This research is motivated by the ongoing impact of the COVID-19 pandemic, which continues to pose challenges for Indonesia, affecting both the economy and daily life. Therefore, this study will discuss long-term predictions for the third phase of COVID-19 in Indonesia using a Deep Learning model. The analysis aims to assist various stakeholders in developing better planning strategies to address COVID-19 in Indonesia. In conducting this research, the author employs neural networks to create a hybrid model combining GRU and LSTM algorithms. Utilizing RMSE and MAPE values, it can be concluded that the model's performance in predicting COVID-19 cases is influenced by the number of epochs used. Furthermore, the model demonstrates optimal performance at 150 epochs for predicting the number of COVID-19 cases in the next 7 days
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