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Prediksi puncak pandemi Covid-19 di Indonesia dengan model SIR

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

Department of Informatics, Universitas Telkom. Jl. Telekomunikasi Terusan Buah Batu, Bandung 40257, Indonesia

Received: 25 Aug 2020; Revised: 30 Nov 2020; Accepted: 7 Dec 2020; Available online: 18 Dec 2020; Published: 31 Jan 2021.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
This research implements the Susceptible, Infected, and Removed (SIR) model to predict 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 mean squared error (MSE). The study uses one of the Quasi-Newton search methods, the Broyden, Fletcher, Goldfarb, and Shanno (BFGS) algorithm, 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 of 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 by 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

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