, S., Nabila, U., & Rahmawati, L. (2024). Pemenuhan Kebutuhan Produksi Beras Nasional Dalam Meningkatkan Kesejahteraan Masyarakat Menurut Perspektif Ekonomi Islam. Jurnal Ekonomi Syariah Dan Bisnis, 7(1). https://doi.org/10.31949/maro.v7i1.9121
Kasote, D., Sreenivasulu, N., Acuin, C., & Regina, A. (2022). Enhancing health benefits of milled rice: current status and future perspectives. Critical Reviews in Food Science and Nutrition, 62(29), 8099–8119.
Marzani, Y., & Juliannisa, I. A. (2024). ASSESSMENT KETERSEDIAAN BERAS PADA 34 PROVINSI DI INDONESIA Assessment Of Rice Availability In 34 Provinces In Indonesia. 8(2), 700–711. https://doi.org/10.21776/ub.jepa.2024.008.02.25
Mavroeidis, A., Roussis, I., & Kakabouki, I. (2022). The role of alternative crops in an upcoming global food crisis: A concise review. Foods, 11(22), 3584.
Mohidem, N. A., Hashim, N., Shamsudin, R., & Che Man, H. (2022). Rice for Food Security: Revisiting Its Production, Diversity, Rice Milling Process and Nutrient Content. Agriculture, 12(6), 741. https://doi.org/10.3390/agriculture12060741
Monath, N., Dubey, K. A., Guruganesh, G., Zaheer, M., Ahmed, A., McCallum, A., Mergen, G., Najork, M., Terzihan, M., & Tjanaka, B. (2021). Scalable hierarchical agglomerative clustering. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 1245–1255.
Oti, E. U., Olusola, M. O., Eze, F. C., & Enogwe, S. U. (2021). Comprehensive Review of K-Means Clustering Algorithms. International Journal of Advances in Scientific Research and Engineering, 07(08), 64–69. https://doi.org/10.31695/ijasre.2021.34050
Ratnasari, V., & Dani, A. T. R. (2023). Mapping the Provincial Food Security Conditions in Indonesia Using Cluster Ensemble-Based Mixed Data Clustering-Robust Clustering with Links (CEBMDC-ROCK). International Journal on Advanced Science, Engineering and Information Technology, 13(2), 611–617. https://doi.org/10.18517/ijaseit.13.2.16457
Rozaki, Z. (2021). Food security challenges and opportunities in Indonesia post COVID-19. Advances in Food Security and Sustainability, 6, 119–168.
Rusadi Akhmad, G. (2023). Proyeksi Kebutuhan dan Ketersediaan Beras di Provinsi DIY Tahun 2045. Jurnal Pendidikan Geografi Undiksha, 11(2), 94–104. https://doi.org/10.23887/jjpg.v11i2.66394
Saefudin. (2023). STRATEGI PERENCANAAN MENGHADAPI KRISIS PANGAN DAN EL NINO. WARTA BSIP PERKEBUNAN, 1(3).
Setiani, S. Y., Pratiwi, T., & Fitrianto, A. R. (2021). Tenaga Muda Pertanian dan Ketahanan Pangan di Indonesia. CAKRAWALA, 15(2), 95–108. https://doi.org/10.32781/cakrawala.v15i2.386
Sintiya, E. S. (2023). Analisis Ketersediaan Beras Menggunakan Sistem Dinamik Sebagai Pendukung Kebijakan Ketahanan Pangan Endah Septa Sintiya. TECNOSCIENZA, 7(2).
Tuslaela, T., Rusdiansyah, R., Supendar, H., & Suharyanti, N. (2024). Implementation of K-Means Clustering in Food Security by Regency in East Java Province in 2022. Sinkron, 9(1), 54–60. https://doi.org/10.33395/sinkron.v9i1.13169
United States Department of Agriculture. (2024). Grain and Feed Update.
Yu, H., & Hou, X. (2022). Hierarchical clustering in astronomy. Astronomy and Computing, 41, 100662.
Zubair, M., Iqbal, M. D. A., Shil, A., Chowdhury, M. J. M., Moni, M. A., & Sarker, I. H. (2024). An improved K-means clustering algorithm towards an efficient data-driven modeling. Annals of Data Science, 11(5), 1525–1544.
Copyright and Licensing
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.