Spatial Pattern of Covid-19 In West Java and DKI Jakarta

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.

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Publication Details

Journal
International Journal of Social Science and Human Research
Published
2025-08-22
DOI
https://doi.org/10.47191/ijsshr/v8-i8-62
Primary Topic
COVID-19 Prevention and Impact
Type
article
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article

Spatial Pattern of Covid-19 In West Java and DKI Jakarta

NI LUH PUTU SUCIPTAWATI, I Made Eka Dwipayana, I Gede Swastama Putra
International Journal of Social Science and Human Research
COVID-19 Prevention and Impact
article

Spatial Pattern of Covid-19 In West Java and DKI Jakarta

NI LUH PUTU SUCIPTAWATI, I Made Eka Dwipayana, I Gede Swastama Putra
article en

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.

International Journal of Social Science and Human ResearchVol. 08(08)
Openalex Percentile: Top 71%
COVID-19 Prevention and Impact
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Spatial Pattern of Covid-19 In West Java and DKI Jakarta — NI LUH PUTU SUCIPTAWATI, I Made Eka Dwipayana, et al. · International Journal of Social Science and Human Research (2025) | TGRS Research Map | TGRS