@inproceedings{cc09243821d74b8fa4727eecb4397511,
title = "Sentiment analysis of restaurant customer reviews on tripadvisor using na{\"i}ve bayes",
abstract = "Sentiment analysis is one method for classifying documents to identify positive or negative opinions. Customer satisfaction has an essential point for customer service. Customer behaviour is currently doing a lot of reviews in online media such as on trip advisor. A restaurant is a business that requires more attention in the service to consumers by improving service to customers continuously. This study tries to classify Surabaya restaurant customer satisfaction using Na{\"i}ve Bayes. Data sampling is crawling by using WebHarvy Tools. The result from this research shows that these two methods get the customer response accurately and Na{\"i}ve Bayes method is more accurate than TextBlob sentiment analysis with a different accuracy of 2.9%.",
keywords = "Customer satisfaction, Na{\"i}ve Bayes, Sentiment analysis, TextBlob",
author = "Laksono, {Rachmawan Adi} and Sungkono, {Kelly Rossa} and Riyanarto Sarno and Wahyuni, {Cahyaningtyas Sekar}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 12th International Conference on Information and Communication Technology and Systems, ICTS 2019 ; Conference date: 18-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ICTS.2019.8850982",
language = "English",
series = "Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "49--54",
booktitle = "Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019",
address = "United States",
}