CLUSTERING ANALYSIS OF MULTIDIMENSIONAL POVERTY IN CENTRAL JAVA PROVINCE, INDONESIA

Abstract

In Indonesia, poverty continues to be a major issue. According to Statistics Indonesia, there were 9.78% of the population living in poverty in 2020, with Java Island accounting for 50% of the nation’s total poor people. Furthermore, poverty reduction is the primary concern due to Central Java’s high poverty rate, which is still higher than the national average, so it has become a shared challenge. This study measured poverty by clusters based on a variety of deprivations that residents of 35 regencies or municipalities in Central Java Province experienced. Additionally, 16 poverty indicators based on the criteria and income of the poor and underprivileged from the Ministry of Social Affairs comprised the variables used in this study. Moreover, by selecting the optimal cluster, characteristic poverty was obtained employing fuzzy C-means (FCM) as cluster analysis. In addition, each municipality/regency that shares a similarity indicator with another municipality/regency was categorized into one cluster. The clusters were fundamental to understanding the determinants of poverty and poverty alleviation programs. According to the clustering results, there were four clusters considered the best cluster, and it demonstrated that the indicators most associated with poverty were non-food expenditure, drinking water adequacy, access to sanitation facilities, the open unemployment rate, and television ownership.