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All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Herferry, Ibrahim Ade
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Computer Science & IT Control & Systems Engineering

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Analisis Prediksi Jangka Panjang COVID 19 Fase ke 3 di Indonesia menggunakan Deep Learning Herferry, Ibrahim Ade; Ferdiansyah, F; Kunang, Yesi Novaria; Purnamasari, Susan Dian
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 4 (2024): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i4.474

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
Co-Authors Ferdiansyah Ferdiansyah Susan Dian Purnamasari, Susan Dian Yesi Novaria Kunang