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Muljana , Hizkia Abiel
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Chemistry Environmental Science Immunology & microbiology Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Physics Social Sciences

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Convolutional Neural Network Method in Determining Pfizer Vaccination Sentiment Analysis Supono, Riza Adrianti; Muljana , Hizkia Abiel
Journal of Social Science Vol. 5 No. 4 (2024): Journal of Social Science
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jss.v5i4.869

Abstract

Coronavirus (COVID-19) is a disease caused by the SARS-CoV-2 virus by attacking the respiratory system in humans and because of the rapid spread of infection, WHO declared COVID-19 a pandemic. Over time, several types of vaccines have been discovered which are thought to minimize the possibility of infection. One of the vaccines is Pfizer. During the use of the Pfizer vaccine, there have been pros and cons caused by the side effects of using the vaccine. Therefore, sentiment analysis was carried out on public opinion with data sourced from tweets on Twitter. The method used in making the model is Convolutional Neural Network (CNN). This model has been successfully created and has been tested on 1158 training data and 773 test data. The training data obtained an accuracy level of 98.87 % and the test data obtained an accuracy level of 69.46%.
Co-Authors Riza Adrianti Supono, Riza Adrianti