Open AccessVILLAGE GROUPING BASED ON THE NUMBER OF HEALTH FACILITIES IN WEST JAVA USING K-MEANS CLUSTERING ALGORITHM
Author(s) -
Frieyadie Frieyadie,
Anggie Andriansyah,
Tyas Setiyorini
Publication year - 2021
Publication title -
jurnal riset informatika
Language(s) - English
Resource type - Journals
eISSN - 2656-1743
pISSN - 2656-1735
DOI - 10.34288/jri.v4i1.300
Subject(s) - sanitation , indonesian , cluster analysis , federal capital territory , java , business , government (linguistics) , welfare , cluster (spacecraft) , environmental health , computer science , socioeconomics , medicine , engineering , economics , artificial intelligence , environmental engineering , market economy , philosophy , linguistics , programming language
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.