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Customers’ Satisfaction and Preferences Using Sentiment Analysis on Traveloka: The Case of Yogyakarta Special Region Hotels

The rapid development of internet use today shows a shift in technology that is increasingly leading to online-based media. Consumers tend to browse the completeness of product and service information via the internet by making purchases online because of limited time and perceived convenience. We analysed some of the features that hotel customers need using customer reviews. This study uses hotel customer reviews on the Traveloka website. The purpose of this study was to determine the important factors that influence tourists in choosing hotels based on hotel customer reviews. We use HBDScan algorithm and machine learning approaches to identify hotel customer segments. We found that the segmentation of tourist preferences and satisfaction is an important stage in behavioural analysis to improve the quality of hotel products and services. This analysis can improve the understanding of hotel managers about different market segments according to the level of customer preference and satisfaction. The findings of this study will help managers to set priority instructions for enhancing appropriate hotel features and use online customer reviews to improve customer satisfaction and hotel performance.