THE IMPLEMENTATION OF FINITE-STATES CONTINUOUS TIME MARKOV CHAIN ON DAILY CASES OF COVID-19 IN BANDUNG

  • Putri Monika Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia
  • Christophorus Soetikno Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia
  • Atje Setiawan Abdullah Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia
  • Budi Nurani Ruchjana Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia
DOI: https://doi.org/10.30598/barekengvol17iss1pp0085-0094
Keywords: Continuous-time Markov chain, finite-state, stationary distribution, limit distribution, COVID-19

Abstract

Markov chain is a stochastic process to describe a phenomenon in the future based on a previous state. In practice, Markov chains are distinguished by time into two, namely discrete-time Markov chain and continuous-time Markov Chain. This research will discuss the continuous-time Markov chain with finite-state. COVID-19 phenomena can describe and predict using the continuous-time Markov chain. Authors use the data daily cases of COVID-19 in Greater Bandung including Bandung City, Bandung District, West Bandung District, Cimahi City and Sumedang District. Used data came from simulated data of daily cases of COVID-19 in Greater Bandung from August, 2020 until November 14, 2021 that recorded through the website COVID-19 of West Java. In terms of described and predicted the COVID-19 phenomenon in Greater Bandung for long-term probability, authors use stationary distribution and limit distribution. COVID-19 phenomenon is described into two states: state 0 (lower than average of data) and state 1 (higher than average of data). The result of continuous-time Markov chain with finite-state shows that the probability of the daily cases of COVID-19 for five locations in Greater Bandung is state 0 have a larger probability than state 1. It means that COVID-19 in Greater Bandung over the long-term will decrease.

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Published
2023-04-15
How to Cite
[1]
P. Monika, C. Soetikno, A. Abdullah, and B. Ruchjana, “THE IMPLEMENTATION OF FINITE-STATES CONTINUOUS TIME MARKOV CHAIN ON DAILY CASES OF COVID-19 IN BANDUNG”, BAREKENG: J. Math. & App., vol. 17, no. 1, pp. 0085-0094, Apr. 2023.
Issue
Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2023 Putri Monika, Christophorus Soetikno, Atje Setiawan Abdullah, Budi Nurani Ruchjana

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