Pengelompokkan Faktor yang Memengaruhi Kemiskinan di Jawa Timur Tahun 2023 Menggunakan Analisis Cluster - Abghaza Bayu Kusuma Wardhana; Rakha Maheswara; Sri Pingit Wulandari (Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa, 2024)
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.