Prediksi puncak pandemi Covid-19 di Indonesia dengan model SIR

Prediction of the peak Covid-19 pandemic in Indonesia using SIR model

*Bambang Ari Wahyudi scopus  -  Universitas Telkom, Indonesia
Irma Palupi scopus  -  Universitas Telkom, Indonesia
Received: 25 Aug 2020; Revised: 30 Nov 2020; Accepted: 7 Dec 2020; Published: 31 Jan 2021; Available online: 18 Dec 2020.
Open Access Copyright (c) 2021 Jurnal Teknologi dan Sistem Komputer under

Citation Format:
This research implements the SIR (Susceptible, Infected, and Removed) model to predict the situation of the COVID-19 outbreak in Indonesia. The government official data, consisting of infected, dead, and recovered, are used as actual data to interpolate the model through matching data with minimum MSE (Mean Squared Error). One of the Quasi-Newton search methods, the BFGS (Broyden, Fletcher, Goldfarb, and Shanno) algorithm, is used to determine the interaction coefficient's optimal value in the model with the minimum MSE value. Based on data as of July 18, 2020, it predicts that the peak of the infected number will be in October 2020 with around 14% of the total population infected, and the MSE=18.42 is relative to the period of the actual data. Meanwhile, the basic reproduction rate is calculated to be 2.035 from the model, where it is underestimated about 29% compared to the relative basic reproduction rate from the provided actual data.
Keywords: SIR model; BFGS; MSE; pandemic prediction; Covid-19
Funding: Universitas Telkom

Article Metrics:

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