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All Journal In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Abdillah, Muhammad Syaddad
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Arts Computer Science & IT Economics, Econometrics & Finance Other

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Deep Neural Network untuk Klasifikasi Influenza Danestiara, Venia Restreya; Abdillah, Muhammad Syaddad
In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Vol 21 No 2 (2022): In Search
Publisher : LPPM UNIBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/insearch.v21i2.956

Abstract

In facing the global threat posed by the Influenza virus, similar to COVID-19, which has the potential to cause pandemics with serious impacts on public health and the economy, this research implements a Deep Learning algorithm for the classification of Influenza viruses based on a dataset containing various characteristics of the virus. The dataset has undergone preprocessing steps, including the removal of irrelevant columns, handling of missing values, and encoding of categorical variables. A Deep Neural Network (DNN) model was developed and trained using cross-validation techniques to enhance performance. Evaluation results show a high level of accuracy in the classification of Influenza viruses. This study concludes that Deep Learning algorithms are effective in classifying Influenza viruses.
Co-Authors Venia Restreva Danestiara