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DOI: 10.14569/IJACSA.2022.0131239
PDF

Estimation of Transmission Rate and Recovery Rate of SIR Pandemic Model Using Kalman Filter

Author 1: Wahyu Sukestyastama Putra
Author 2: Afrig Aminuddin
Author 3: Ibnu Hadi Purwanto
Author 4: Rakhma Shafrida Kurnia
Author 5: Ika Asti Astuti

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 12, 2022.

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Abstract: COVID-19 is a global pandemic that significantly impacts all aspects. The number of victims who died makes this disease so terrible. Various policies continue to be pursued to reduce the spread and impact of COVID-19. The spread of a disease can be modeled in differential equation modeling. This differential equation modeling is known as the SIR Model. A differential equation can be expressed in a state-space model. The state-space model is a model that is widely used to design a modern control system. This research carried out the transmission rate and recovery rate estimates in the SIR pandemic model. Estimation of the transmission rate and recovery rate in this study poses a challenge to the value of the number of people confirmed as infected. The experimental result shows that the transmission and recovery rates can be estimated using the data for the infected and recovered persons. Estimates of infected and recovered people were conducted using the Kalman Filter.

Keywords: Kalman filter; pandemic; SIR model

Wahyu Sukestyastama Putra, Afrig Aminuddin, Ibnu Hadi Purwanto, Rakhma Shafrida Kurnia and Ika Asti Astuti, “Estimation of Transmission Rate and Recovery Rate of SIR Pandemic Model Using Kalman Filter” International Journal of Advanced Computer Science and Applications(IJACSA), 13(12), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131239

@article{Putra2022,
title = {Estimation of Transmission Rate and Recovery Rate of SIR Pandemic Model Using Kalman Filter},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131239},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131239},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {12},
author = {Wahyu Sukestyastama Putra and Afrig Aminuddin and Ibnu Hadi Purwanto and Rakhma Shafrida Kurnia and Ika Asti Astuti}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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