Abstract
The internet is a communication tool that we often use. The internet itself has brought many benefits. However, some people misuse it, for example, individuals or a group of people who spread hoaxes or fake news to incite and lead the publics’ opinions to their desired side. When COVID-19 spread in Indonesia and the government implemented mandatory vaccine obligations, the total of hoaxes on vaccination increased rapidly. Due to a large number of hoaxes on the Internet on COVID-19 vaccinations, As for several studies on the creation of a hoax detection system with various methods to try to overcome this problem, one of the studies with a system that detects hoax news and uses several methods, one of these methods is Levenshtein, getting a fairly low-performance result of 40% compared to other methods used. Therefore. Researchers are motivated to develop a hoax detection system with a similar method by adding Feature Extraction which aims to improve system performance from the previous research. In this study, 2 main experiments were conducted using Levenshtein distance as the main classification method, the results showed the best results in experiment-2 with an f1-score of 70.2% which was an increase compared to previous studies due to adding feature extraction using tf-idf.
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