Computing the auto regressive distributed lag (ARDL) method in forecasting COVID-19 data: A case study of NTB Province until the end of 2020

The purpose of this research is to conduct data forecasting on the spread of COVID- 19 in West Nusa Tenggara Province, Indonesia at the end of 2020. The data used in this research is the COVID-19 data in NTB Province including the data of the number of positive patient, the number of patients recovered and the number of patient passed away. The forecasting process uses the Autoregressive Distributed Lag (ARDL) method of the GUI Multiple Forecasting System (G-MFS) based on MATLAB by determining the prediction on the next day of the graph equation generated after the data simulation. The forecasting of the COVID-19 spread in NTB at the end of the year of 2020 obtained that the number of confirmed patients amounting to 19,614 people with an average increase of 1.48%, the number of patients healed are 6,651 with an average increase of 1.10%, and the number of patients died amounting to 4,953 people with an average increase of 2.42%. The average increase in the number of patients who died showed that the provincial government of NTB needs to give more serious attention to handling COVID-19 patients.