Regional Clustering in Sumatera Based on Walfare Indicators Using Fuzzy C-Means
DOI:
https://doi.org/10.30871/jaic.v9i5.10103Keywords:
Welfare, Sumatera Island, Clustering, Fuzzy C-Means, Partition Coefficient IndexAbstract
Welfare refers to a condition in which individuals have sufficient means to meet both physical and spiritual needs. In Indonesia, welfare is a national goal, yet Sumatra experiences the highest development disparity, contributing to unequal welfare distribution across regions. This study aims to cluster regions in Sumatra based on welfare indicators using the Fuzzy C-Means (FCM) method, analyze cluster characteristics, and provide policy recommendations for decision-makers. FCM is used because it accommodates uncertainty and allows each data point to belong to more than one cluster, making it suitable for welfare analysis. Cluster validity was tested using Partition Coefficient Index (PCI) and Silhouette Coefficient, both indicating that the optimal number of clusters is two. The results show that Cluster 1 consists of 62 regions with relatively higher welfare conditions, while Cluster 2 includes 92 regions with lower welfare characteristics. One notable member of Cluster 2 is Ogan Komering Ulu, with a high membership degree of 0.869. Recommended policies include improving access to clean water and healthcare, enhancing education, strengthening local economies, and delivering targeted social assistance to underdeveloped areas. For Cluster 1, sustainable development efforts should be maintained.
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