Sentiment Analysis of Airline Ticket and Hotel Booking of Traveloka Using Support Vector Machine

Digital information technology has penetrated most parts of the world, especially customer service. Internet support has made systems running in human life into digitalized activities, including, in this case, booking airline tickets and hotel bookings. One application that has been developing since 2012 is Traveloka. This study utilizes sentiment analysis to assess this application review via Twitter. The method used in this sentiment analysis is a support vector machine (SVM). This research aims to find the confusion matrix in the model resulting from the review of this application. These results are then used to create desktop-based applications. The evaluation results of the model show the accuracy, precision, recall, and F1-Score of 0.75, 0.67, 1, and 0.8, respectively.