The Implementation of Control Charts as a Verification Tool in a Time Series Model for COVID-19 Vaccine Participants in Pontianak

Abstract

Vaccines are the primary weapon used to stop the outbreak, especially amid the COVID-19 pandemic. Thus, supplying vaccines to control the COVID-19 pandemic is essential, especially in minimizing the incidence and achieving herd immunity to break the chain of COVID-19. West Kalimantan has taken firm anticipatory steps to prevent COVID-19 in the form of a vaccination program in Indonesia. The highest vaccination achievement occurs in Pontianak City, the province’s capital. The research analyzed data on vaccine participants in Pontianak using time series analysis. In addition, the residuals from the time series model were used as observations in constructing the control chart. The research also analyzes the accuracy of the time series model using the Individual Moving Range (IMR) control chart. The results show that the ARIMA model (5,0,2) is the best because it fulfills the assumption of white noise. However, the ARIMA (5,0,2) model is inaccurate in making predictions because the residuals from the ARIMA (5,0,2) model are out of control (based on the IMR control chart). Hence, it is necessary to evaluate in determining the time series model. It can be analyzed using a control chart. Therefore, measuring the model’s accuracy on the best model is essential in predicting several subsequent periods.