Pola Spasial Penyebaran Wabah COVID-19 Menggunakan Sistem Informasi Geografis (Studi Kasus: Provinsi DKI Jakarta)

Abstract

The COVID-19 pandemic has been running in Indonesia for more than a year. The case first was find in March 2020. DKI Jakarta as the capital city of the country with a high population density and an economic center that was threatened because the area has a high vulnerability to the spread of COVID-19. The number of confirmed cases that continues to soar and the spread that is difficult to control has resulted in the DKI Jakarta government taking policies such as implementing large-scale social restrictions (PSBB), which aims to stop the spread of COVID-19, and to look for patterns of spread of COVID-19. In this study using a geographic information system in looking for patterns of the spread of COVID-19. The analytical method used is spatial autocorrelation, which is carried out using the Moran Index. In addition, the autocorrelation test was also carried out using local Indicator of spatial autocorrelation (LISA) with the results in the form of a cluster map and a map of significance. Ordinary Least Squares analysis method is a regression technique that provides a global model for understanding and predicting variables in research. The correlation variables used in this research are Markets, Supermarkets, Buses, and Stations. The result of this study is the spatial autocorrelation of the pattern of spread of COVID-19 between villages and spatially the distribution pattern is clustered. In the OLS regression distribution pattern, the supermarket variable with an R-Squared value of 0.128555 or 12% affects the spread of COVID-19. Based on the calculation of R-Square, Koenker (BP) and also on the OLS model the assumption of homoscedasticity is not met, so the model is Ordinary Least Squares not good compared to other models in analyzing the pattern of the spread of COVID-19 in DKI Jakarta.