K-Means Clustering for Grouping Indonesia Underdeveloped Regions in 2020 Based on Poverty Indicators

  • Resti Wahyuni Badan Pusat Statistik Provinsi Sulawesi Tengah
Keywords: Poverty, Grouping, Underdeveloped Areas, K-Means

Abstract

Poverty is still a problem in Indonesia, especially in underdeveloped areas. Underdeveloped areas are areas where the region and its people are less developed than other regions on a national scale. The classification of disadvantaged areas is determined by the president in the Presidential Regulation of the Republic of Indonesia Number 63 of 2020 concerning the Determination of Underdeveloped Regions of 2020-2024. Various policies need to be set by the government to overcome poverty in underdeveloped areas. Program planning strategies may be different for each region. Therefore, in order to achieve an optimal implementation of poverty alleviation programs, it is necessary to group the districts covered in underdeveloped areas in Indonesia based on poverty indicators. The data used is macro data from the characteristics of each region in disadvantaged areas obtained from regional publications in the figures for each district. From the results of the analysis of k means clustering formed three groups with different characteristics in each cluster. In cluster one, the focus of government policies is on employment and sanitation aspects, cluster two is on health, education, and employment aspects, cluster three is on all aspects because cluster three is the area with the highest percentage of poor people compared to the other two clusters. The high percentage of poor people is also followed by other poor aspects.

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Published
2021-12-31
How to Cite
Resti Wahyuni. (2021). K-Means Clustering for Grouping Indonesia Underdeveloped Regions in 2020 Based on Poverty Indicators. Parameter: Journal of Statistics, 2(1), 8-15. https://doi.org/10.22487/27765660.2021.v2.i1.15675
Section
Articles