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Sentiment Analysis of Tourism Objects on Trip Advisor Using LSTM Method

Author

Listed:
  • Novita Hanafiah

    (Bina Nusantara University, Kebon Jeruk Raya street No. 27, West Jakarta, 11530, Indonesia)

  • Yanto Setiawan

    (Bina Nusantara University, Kebon Jeruk Raya street No. 27, West Jakarta, 11530, Indonesia)

  • Aldi Buntaran

    (Bina Nusantara University, Kebon Jeruk Raya street No. 27, West Jakarta, 11530, Indonesia)

  • Muhammad Reynaldi

    (Bina Nusantara University, Kebon Jeruk Raya street No. 27, West Jakarta, 11530, Indonesia)

Abstract

This study developed a sentiment analysis application for comments on tourist sites. It is used to help people who want to know about tourist attractions information to get positive or negative information. The method used to analyze the sentiment was LSTM. The determination of LSTM architecture consists of scraping data, manual labelling, preprocessing (case folding, removing punctuation, removing stopwords, tokenization, and lemmatization), word2index, word embedding, and LSTM layer. In order to achieve optimal accuracy, it is necessary to determine the right embedded method, the total number of layers for the dropout layer, and LSTM. The performance of this study showed that the accuracy and loss from sentiment analysis using the LSTM method were 96.71% and 14.22%.

Suggested Citation

  • Novita Hanafiah & Yanto Setiawan & Aldi Buntaran & Muhammad Reynaldi, 2022. "Sentiment Analysis of Tourism Objects on Trip Advisor Using LSTM Method," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 4(2), pages 01-06, July.
    • Handle: RePEc:alk:jcsts0:v:4:y:2022:i:2:id:3650
    DOI: 10.32996/jcsts.2022.4.2.1
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