Parameters Estimation of Generalized Richards Model for COVID-19 Cases in Indonesia Using Genetic Algorithm

Maya Rayungsari, Muhammad Aufin, Nurul Imamah


In this research, genetic algorithm was implemented to estimate parameters in generalized Richards model by adjusting COVID-19 case data in Indonesia. Data collected were the daily new cases and cumulative number of COVID-19 case in Indonesia from early March to early June 2020, that was reported by The best pair of parameters was selected based on the lowest cost function value, determined from the distance between data with estimated model and real data. Next, model with estimated parameters is used to predict new cases and cumulative cases for upcoming days.
Numerical simulations were carried out so that the peaks and ends of the COVID-19 pandemic can be seen easily.


Parameters Estimation; Generalized Richards Model; COVID-19; Genetic Algorithm

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N. C. Peeri, N. Shrestha, M. S. Rahman, R. Zaki, Z. Tan, S. Bibi, M. Baghbanzadeh, N. Aghamohammadi, W. Zhang, and U. Haque, “The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned?” International Journal of Epidemiology, 2020.

C. Viboud, L. Simonsen, and G. Chowell, “A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks,” Epidemics, vol. 15, pp. 27–37, 2016.

G. Chowell, “Fitting dynamic models to epidemic outbreaks with quantified uncertainty: A primer for parameter uncertainty, identifiability, and forecasts,” Infectious Disease Modelling, vol. 2, no. 3, pp. 379–398, 2017.

A. Szparaga and S. Kocira, “Generalized logistic functions in modelling emergence of Brassica napus L.” PLOS ONE, vol. 13, no. 8, p. e0201980, 2018.

F. J. Richards, “A Flexible Growth Function for Empirical Use,” Journal of Experimental Botany, vol. 10, no. 2, pp. 290–301, 1959.

N. Nuraini, K. Khairudin, and M. Apri, “Modeling Simulation of COVID-19 in Indonesia based on Early Endemic Data,” Commun. Biomath. Sci., vol. 3, no. 1, pp. 1–8, 2020.

Carwoto, “Implementasi Algoritma Genetika untuk Optimasi Penempatan Kapasitor Shunt pada Penyulang Distribusi Tenaga Listrik,” Jurnal Teknologi Informasi DINAMIK, vol. 12, pp. 122–130, 2007.

M. Rayungsari, N. Imamah, A. Imaniyah, and V. B. Kusuma, “Estimasi Parameter Model Predator-prey Menggunakan Algoritma Genetika,” Jurnal Gammath, vol. 4, pp. 103–112, 2019.

S. Anam, “Parameters Estimation of Enzymatic Reaction Model for Biodiesel Synthesis by Using Real Coded Genetic Algorithm with Some Crossover Operations,” IOP Conference Series: Materials Science and Engineering, vol. 546, p. 052006, 2019.

R. D. Hidayaturrachmah, S. Anam, and Marjono, “Allocation of Thesis Supervisor Using Genetic Algorithm,” Jurnal EECCI, vol. 12, pp. 26–32, 2018.

S. Fitra, “Total Kasus & Kasus Baru Covid-19,, diakses tanggal 8 Juni 2020 .”


Copyright (c) 2020 Maya Rayungsari, Muhammad Aufin, Nurul Imamah

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 Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Negeri Gorontalo
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