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Khairul Azman
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering

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USING THE YOU ONLY LOOK ONCE (YOLO) METHOD FOR DETECTING PHYSICAL DISTANCING AND MASKED FACES Khairul Azman; Muhammad Arhami; Azhar; Zhenyu Cui
Bulletin of Engineering Science, Technology and Industry Vol. 1 No. 3 (2023): September
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v1i3.17

Abstract

The flow of news regarding the development of Covid-19 has dominated various information channels in Indonesia in the last 2 years, either through print media or digital media. Various types of news related to Covid-19 continue to circulate, including hoax news. One of the hoax news that is widely circulating is news about the Covid-19 vaccine. The rise of information containing hoax news and untrue rumors about the Covid-19 vaccine in society can worsen the pandemic situation. Currently there is no intelligent system capable of classifying hoaxes regarding the Covid-19 vaccine. To maximize prevention of the spread of hoax news about the Covid-19 vaccine and overcome the problems faced, the author designed a classification system for hoax news about the Covid-19 vaccine using a machine learning approach. The system built can classify news using a combination of the Name Entity Recognition (NER) and Backpropagation algorithms. The datasets used are: 600 Covid-19 vaccine news data obtained from the sites https://turnbackhoax.id/ and https://www.kompas.com/ with the keyword "covid vaccine". The dataset is divided into two, training data and test data. The training data is preprocessed and then used in model design. Test data is used to evaluate the results of model design. This process produces a machine learning model with a good accuracy level of 97.62%.
Co-Authors Arhami, Muhammad Azhar Zhenyu Cui