<![CDATA[The Indonesian government and public healthcare system have been under massive pressure dueto increased infections and mortality rates among Covid-19 patients. An appropriate model isneeded to model the mortality of Covid-19 patients in Indonesia to help the Indonesiangovernment develop the right policy for dealing with the Covid-19 pandemic. Artificial neuralnetworks are increasingly popular in various research fields. Artificial neural networks can detectspecific patterns in mortality modeling. In this study, we use artificial neural networks to modelthe 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 ofartificial neural networks with that of the Holt-Winters method. The results showed that the bestmodel of artificial neural networks produced an RMSE of 3.0530. In contrast, the Holt-Wintersmethod produced an RMSE of 664.9022. Therefore, the artificial neural networks performedbetter than the Holt-Winters method in analyzing mortality data of Covid-19 patients inIndonesia.]]>
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