Sentiment Analysis of Tourism Objects on Trip Advisor Using LSTM Method

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%.