Abstract:
COVID-19 spreading has become a noveland serious issue globally,and the number of COVID-19 infection cases has been rapidly risen, causing a crucial impact on the healthcare system and economic crisis. In Southeast Asia, there are many of daily COVID-19 infection cases in many countries leading to several problems. A large number of people are aware of the pandemics and exposed to new information and studies to prevent and tackle the situation.The aim of this study was to adopt an appropriate statistical analysis to compare the mean differences of the monthly number of COVID-19 confirmed cases in the Southeast Asia countries and the associationbetween the geography and the monthly number of COVID-19 infections cases in the Southeast Asia region during2020. The data, the total cumulative number of COVID-19 confirmed casesand the monthly number of COVID-19 infection cases, can be accessed by the free resource of Our World in Data, which is a reliable data source. These data are analyzed by R program. The results showed that Indonesia was affected dramatically by COVID-19 spreading with approximately 600,000 cumulative infection cases as a resultof the descriptive analysis method. The Kruskal Wallis test and Dunns test revealed there were significant mean differences in the monthly number of COVID-19 infection cases in the Southeast Asia countries during 2020 (p<0.05).In addition, the Chi-square test has shown that the geography was associated with the monthly number of COVID-19 infection cases (p<0.05).