Analisis Prediksi Jangka Panjang COVID 19 Fase ke 3 di Indonesia menggunakan Deep Learning

Ibrahim Ade Herferry(1*), F Ferdiansyah(2), Yesi Novaria Kunang(3), Susan Dian Purnamasari(4),

(1) Universitas Bina Darma, Palembang, Indonesia
(2) Universitas Bina Darma, Palembang, Indonesia
(3) Universitas Bina Darma, Palembang, Indonesia
(4) Universitas Bina Darma, Palembang, Indonesia
(*) Corresponding Author

Abstract


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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DOI: https://doi.org/10.30645/kesatria.v5i4.474

DOI (PDF): https://doi.org/10.30645/kesatria.v5i4.474.g469

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