Open AccessImplementation of the K-Medoids Algorithm for Data Clustering of Covid 19 Cases in West Java
Author(s) -
Ririn Restu Aria
Publication year - 2021
Publication title -
ijistech (international journal of information system and technology)
Language(s) - English
Resource type - Journals
ISSN - 2580-7250
DOI - 10.30645/ijistech.v5i1.109
Subject(s) - java , medoid , cluster analysis , cluster (spacecraft) , geography , covid-19 , k medoids , algorithm , computer science , artificial intelligence , medicine , operating system , disease , pathology , infectious disease (medical specialty) , cure data clustering algorithm , correlation clustering
The Covid 19 pandemic has hit Indonesia for almost 15 months since March 2020. The virus has spread to all provinces in Indonesia. Various efforts were made to be able to reduce or prevent the spread of the coronavirus, including the implementation of the PSBB in various areas including in West Java province. In this study, the objective of this research is to cluster the data on cases of Covid 19 in West Java which are recapitulated daily based on districts/cities that occurred on May 20, 2021. For the clustering process, the K-medoids algorithm is used which determines 3 clusters based on the variables used, namely discarded close contact, suspects discarded, probable completed, probable died, totally positive, positive recovered, and positive died. For data processing, a calculation analysis was carried out using the stages in the K-medoids algorithm and the Rapidminer application with high cluster mapping of 6 districts/cities, medium clusters there were 19 districts/cities, while low clusters had 2 districts/cities. The results of the analysis are expected to provide information about the distribution and mapping of clusters in West Java province.