HIERARCHICAL CLUSTER ANALYSIS ON PEOPLE'S WELFARE IN SOUTHEAST SULAWESI PROVINCE - Musa, Marsuddin; Fallo, Sefri Imanuel (BAREKENG: Jurnal Ilmu Matematika dan Terapan, 2023)
Problems with people's welfare typically result from the government's development efforts in a region not being done properly or not being done equally. Consider grouping and defining the traits of each region's degree of welfare as a potential answer to ensure that development policies and strategies are well-targeted. This study aims to classify 17 regency/cities in Southeast Sulawesi province based on several indicators of people's welfare. The method used is hierarchical cluster analysis with several approaches, including Single Linkage, Complete Linkage, Average Linkage, and Ward's. The data used in this study is secondary data obtained from the publication of the Central Agency of Statistics (CAS) of Southeast Sulawesi Province. Based on the results of the evaluation the best method used is Ward's method which produces three clusters. The first cluster consists of 9 regencies, namely Buton, North Buton, South Buton, Central Buton, Muna, West Muna, Wakatobi, Konawe Islands, and East Kolaka, the majority of which come from the archipelago. Some of the problems that occur in these areas are the relatively high poverty rate and the low average length of schooling and life expectancy. The same thing happened to the second cluster which consisted of 6 regencies, namely Konawe, South Konawe, North Konawe, Bombana, Kolaka, and North Kolaka with problems of poverty, the average length of schooling, and relatively low sources of proper drinking water when compared to other clusters. The third cluster consists of 2 urban areas, namely Kendari City and Baubau City, the problems that occur are the relatively high unemployment rate and population density. The government ought to offer more initiatives to handle issues with poverty, education, and health in regions in clusters 1 and 2. While in cluster 3, the government ought to offer more initiatives to combat jobless issues and prepare for rising population densities.