Gian Septiansyah
Program Studi Matematika Fakultas MIPA Universitas Lambung Mangkurat Jl. A. Yani KM. 36, Banjarbaru 70714, Kalimantan Selatan

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PEMODELAN MATEMATIKA PENYEBARAN COVID-19 DENGAN MODEL SVEIR Gian Septiansyah; Muhammad Ahsar Karim; Yuni Yulida
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol. 16(2), 2022
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v16i2.6496

Abstract

Coronavirus disease 2019 or also known as Covid-19 is a disease caused by a type of coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) or better known as the corona virus. Covid-19 become a pandemic since 2020 and has been widely studied, one of which is in mathematical modeling. In this study, the spread of Covid-19 is modeled using the SVEIR (Susceptible, Vaccination, Exposed, Infected, and Recovered) model. The purpose of this study explains the formation of the Covid-19 SVEIR model, determines the equilibrium point, determines the basic reproduction number, and analyzes the stability of the Covid-19 SVEIR model. The purpose of this study explains the formation of the Covid-19 SVEIR model, determines the equilibrium point, the basic reproduction number, and analyzes the stability of the Covid-19 SVEIR model. The result of this study is to explain the formation of the Covid-19 SVEIR model and obtained two equilibrium points, the disease-free equilibrium point and the endemic equilibrium point. Furthermore, the basic reproduction number  is obtained through the Next Generation Matrix method. The results of the stability analysis at the disease-free equilibrium point were locally asymptotically stable with conditions  while at the endemic equilibrium point local asymptotically stable with conditions . The natural death rate is greater than the effective contact rate. A numerical simulation is presented to show a comparison spread of Covid-19 by providing different levels of vaccine effectiveness using the Runge-Kutta Order method.