Sentiment Analysis Using Text Mining of Indonesia Tourism Reviews via Social Media

Dini Turipanam Alamanda∗, Abdullah Ramdhani, Ikeu Kania, Wati Susilawati and Egi Septian Hadi
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Dini Turipanam Alamanda∗: Garut University, Garut, Indonesia
Abdullah Ramdhani: Garut University, Garut, Indonesia
Ikeu Kania: Garut University, Garut, Indonesia
Wati Susilawati: Garut University, Garut, Indonesia
Egi Septian Hadi: Garut University, Garut, Indonesia

International Journal of Humanities, Arts and Social Sciences, 2019, vol. 5, issue 2, 72-82

Abstract: The Indonesian tourism industry continues to develop and has become the core of the nation’ economy. Indonesia is known for its wealth of natural beauty, which can be used as a potential for tourism business. Garut is a city in Indonesia known for its beach, mountains, and culinary arts. The purpose of this study is to create a priority map of tourist attractions that can be utilized by local governments. Sentiment analysis was used 413,175 netizen comments via the social media platforms Instagram and Google reviews. Data was collected from January 2018-February 2019. The results show that the number of positive comments is significantly higher than the number of negative comments. Beach tourism a serious priority; not only is it the most preferred tourist attraction, but also the type that gets the most negative comments. While the main problem for Garut Regency tourism is hygiene, garbage is either overlapping or scattered, preventing Garut from having all-around tourism charm instead of being superior only in the sector of natural beauty. The suggestions in this research can be used as proposals for improving and developing tourism to realize a dignified ‘Garut Charm’.

Keywords: Tourism; tourism development; text mining; sentiment analysis (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:apa:ijhass:2019:p:72-82

DOI: 10.20469/ijhss.5.10004-2

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