IMPLEMENTATION K-MEDOIDS ALGORITHM FOR DISTRIBUTION MAPPING OF COVID-19 IN SURABAYA

Abstract

Surabaya was recorded as the city with the highest active Covid-19 in East Java with 225 cases based on data released by the East Java Province on March 1, 2021. One step to minimizing the increase of cases is by grouping regions based on the number of existing cases. The previous mapping only displayed data on the status of confirmed patients in each region which was updated daily. So in this research, a mapping of urban villages in Surabaya was carried out which would be included in the cluster based on confirmed cases in treatment, confirmation of recovery, and confirmation of death using thealgorithm K-Medoids. K-Medoids is a clustering algorithm (unsupervised learning) in machine learning, the development of K-Means which is sensitive to outliers. K-Medoids has better clustering performance for large datasets. The results of the analysis showed that the urban villages with the highest number of deaths were Karah and Kutisari with 3 cases. The results of clustering using K-Medoids with an evaluation value of the Davies-Bouldin Index (DBI) of 0.5666 obtained the optimum cluster of 4 clusters. Cluster 1 (confirmed cases of high
death) 35 urban villages, clusters 2 and 3 (confirmed cases under treatment, confirmed cases recovered, and confirmed cases of low death) 56 and 49 urban villages, and cluster 4 (confirmed cases under treatment and confirmed cases recovered high) 14 urban villages.