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All Journal Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan
Sapulette, Nona Tjie
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Numerical Solution Of The SIRV Model Using The Fourth-Order Runge-Kutta Method Rijoly, Monalisa E; Lesnussa, Yopi Andry; Sapulette, Nona Tjie
Jurnal Matematika Vol 13 No 2 (2023)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2023.v13.i02.p164

Abstract

This study aimed to predict the spread of the Covid-19 virus in Maluku Province using the fourth-order Runge-Kutta method. The mathematical model of the spread of the Covid-19 virus is a system of differential equations which includes Susceptible (S) variables, namely human subpopulations that are susceptible to Covid-19 virus infection, Infected (I), namely human subpopulations infected with the Covid-19 virus, Recovered (R) namely subpopulation of people who have recovered and Vaccination (V) namely a subpopulation that has been vaccinated and is immune to the Covid-19 virus, used as initial values. The values of are parameter values that are numerically solved by the fourth-order Runge-Kutta method performed for 24 literations with . Data were obtained from the Maluku Provincial Health Office from March 2022 - November 2022. Based on the data obtained, the average of the data is used as the initial value, where . The initial and parameter values were substituted into the numerical solution and simulated using Matlab. The rate value of each class for the next 24 months for the Susceptible (S), Infected (I), and Recovered (R) classes has decreased until it approaches zero equilibrium. It shows that the subpopulation of the three classes no longer exists, and the Vaccinated (V) class has increased significantly because almost all of the population has been vaccinated in the next 24 months. It shows that after an individual is vaccinated, he does not return to being vulnerable.
DYNAMICS OF A SIRV MODEL FOR THE SPREAD OF COVID-19 IN MALUKU PROVINCE Sapulette, Nona Tjie; Lesnussa, Yopi Andry; Rijoly, Monalissa E
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1673-1684

Abstract

COVID-19 (Coronavirus Disease 2019) is caused by the SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) coronavirus spreading around the world. In this study, the SIRV model was used, which is an epidemic model carried out by grouping the population into four subpopulations, namely the subpopulation of susceptible individuals who can be infected (Susceptible), the subpopulation of infected individuals (Infected), the subpopulation of individuals who recover from illness (Recovered), and the subpopulation of individuals who have been vaccinated (Vaccination). Based on the dynamic system analysis conducted, two equilibrium points were obtained, namely the disease-free equilibrium point and the endemic equilibrium point. In addition, based on data processing and model simulation results obtained, was obtained so that it can be concluded that the higher the number of vaccinated populations, the lower the level of Covid-19 spread, which means that vaccines can suppress cases of Covid-19 spread in Maluku Province
Co-Authors Rijoly, Monalisa E Rijoly, Monalissa E Yopi Andry Lesnussa