Analisis K-Medoids Dalam Pengelompokkan Penduduk Buta Huruf Menurut Provinsi

Sri Rahayu Ningsih, Irfan Sudahri Damanik, Agus Perdana Windarto, Heru Satria Tambunan, Jalaluddin Jalaluddin, Anjar Wanto

Abstract


Illiteracy is the state of being unable to read and to write for communication. A large number of people still experiencing illiteracy in a country is one indicator showing that the country is still not developed. As many as 3.4 million people or around 2.07% of the population in Indonesia are still illiterate. This study aims to create a grouping model using the k-medoids algorithm. The k-medoids method is a clustering method that serves to break down datasets into groups. The data used is sourced from the Central Statistics Agency. Entered data are percentage of illiterate population in 2009-2017. The number of records used is 34 provinces which are divided into 3 clusters namely high cluser, medium cluster and low cluster. From the results of k-medoids calculation, one (1) province was categorited as a high cluster, twelve (12) provinces as a medium cluster and twenty-one (21) provinces as a low cluster. The implementation process using the RapidMiner 5.3 application is used to help find accurate values. It is hoped that this research can be used as one of the bases for decision making for the government in an effort to equalize the level of illiteracy according to the province which has an impact on reducing of illiteracy rates in Indonesia.

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DOI: http://dx.doi.org/10.30645/senaris.v1i0.78

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