Group chat analysis of hoax detection during the covid-19 pandemic using the k nearest neighbors algorithm and massive text processing

Group chat is the most widely used choice of various short information. Besides being easy to send messages, sharing messages in group considered effective compared sending massively several users. The ease often as spread fake news and untrue or hoaxes, especially during Covid-19 pandemic, information shared can be easily by anyone without seeing a valid source. dissemination related clear source dangerous act, because it lead users into false endanger themselves. Fake message detectors have not been implemented instant applications, for this reason, there need detector machine analyze activities see whether included content containing not. If has lot news, you sure that good follow. use K-Nearest Neighbors algorithm quite classifying an object, results determined miss-information true news. process processing carried out massive text method characteristics are different each user so maximized later classification. As result, analyzed based on active time, activity, sent between