DOI: https://doi.org/10.14710/jfma.v6i1.17861

ARTIFICIAL NEURAL NETWORK APPLICATION IN MODELING MORTALITY OF COVID-19 PATIENTS IN INDONESIA

*Rika Fitriani  -  Universitas Gadjah Mada, Indonesia
Ruth Cornelia Nugraha  -  Universitas Gadjah Mada, Indonesia

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Abstract

The Indonesian government and public healthcare system have been under massive pressure due
to increased infections and mortality rates among Covid-19 patients. An appropriate model is
needed to model the mortality of Covid-19 patients in Indonesia to help the Indonesian
government develop the right policy for dealing with the Covid-19 pandemic. Artificial neural
networks are increasingly popular in various research fields. Artificial neural networks can detect
specific patterns in mortality modeling. In this study, we use artificial neural networks to model
the mortality rate of Covid-19 patients in Indonesia. We try combinations of activation functions,
learning rates, and hidden layers for the best predictions. We compare the prediction accuracy of
artificial neural networks with that of the Holt-Winters method. The results showed that the best
model of artificial neural networks produced an RMSE of 3.0530. In contrast, the Holt-Winters
method produced an RMSE of 664.9022. Therefore, the artificial neural networks performed
better than the Holt-Winters method in analyzing mortality data of Covid-19 patients in
Indonesia.

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Keywords: artificial neural networks, mortality rate, Covid-19

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Section: FUNDAMENTAL MATHEMATICS AND APPLICATIONS
Language : EN
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