Deep Neural Network untuk Klasifikasi Influenza

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.