Open AccessPengelompokkan Sumber Air Minum Dari Air Sungai Menggunakan Metode K-Means
Author(s) -
Sabrina Biutiqwin Sinaga,
S solikhun,
Dedi Suhendro
Publication year - 2021
Publication title -
jurasik : jurnal riset sistem informasi dan teknik informatika/jurasik (jurnal riset sistem informasi dan teknik informatika)
Language(s) - English
Resource type - Journals
eISSN - 2549-7839
pISSN - 2527-5771
DOI - 10.30645/jurasik.v6i1.289
Subject(s) - environmental science , cluster (spacecraft) , geography , population , river pollution , water source , hydrology (agriculture) , water resource management , pollution , ecology , engineering , environmental health , medicine , geotechnical engineering , computer science , biology , programming language
River water is one of the most frequently used water by the community and has a multipurpose function for life, one of which is a source of drinking water. However, now we know that the population of river water pollution is very high and it is used as a waste disposal site which causes a lot of river water to be polluted, it can make people susceptible to disease because they consume unhealthy river water. Judging from the data obtained by province, many use river water as a source of drinking water, for this reason the authors conducted a study that aims to classify drinking water sources from river water by province using the K-means Clustering algorithm and will test it with the Rapidminer application, so that Data from 34 provinces will be divided into 3 clusters in which cluster 1 (C1) is a high group, cluster 2 (C2) is a medium group, and cluster 3 (C3) is a low group. The results obtained from this study are C1 with a total of 2 provinces, C2 with a total of 9 provinces, C3 with a total of 23 provinces and the value of the results carried out with the Rapidminer application has the same value. With this research, it is hoped that this can provide information for the government about the data on the grouping of drinking water sources and used as a consideration for overcoming polluted rivers.