A New Prediction of Daily Number of New Cases and Total Number Infected for nCOVID-19 Plague Infections In Indonesia with the Modification of the Bernoulli Differential Equation

TL;DR

This paper develops a modified Bernoulli differential equation model to predict daily and total COVID-19 cases in Indonesia, demonstrating high accuracy with R2 values of 0.9927 and 0.807, respectively.

Contribution

It introduces a modified Bernoulli differential equation model for COVID-19 case prediction in Indonesia, validated with real data and MATLAB simulations.

Findings

Peak daily cases around 400 in mid-June

Total cases estimated at approximately 12,000

Model shows high correlation with real data (R2=0.9927)

Abstract

The application of differential equations is commonly used in mathematics and physics, as well as various other sciences to explain a phenomenon in a system. This paper explains the mathematical modeling in the analysis of the nCOVID-19 plague in Indonesia on March 3, 2020, to April 19, 2020, with the modification of the Bernoulli equation and the simulation by MATLAB. In this study, it can be concluded that it was found that the daily number of nCOVID-19 cases in Indonesia will have the highest case at a maximum of around 400 and the total number of positive nCOVID-19 in Indonesia will reach 12000 people with a quiet period in mid-June. In this modeling, it has also been found that the value of R2 = 0.9927 on the total number of positive nCOVID-19 in Indonesia taken from 3 March 2020 to 19 April 2020, while the value of R2 = 0.807 daily number of positive new cases of nCOVID-19 in Indonesia taken from March 3, 2020, to April 19, 2020. Based on this research, it can be shown that the nCOVID-19 model for a case in the Indonesia plague is quite accurately compared by the real data.