Open AccessApplication of Data Mining Clustering the Development of Covid-19 Using K-Medoids Method
Author(s) -
Novia Gusmantoni
Publication year - 2022
Publication title -
upi yptk journal of computer scine and information technology
Language(s) - English
Resource type - Journals
ISSN - 2502-1486
DOI - 10.35134/jcsitech.v8i1.29
Subject(s) - cluster analysis , covid-19 , data set , computer science , cluster (spacecraft) , data mining , set (abstract data type) , social distance , geography , artificial intelligence , medicine , disease , pathology , infectious disease (medical specialty) , programming language
At the beginning of March, Indonesia was hit by the entry of the corona virus (covid) outbreak. Every day the cases of the spread of covid-19 in Indonesia continue to increase. The public is asked to carry out social distancing in order to break the chain of the spread of Covid-19 which is spread in various regions in Indonesia. Therefore, the data that has been accommodated is certainly a lot, from the data it can be seen that the patterns of determining the grouping of the spread of Covid-19 are based on test scores. Public. K-Medoids is a partitional clustering analytical method that aims to get a set of k-clusters among the data that is closest to an object in grouping a data. The results of the study of grouping the spread of the new covid-19 show that people come from various regions in Indonesia. Characteristics with a body temperature above 36.9 C and accompanied by fever and continuous cough show one of the symptoms of Covid-19.