Abstract

Changes in the number of positive COVID-19 patients in Indonesia greatly affect the number of beds in hospitals. Indonesia as a country that has a large population requires an accurate frequency analysis to make policies in dealing with changes in the number of patients. This study focuses on analyzing the frequency of COVID-19 patients by using probability modeling. Probability modeling will be carried out using four probability density functions (pdf) namely Gamma, Amarendra, Rani, and Sujatha 2 Parameters will be used in this study. The estimated parameter from the pdf used in this study will be obtained using the maximum likelihood technique. The distribution will be chosen using a few Good of Fit Test techniques, including graphical (pdf plot and CDF plot) and numerical (Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) methods. The majority of the time, graphical approaches get identical results, however their AIC and BIC results differ. The distribution with the lowest AIC and BIC values is chosen as the best appropriate outcome. The Sujatha two parameter distribution has generally been deemed to be the best model.

Keywords

References

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