Covid-19 Data Analysis in Tarakan with Poisson Regression and Spatial Poisson Process

COVID-19 entered Indonesia in March 2020 and included North Kalimantan Province, Tarakan. cases have outspread The cause of the patterns were not known yet. One relevant approach was to use Generalized Linear Models. two methods are Poisson Regression Stochastic with Spatial Process. variables used rainfall, population density, temperature each village analysis founds that only one factor affected temperature. Then, results refined Process, where addition influencing factors also, distribution obtained. showed pattern case non-homogeneous process criteria. Then model density intensity obtained using regression. From model, it covariate significantly influence rainfall Compared general regression analysis, average had a significant effect. Thus, better method used, namely It also shown by models' AIC values, value Process smaller than Regression.