Analisis Spasial Persebaran COVID-19 di Indonesia Menggunakan Metode K-Means Clustering dan ESD

Abstract

The COVID-19 pandemic, which began in March 2020, has had a significant impact on public health in Indonesia. Although case numbers have started to decline, understanding the spatial spread of the virus remains crucial for effective response efforts. Conventional analyses that rely solely on descriptive statistics often overlook spatial relationships between regions. This study combines Exploratory Spatial Data Analysis (ESDA) and K-Means Clustering to examine the spatial distribution of COVID-19 cases and group Indonesian provinces based on the number of cases, recovery rates, and mortality rates. The data used include Indonesias provincial shapefiles from GADM and COVID-19 case data from Data Wrapper. The analysis reveals three main clusters. Cluster one includes DKI Jakarta, West Java, and Central Java, characterized by high case numbers and mortality rates, with below-average recovery rates. Cluster two consists of East Java, North Sumatra, and South Sulawesi, with relatively low case numbers, very low recovery rates, and high mortality rates. Cluster three comprises 26 other provinces with lower case numbers, high recovery rates, and low mortality rates. These findings indicate that COVID-19 transmission in Indonesia is not spatially uniform, highlighting the need for targeted intervention in high-risk areas.