SPATIO-TEMPORAL MODEL FOR PREDICTING COVID19 CASES IN INDONESIA

Objective: Spatio-temporal modelling is a method used for data which has spatial (area) and temporal (time) property. Confirmed cases of Covid19 in each province Indonesia were recorded from March 2nd to September 15th, 2020. The spatio-temporal model this study are split into two parts ARIMA(p,d,q) the pattern Bayesian Poisson regression explain pattern.Method: Data was obtained Repository Indonesian National Board Disaster Management - Task Force Covid-19 Rapid Response (Gugus tugas Percepatan penangana Covid19) official website an opened source data. Rstudio, Arcgis excel carry out statistical analysis involved investigation. In analysis, assumed have increasing trend create stationary series, integrated conducted. Box-Jenskin Ljung-Box taken parameter estimation identification process. For Regression fitted dataset with Metropolis algorithm.Result: Model IMA(1,1), general, can he confirmed Indonesia. This define that case number at particular time affected by moving average lag-1. Meaanwhile, elaborate shows also population density those provinces. As there some limitation applied study, further research needed.