Deteksi Konten Hoaks Pada Media Sosial Twitter dan Facebook Menggunakan Metode Naïve Bayes dengan Studi Kasus Covid – 19
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Institusion
Politeknik Negeri Jember
Author
Anjarwati, Retno
Subject
458 - Teknik Informatika
Datestamp
2022-04-05 02:04:49
Abstract :
With the rapid development of the internet, information sources can be accessed more easily and faster. Social media has transformed into one of the main means for exchanging information and communicating in cyberspace. Sharing information with others is a positive thing, but not all information disseminated through social media is in the form of facts. There have been various cases of spreading news that are not facts or are often called hoaxes. One of the hoaxes that is also widely circulated through social media is the hoax about Covid-19. The more widespread the trend of hoaxes that poison the news, especially on social media, ideas have also emerged to take preventive measures against the spread of hoax news. This study will focus on detecting hoax content circulating on social media Twitter and Facebook regarding Covid-19 using the nave Bayes algorithm and TF - IDF weighting. The data used is 2,480 data taken from Social Media Twitter and Facebook. The evaluation results show that the Naïve Bayes Classifier algorithm has a good performance level to identify hoax or non-hoax news with an accuracy of 89% in the first experiment, K-Fold Validation at 90.2% and in the third experiment at 95%.
With the rapid development of the internet, information sources can be accessed more easily and faster. Social media has transformed into one of the main means for exchanging information and communicating in cyberspace. Sharing information with others is a positive thing, but not all information disseminated through social media is in the form of facts. There have been various cases of spreading news that are not facts or are often called hoaxes. One of the hoaxes that is also widely circulated through social media is the hoax about Covid-19. The more widespread the trend of hoaxes that poison the news, especially on social media, ideas have also emerged to take preventive measures against the spread of hoax news. This study will focus on detecting hoax content circulating on social media Twitter and Facebook regarding Covid-19 using the nave Bayes algorithm and TF - IDF weighting. The data used is 2,480 data taken from Social Media Twitter and Facebook. The evaluation results show that the Naïve Bayes Classifier algorithm has a good performance level to identify hoax or non-hoax news with an accuracy of 89% in the first experiment, K-Fold Validation at 90.2% and in the third experiment at 95%.
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