Tag Archive for: Topic Modelling

The development of internet users in Indonesia continues to increase over time, this makes customers comfortable with digital transactions. Trinusa Travelindo Company or better known as Traveloka, which is engaged in the online travel agent sector, has proven its extraordinary achievement, namely becoming the E-tourism application that is ranked 1st most visited by the Indonesian people in 2022. However, these results are also directly proportional to the number of negative reviews created in the application review itself. This study aims to identify what issues affect customer satisfaction with topic modelling. This study uses the text mining method derived from the results of Traveloka application user reviews. The data source obtained in this study is secondary data by using the Traveloka application review data crawling technique with samples from January to May. Based on sentiment analysis, positive sentiment is more dominant (50.38%) compared to negative sentiment (49.62%). User reviews are grouped based on the results of sentiment analysis, then Topic Modelling is carried out to find out what issues affect customer satisfaction. The topic modelling of the data used is Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA) with the help of phyton 6.3. to find out what words and topics often appear or as factors that influence customer satisfaction. The most influential negative issues include the refund and payment process, pay later services, and the ordering experience which is considered complicated. On the other hand, issues that contribute positively to customer satisfaction include product quality, service quality, and promos and discounts. This is reinforced by the results of topic modelling which show that these aspects are often the main concerns in user reviews on the Google Play store. Thus, this study suggests that in order to increase customer satisfaction, Traveloka needs to focus on improving the quality of service, products, and offering more attractive promos, while simplifying the refund process and ordering experience in the application, some still say it is complicated