Aspect-Based Sentiment Analysis of Hotels in Bali on Tripadvisor Using BERT Algorithm
DOI:
https://doi.org/10.25008/ijadis.v4i2.1284Keywords:
Aspect-Based Sentiment Analysis, ABSA, TripAdvisor, BERT, Deep learningAbstract
The covid pandemic that began in 2020 has caused enormous losses worldwide, including in Indonesia. Human-to-human contact is the source of the transmission of the covid virus, so the government urges people to maintain cleanliness when interacting. Bali is a popular destination for foreign and domestic visitors in Indonesia. Hospitality businesses in Bali unquestionably face a high risk of covid transmission; consequently, changes in hotel business processes are unavoidable; the implementation of new business processes can have a negative effect on business performance. In order to maintain Bali's reputation as the most popular tourist destination in Indonesia, the government must evaluate the performance of several hotel services that have implemented new business processes. The Aspect-Based Sentiment Analysis (ABSA) methodology can be utilized for performance evaluation. One of the finest algorithms for analyzing text, Bidirectional Encoder Representations from Transformer (BERT), is required for sentiment analysis. The data consists of textual customer evaluations of hotels in Bali that have implemented a new protocol or Standard Operational Procedure (SOP), retrieved from the Tripadvisor website. In the form of a number of evaluations of various aspects of the hotel, the research results can assist the government in analyzing the performance of hotels in Bali based on predetermined criteria.
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