The Use of ST-DBSCAN in the Analysis of Covid-19 Spread Patterns Based on Spatio-Temporal Data

Abstract

The spread of Covid-19 poses significant risks, necessitating strict policies and specialized plans. One of the measures that can be taken to help control the spread is accurately identifying areas with a high number of Covid-19 cases and areas with lower case numbers. This study aims to analyze the spread of Covid-19 using the ST-DBSCAN algorithm. The ST-DBSCAN algorithm was applied to Covid-19 spread data in Makassar city in August and September 2021, using spatial aspect parameters (Eps1) = 0.002, temporal aspect (Eps2) = 14, and minimum cluster members (MinPts) = 10, resulting in 78 clusters and 1639 noise points. The clusters formed through the application of the ST-DBSCAN algorithm were used to analyze patterns based on spatio-temporal aspects. The spatio- temporal patterns identified include occasional patterns and stationary patterns. The analysis results indicate that the area with the highest Covid-19 spread is in the southeastern part of Makassar city, specifically in Rappocini district, with 921 cases.