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ANALISIS KASUS COVID-19 DI PROVINSI NUSA TENGGARA BARAT MENGGUNAKAN METODE RANTAI MARKOV Dara Puspita Anggraeni; Attina Ulansari; Mustika Hadijati; Lisa Harsyiah
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 14 No 2 (2022): Journal of Statistical Application and Computational Statistics
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v14i2.356

Abstract

The aim of this research is to determine the shape of the matrix of the transition opportunity and predict the probability of the occurrence of Covid 19. The method used is Markov Chain which utilizes historical data from Covid 19 cases. This method can explain the probability of occurrence in stages or per state. The data used is data on positive cases, recovered and died from Covid 19, starting from January 24 to April 23, 2021. The results of this study are in the form of a transition opportunity matrix for each Covid 19 case and the highest probability value at steady state for positive patient cases is 39.496% in state 3, the probability value in the case of a recovered patient is 33.088% in state 2 and the probability value in the case of a deceased patient is 41.414% is in state 1.