Year: 2025
Type: article
Abstract: This study aims to analyze the spatial pattern of COVID-19 in West Java and DKI Jakarta and identify areas with high case concentrations using spatial analysis methods. The data used is the number of COVID-19 cases. Moran's I analysis was conducted to determine spatial autocorrelation, while Local Indicators of Spatial Association (LISA) was used to identify local spatial patterns. This study used COVID-19 case data from all districts/cities in West Java and DKI Jakarta as the unit of analysis. Moran's I analysis showed a strong positive spatial autocorrelation with a value of 0.661, indicating that areas with a high number of cases tend to cluster with other areas that also have a high number of cases. The results of the LISA analysis identified Jakarta, Bekasi, and Depok as areas with the High-High (HH) category, which means there is a high concentration of cases. Meanwhile, Bekasi Regency is categorized as Low-High (LH), which indicates a low number of cases even though it borders a high-incidence area.
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4413430364