Application of Data Mining Clustering the Development of Covid-19 Using K-Medoids Method - Novia Gusmantoni (Journal of Computer Scine and Information Technology, 2022)
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.