Clustering of districts and cities in Indonesia based on poverty indicators using the K-means method / Khoirun Niswatin ... [et al.] - Niswatin, Khoirun; Andreas, Christopher; Oktavia Hans, Putri Fardha Asa; Mardianto, M. Fariz Fadilah (2021)
Poverty is a multidimensional problem caused by various aspects and has an impact on many aspects of life. As one of the objectives of the Sustainable Development Goals (SDG's), poverty eradication aims to improve welfare in all forms everywhere. Therefore, regional clustering is carried out based on poverty indicators as one of the alternatives to solve poverty problems in Indonesia. In this research, the mapping will be carried out based on districts and cities, so that the core problems in each region can be identified. By using the K-Means clustering method, eight clusters of districts and cities with different poverty levels were obtained. Each cluster member from the very not poor to very poor level is 130, 76, 126, 98, 66, 5, 5, and 8 districts and cities. Thus, most districts and cities in Indonesia are categorized as prosperous, only some region need special attention and treatment from the government.