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All Journal Eksakta : Berkala Ilmiah Bidang MIPA Lattice Journal : Journal of Mathematics Education and Applied Limits: Journal of Mathematics and Its Applications
Maiyastri
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Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering

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Journal : Eksakta : Berkala Ilmiah Bidang MIPA

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Clustering Provinces in Indonesia Based on The Main Food Crop Production Using The Spatial Fuzzy C-Means Yozza, Hazmira; Aldi Mukhlis; Maiyastri
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 25 No. 04 (2024): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol25-iss04/385

Abstract

Agriculture plays a strategic role in achieving food security in Indonesia. However, the production of major food crops in Indonesia shows uneven distribution, which may affect efforts to achieve food self-sufficiency. This study aims to cluster 34 provinces in Indonesia based on the total production of seven major food crops (rice, corn, soybean, mung bean, peanut, cassava, and sweet potato) using the Spatial Fuzzy C-Means (sFCM) method. Cluster validation using Modified Partition Coefficient (MPC) and Partition Entropy (PE) shows that the clustering results have high membership clarity and low entropy, making them relevant for spatial data analysis. The findings highlight the unequal distribution of food crop production and provide policy recommendations, where the first cluster can be optimized as a national food production hub, while the second cluster requires interventions based on infrastructure, technology, and redistribution policies.  This research makes an important contribution in providing a data-driven scientific basis for food production equity planning. The sFCM method used demonstrates effective capabilities in analyzing data with spatial elements, supporting more inclusive policies for the improvement of national food security and the achievement of sustainable development goals in Indonesia. 
Co-Authors Acnesya, Vivin Aldi Mukhlis Cintya Mukti Devianto, Dodi Elfa Rafulta Hazmira Yozza Yanuar, Ferra