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Inna Syafarina
Research Center of Informatics, National Research and Innovation Agency. Jl. Sangkuriang, Komplek LIPI Gedung 20 Lt. 3, Bandung 40135|National Research and Innovation Agency
Computer Science & IT Electrical & Electronics Engineering

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Comparison of various epidemic models on the COVID-19 outbreak in Indonesia Intan Nuni Wahyuni; Ayu Shabrina; Inna Syafarina; Arnida Lailatul Latifah
Jurnal Teknologi dan Sistem Komputer Volume 10, Issue 1, Year 2022 (January 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2021.14222

Abstract

This paper compares four mathematical models to describe Indonesia's current coronavirus disease 2019 (COVID-19) pandemic. The daily confirmed case data are used to develop the four models: Logistic, Richards, SIR, and SEIR. A least-square fitting computes each parameter to the available confirmed cases data. We conducted parameterization and sensitivity experiments by varying the length of the data from 60 until 300 days of transmission. All models are susceptible to the epidemic data. Though the correlations between the models and the data are pretty good (>90%), all models still show a poor performance (RMSE>18%). In this study case, Richards model is superior to other models from the highest projection of the positive cases of COVID-19 in Indonesia. At the same time, others underestimate the outbreak and estimate too early decreasing phase. Richards model predicts that the pandemic remains high for a long time, while others project the pandemic will finish much earlier.
Co-Authors Arnida Lailatul Latifah Ayu Shabrina Intan Nuni Wahyuni