Application of Data Mining Using the K-Medoids Algorithm for Poverty Index Clustering

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Muhammad Faisal Wiranti Sri Utami

Abstract

Poverty index is a term for measuring poverty, this is done by a government agency or commonly referred to as the Central Statistics Agency (BPS). The poverty index or poverty rate is the percentage of the population in a province who is below the poverty line, which is the minimum in obtaining an adequate standard of living. In the government's efforts to reduce the level of poverty in a province, the government often provides special assistance programs for people belonging to the poverty line. Based on the explanations that have been discussed, a conclusion can be drawn. This research can be done using the Data Mining technique to group the total Poverty Index by Province in Indonesia using the K-Medoids Algorithm, then by determining the Clusters randomly. The results of this study are expected to assist the government in providing assistance to the affected population below the poverty line.

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How to Cite
[1]
M. Faisal and W. Utami, “Application of Data Mining Using the K-Medoids Algorithm for Poverty Index Clustering”, CCIT (Creative Communication and Innovative Technology) Journal, vol. 15, no. 2, pp. 272-281, Aug. 2022.
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