Solusi Numerik Model Penyebaran Virus Covid-19 Dengan Vaksinasi Menggunakan Metode Runge-Kutta Fehlbrg Orde Lima Pada Provinsi Maluku - Rijoly, Monalisa E.; Rumlawang, Francis Y.; Maurits, Stefalya (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia, 2023)
COVID-19 is a new type of disease that has never been identified in humans before. The virus that causes COVID-19 is called Servere Acute Respiratory Syndrome Coronavirus-2 (Sars-Cov-2). The purpose of this study is to predict the spread of the COVID-19 virus by vaccination in Maluku Province in the next 20 months. The mathematical model used in this study is SEIRV with five sub-populations. Susceptible sub population (S), patient under surveillance (PDP)/Exposed sub population (E), Infected (I), Recovered (R), and Vaccinated (V) sub population as initial values S0 =190.295, E0=261, R0=172, and V0=7.693. Furthermore, numerical model simulations using the fifth order Runge-Kutta Fehlberg method over the next 20 months are for the susceptible sub population (S) of 693 people, for the Patient Under Monitoring sub population (PDP) (E) of 101 people, for the sub population infected (I) of 301 people, for the rate of recovery population (R) of 704 people and for the vaccinated sub population (V) of 16,951 so that it can be concluded that the sub population (V) has effectiveness because the susceptible sub population (S) decreases so that vaccination can be a solution to prevent the spread of the COVID-19 virus in Maluku Province within the next 20 months.