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Social and economic welfare reflects the quality of life in a region and is influenced by local social, economic, and environmental factors. East Java, as the second most populous province in Indonesia, faces challenges in improving the welfare of its residents, particularly due to varying regional characteristics such as employment, education, and population demographics. To understand the patterns of interrelationships among factors affecting welfare, this study conducted a klaster analysis to group regions based on similar characteristics. The klaster analysis employed both hierarchical (complete linkage) and non-hierarchical (K-means) approaches to determine the optimal number of klasters. The results revealed that the level of diversity across regions in East Java tends to be homogeneous in social and economic aspects, with average values exceeding standard deviations. Assumption tests for the klaster analysis confirmed that the data met the assumptions of multivariate normal distribution and dependency.Through hierarchical (complete linkage) and non-hierarchical (K-means) klaster analysis, two main klasters were formed, dividing districts/cities in East Java based on welfare characteristics. Using the complete linkage method, 27 regions were grouped into klaster 1, and 11 regions into klaster 2, while K-means grouped 26 regions into klaster 1 and 12 regions into klaster 2. Out of the six variables used, one variable was found to be insignificant in influencing the klastering results. Based on the mapping results, the grouping aligns with similar criteria, where urban areas predominantly fall into one klaster, and the other klaster is dominated by rural areas.

Poverty means the inability to fulfill the basic needs of family members, both food and non-food.  In this study, we will analyze several indicators that are assumed to be factors that influence poverty in East Java in 2023, including East Java in 2023, including the percentage of poor people, life expectancy, average years of schooling, and unemployment rate. life expectancy, average years of schooling, and open unemployment rate using cluster analysis to group kabupatens. cluster analysis to group districts/cities into clusters based on the factors that influence poverty. factors that influence poverty. The data used is secondary data obtained through the Central Bureau of Statistics (BPS) website as much as 38 data. Then the data obtained were analyzed for data characteristics, multivariate normal distribution assumption test, independent assumption test, and cluster analysis. assumption test, multivariate normal distribution, independent assumption test, cluster analysis hierarchical, and non-hierarchical cluster analysis, and selection of the best method to determine the optimum cluster. optimum cluster. So that the results obtained data characteristics tend not to be equal, fulfill the multivariate normal distribution assumption test, dependent data. At Hierarchical clustering results obtained the grouping of districts/cities in East Java based on the factors that influence poverty into 5 based on factors that influence poverty into 5 clusters, with 7 districts/municipalities in cluster 1, 16 districts/municipalities in cluster 2, 10 districts/municipalities in cluster 3, 4 districts/municipalities in cluster 4. districts/municipalities in cluster 3, 4 districts/municipalities in cluster 4, and 1 district/municipality in cluster 5. Based on these results, differences in characteristics between clusters indicates that there are significant variations in poverty factors in each region. The results of the non-hierarchical clustering resulted in the grouping of districts/municipalities in East Java based on the factors affecting poverty into 2 clusters, with 13 clusters. factors that influence poverty as many as 2 clusters, with 13 cluster 1, 25 districts/cities in cluster 2. Also, the results of the ANOVA test results obtained the results of all variables of the factors that influencing poverty in districts/municipalities in East Java Province significantly on poverty.