Analisis K-Means Clustering untuk Pengelompokan Produksi Padi di Provinsi Aceh Tahun 2025
Abstract
Indonesia is an agricultural country that makes rice (Oryza sativa L.) as a major food commodity. Aceh Province is one of the rice-producing regions in Indonesia with varying levels of production in each district/city. This study focuses on the grouping of rice-producing districts/cities in Aceh Province using the K-means clustering method by utilizing two variables, namely the harvested area of rice plants and rice production using 3 clusters for 23 districts in Aceh. The results show that there are 8 districts in cluster 1, 11 districts in cluster 2, and 4 districts in cluster 3. Cluster 3, which consists of 4 districts, is a group of districts with the highest harvested area and rice production compared to other districts/cities in Aceh province.
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Abdurrozzaq Hasibuan, Suhela Putri Nasution, Fitri Amja Yani, Henni Adlini Hasibuan, & Nyak Firzah. (2022). Strategi Peningkatan Usaha Tani Padi Sawah Untuk Meningkatkan Perekonomian Masyarakat Desa. ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains Dan Teknologi, 1(4), 477–490. https://doi.org/10.55123/abdikan.v1i4.1095
Aisyah, A., Putri, A., Sabrina, N. I., & Meila, O. (2025). K-Means Klastering Tanaman Biofarma Zingiber officinale Indonesia Tahun 2023 (Vol. 4, Number 1).
Ariansah, B., Khaira, U., & Abidin, Z. (2025). Penerapan K-Means Clustering untuk Pengelompokan Data Industri Kecil Menengah di Provinsi Jambi. Jurnal Teknologi Sistem Informasi, 6(2), 359–371. https://doi.org/10.35957/jtsi.v6i2.13553
Arini, E. R. (2023). Penerapan K-Means Cluster di Provinsi Jawa Timur Berdasarkan Ketahanan Pangan Implementation of K-Means Cluster In EastJava Based on Food Security. In JSNu : Journal of Science Nusantara (Vol. 3, Number 1).
Badan Pusat Statistik. (2026, February 2). Luas panen padi pada tahun 2025 mencapai sekitar 11,32 juta hektare dengan produksi padi sebanyak 60,21 juta ton gabah kering giling (GKG). https://www.bps.go.id/id/pressrelease/2026/02/02/2545/luas-panen-padi-pada-tahun-2025-mencapai-sekitar-11-32-juta-hektare-dengan-produksi-padi-sebanyak-60-21-juta-ton-gabah-kering-giling--gkg-.html
BPS Aceh. (2025, February 25). Luas panen, produktivitas, dan produksi padi menurut kabupaten/kota di Provinsi Aceh, 2025. Badan Pusat Statistik Provinsi Aceh. https://aceh.bps.go.id/id/statistics-table/3/WmpaNk1YbGFjR0pOUjBKYWFIQlBSU3MwVHpOVWR6MDkjMyMxMTAw/luas-panen-produktivitas-dan-produksi-padi-menurut-kabupaten-kota-di-provinsi-aceh.html
Dionesius Budiman, N., Santu, L., Pertanian, F., & Peternakan, D. (2024). KAJIAN STRATEGI DAN KEBIJAKAN PEMERINTAH INDONESIA DALAM MENCAPAI TARGET SWASEMBADA BERAS. JURNAL PERTANIAN CEMARA, 21.
Farismana, R. (2024). PENERAPAN K-MEANS CLUSTERING UNTUK PEMETAAN PRODUKTIVITAS PADI DAN PREDIKSI PANEN DI KABUPATEN INDRAMAYU. Journal of Information System, Applied, Management, Accounting and Research, 8(3), 589. https://doi.org/10.52362/jisamar.v8i3.1572
Marisa, F., Zahma, A., Muit Bau, A., Noviansa, E., Neno, A. S., Lidya Maukar, A., Informatika, T., Malang, W., Borobudur, J., & 35, N. (2021). Digitasi Produktivitas Panen Padi Berbasis K-Means Clustering. SMARTICS Journal, 7(1). https://doi.org/10.21067/smartics.v7i1.5270
Maulidina, R., & Riska, S. Y. (2023). Application of the K-Means Algorithm for Clustering Plantation Crop Production in Indonesia. SMATIKA JURNAL, 13(02), 339–349. https://doi.org/10.32664/smatika.v13i02.991
Paipan, S., & Abrar, M. (2020). ANALISIS KONDISI KETERGANTUNGAN IMPOR BERAS DI INDONESIA (Vol. 6, Number 2).
Septianto, M. A., Faqih, A., & Rinaldi, A. R. (2025). KLASTERISASI DATA PRODUKSI PERTANIAN DI KABUPATEN CIREBON DENGAN ALGORITMA K-MEANS. Jurnal Informatika Dan Teknik Elektro Terapan, 13(2). https://doi.org/10.23960/jitet.v13i2.6174
Simangunsong, A. A., Gunawan, I., Nasution, Z. M., & Artikel, G. (2022). Pengelompokkan Hasil Produksi Tanaman Perkebunan Berdasarkan Provinsi Menggunakan Metode K-Means Clustering Production of Plantation Crops by Province Using the K-Means Method Article Info ABSTRAK. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 1(4), 2828–9099. https://doi.org/10.55123/jomlai.v1i4.1661
Sinaga, K. P., & Yang, M. S. (2020). Unsupervised K-means clustering algorithm. IEEE Access, 8, 80716–80727. https://doi.org/10.1109/ACCESS.2020.2988796
Wahyudi, G. R., Rahmaddeni, R., Dini, E., Adrianto, S., & Fadila, R. (2025). Pengelompokan Kabupaten di Indonesia untuk Pemetaan Pendapatan Daerah Menggunakan Algoritma K-Means. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 5(3), 1143–1151. https://doi.org/10.57152/malcom.v5i3.2206
Yunitasari, D. (2025). JURNAL MANAJEMEN EKONOMI DAN BISNIS. 1(2), 30–42.
DOI: https://doi.org/10.35308/invasi.v4i2.15650
DOI (PDF): https://doi.org/10.35308/invasi.v4i2.15650.g6462
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