PEMODELAN PREDIKSI PUNCAK PANDEMI VIRUS SARS-COV-2 DI INDONESIA DENGAN ANALISIS REGRESI
Keywords:
Pandemic Peak Prediction, Logistic Regression, Sars-Cov-2 VirusAbstract
The increasing spread of the outbreak caused by the Sars-Cov-2 virus is making the world even more worried. The virus, which began in the Chinese mainland, entered Indonesia on March 2, 2020 and has infected more than 400,000 people in Indonesia until now. Mitigation steps need to be taken, one of which is by knowing the peak of the pandemic and the number of people who can infected by Sars-Cov-2 virus at any one time. Time series regression analysis was used in this research to obtain a predictive result that gave the smallest error value. Logistic regression with logit variant logistic binary regression was used to predict in this research. This technique is used because it is considered good because of the simplicity of this technique, but it can work with both binary and categorical data. The results obtained are that the peak of this virus can reach 5911 people infected per day, with the peak of the pandemic occurring on 110 days after March 2 or the second wave occurring at 110 days after June 20, 2020. The accuracy result obtained is 0.99 with the resulting error less than 0.01.
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