Application of Data Mining Using the KMedoids Algorithm for Poverty Index Clustering
DOI:
https://doi.org/10.33050/ccit.v15i2.2311Keywords:
Data Mining, K-Medoids, Proverty IndexAbstract
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.