Transmission Rate Estimation of COVID-19 in Bandung Using SIR Model and Runge-Kutta Fourth-order

The global outbreak of COVID-19, initially detected in Wuhan, China, at the end of 2019, has rapidly escalated into a pandemic, affecting numerous countries worldwide, including Indonesia. Among the impacted regions in Indonesia, Bandung, a significant city in West Java, has experienced a notable spread of the virus. This research focuses on predicting the transmission of COVID-19 in Bandung using the Susceptible, Infected, Recovered (SIR) model, a foundational framework in epidemiology. The SIR model in this research is solved using the Runge-Kutta $4^{th}$ Order (RK4) method, a numerical approach known for its high accuracy in solving differential equations. The model was applied to a dataset of COVID-19 cases in Bandung obtained from the Bandung COVID-19 Information Center from February 2021 to June 2023. The data was processed to handle missing values. Missing values are handled using the LOCF approach and then used to simulate the spread of the virus. This research aims to evaluate the effectiveness and accuracy of the SIR model when combined with the RK4 method in predicting COVID-19 transmission dynamics in Bandung. The findings reveal that this approach is effective, as demonstrated by the low RMSE values of 0.15 for infected and 0.7 for recovered cases. This close agreement between the model's predictions and actual data underscores the importance of accurately calibrating the transmission rate within the model, as it significantly influences the model's predictive accuracy. This research highlights the SIR model's potential, enhanced by the RK4 method, as a reliable tool for forecasting pandemic trends in Bandung.