Spatial Autocorrelation using Moran's Index to Map the Confirmed Positive of Covid-19 Cases in Java

ABSTRACT

Various policies to suppress Covid-19 cases have been implemented by the government since Covid-19 first appeared in Indonesia in March 2020. The island of Java has become one of the government's focuses in suppressing the Covid-19 cases, considering that the island of Java is central in Indonesia. Six provinces on the island of Java are also the provinces with the highest cases. DKI Jakarta, West Java, and Central Java are the three provinces with the most cases. The spread of Covid-19 cases on the island of Java is possible to occur spatially, given the easy access to mobility. One of the measuring tools in Statistics that can be used to see the correlation between locations is the Moran's Index method. This method considers the global spatial autocorrelation. This study aims to measure the spatial correlation and map the government policies' results in Covid-19 cases. This study looks at the spatial autocorrelation between provinces on Java Island based on data confirmed positive for Covid-19 from January 11st to October 31st, 2021. The data obtained are grouped based on the date of government policies related to extensive and micro-scale social restrictions;namely, there are 26 observations. The result is that four observations have positive spatial autocorrelation, and the rest have negative autocorrelation. The spatial influence between provinces on Java Island globally, which correlates with more than 50%, occurred in 12 observations (extension of PPKM, micro PPKM, and emergency PPKM). © 2023 American Institute of Physics Inc.. All rights reserved.