Abstract

TripAdvisor is an online platform where people can review tourist destinations. With so many reviews available, assessing public sentiment can be challenging. We conducted sentiment analysis on the review data from Indonesia's five most popular temples: Borobudur, Prambanan, Plaosan, Ijo, and Mendhut. Ratings on Tripadvisor reviews do not determine positive and negative sentences. Therefore, an automated method is necessary. Our research proposed using Lexicon-based and Stochastic Gradient Descent techniques for sentiment analysis. This study uses a lexicon-based because it can determine the weighting for the orientation of positive and negative sentiment words. SGD is used to build classification models because it can solve problems with large and complex datasets. The evaluation results showed that our method can significantly increase the model's performance. The result without a lexicon-based approach has an accuracy value of 70.3% while using a lexicon-based system improves the accuracy to 90.5%.

Original languageEnglish
Title of host publicationProceeding - International Conference on Information Technology and Computing 2023, ICITCOM 2023
EditorsHsing-Chung Chen, Cahya Damarjati, Christian Blum, Yessi Jusman, Siti Nurul Aqmariah Mohd Kanafiah, Waleed Ejaz
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages232-237
Number of pages6
ISBN (Electronic)9798350359633
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Information Technology and Computing, ICITCOM 2023 - Hybrid, Yogyakarta, Indonesia
Duration: 1 Dec 20232 Dec 2023

Publication series

NameProceeding - International Conference on Information Technology and Computing 2023, ICITCOM 2023

Conference

Conference2023 International Conference on Information Technology and Computing, ICITCOM 2023
Country/TerritoryIndonesia
CityHybrid, Yogyakarta
Period1/12/232/12/23

Keywords

  • Lexicon Based
  • Sentiment Analysis
  • Stochastic Gradient Descent

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