Social media in providing freedom of access to information has a rapid effect on tourist destinations in Indonesia. A tweet may also contain information or conditions about tourist destinations that they will or have visited, such as visitor experiences in traveling, visitors' opinions of tourist attractions, and other tourist attractions. The condition of tourism globally, especially in the Gunungkidul area after the Covid-19 pandemic, has experienced a significant decline. This condition motivated researchers to conduct research with the aim of contributing to post-Covid-19 tourism development, in particular by conducting a sentiment analysis of comments by tourists visiting tourist areas in Gunungkidul Regency. Sentiment analysis is the process of using text analytics to derive various data sources from the internet and various social media platforms. Comment data obtained through social media Twitter. This classification is used to find out how comments about tourist attractions in Gunungkidul are. Lexicon based and pivoting are methods used to classify public opinion into three classes, namely positive, negative and neutral sentiments. This method is used to classify the results of community comment data written on the form of community satisfaction with tourism in Gunungkidul. This study aims to find out how people's opinions regarding tourism in Gunungkidul during the Covid-19 pandemic took place. The results of this study are used to determine the classification of community commentary data so that services can be easily developed through comments given by the public. The results of the sentiment analysis show that there are 51% positive emotion categories, 1% negative and 48% neutral.
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