VILLAGE GROUPING BASED ON THE NUMBER OF HEALTH FACILITIES IN WEST JAVA USING K-MEANS CLUSTERING ALGORITHM

Frieyadie Frieyadie; Anggie Andriansyah; Tyas Setiyorini

doi:10.34288/jri.v4i1.140

Authors

Frieyadie Frieyadie Universitas Nusa Mandiri
Anggie Andriansyah Universitas Nusa Mandiri
Tyas Setiyorini Universitas Nusa Mandiri

(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v4i1.140

Keywords:

Health Facilitie, Covid-19, Clustering, K-Means Algorithm

Abstract

Health is very important for the welfare and development of the Indonesian nation because as a capital for the implementation of national development, it is essentially the development of all Indonesian people and the development of all Indonesian people. Due to the outbreak of the Covid-19 virus, many health facilities must be provided for patients. Of course, the government must pay attention to the health facilities that can be used in every district/city in West Java in the future. Therefore, to determine the level of availability of sanitation facilities in each district/city in West Java, we need a technology that can classify data correctly. One method of data processing in data mining is clustering. The application of clustering to this problem can use the K-Means algorithm method to group the most frequently used data. The purpose of this study is to classify sanitation data on the highest sanitation facilities, medium sanitation facilities, and low sanitation facilities, so that areas/cities that are included in the low cluster will receive more attention from the government to improve/provide sanitation facilities.

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