Klasterisasi provinsi di Indonesia berbasis perkembangan kasus Covid-19 menggunakan metode K-Medoids

Abstract

COVID-19 is a disease caused by a new type of corona virus Sars-CoV-2 which is affecting almost all countries in the world. The country of Indonesia is one of the states of Southeast Asia which has a high spike in positive confirmed cases. With the growth in the number of positive confirmed patients, patients died, and patients recovered in Indonesia; then clustering is done using K-Medoids to see the development of the COVID-19 case in Indonesia. K-Medoids is a classic partitioning technique from clustering that classifies object n datasets into k clusters. By clustering using the K-Medoids method; then obtained provinces that have confirmed positive corona in Indonesia are divided into 3 groups. Members from group 1 which are in the high category are 2 provinces; members from group 2 in the medium category are 6 provinces; while for members of group 3 with a low category of 26 provinces.