Analysis of Covid-19 Spread in Palopo City Using DBSCAN Algorithms

Abstract

Pandemic Covid-19 has spread rapidly, causing a severe health crisis worldwide, including Indonesia. As is well known, due to Indonesia’s diverse population, there are differences in the number of cases between cities. Therefore, a distribution clustering process is needed to develop a map of Covid-19 cases which aims to enable optimal handling of this pandemic. In this study, DBSCAN was used for the clustering process of Covid-19 spread on Palopo city. Clustering using the DBSCAN algorithm is needed to find out the clusters that are formed and the location of Covid-19 spread in certain areas. The result of clustering using DBSCAN show that the largest cluster has a total 0f 432 cases that occurred throughout the time period with an average of 15 cases per day. After visualization, the most distribution of Covid-19 was in the central area of Palopo City and concentrated in Wara District with 250 cases.