Transition Probability Markov Chain For Asymtomatic and Suspect Classification Covid-19 in Batam City Gaby Wilanda Teacher, Herlina Hanum, Des Alwine Zayanti, Dian Cahyawati Sukanda
Sriwijaya University
Abstract
The aim of this study is to analyze and determine the transition probability asymptomatic cases and suspect cases Covid-19 in Batam using discrete time Markov Chain analysis. The data analyzed was obtained from daily Covid-19 positive case data from Press Release Against Corona Batam from January 1, 2021 to June 30, 2021. The results of the Markov Chain analysis with three states namely stagnant, decreased and rising state indicate that for long-term conditions in asymptomatic case, the probability of transition in a stagnant state is 0,067, in a decreased state is 0,483 and the probability of transition is increased is 0,450. The transition probability for the characteristics of the suspect case in a fixed state is 0,107, the situation will decrease is 0,408, and the transition probability will increase is 0,485. These results indicate that a greater chance for the long term of each state exists in the suspect case.
