Feedback analysis of service quality through data mining approach - Singgalen, Yerik Afrianto (Institute of Computer Science (IOCS), 2024)
This study explores the application of data mining techniques to analyze customer feedback for improving service quality at Tanjung Lesung Beach Hotel. Utilizing the Knowledge Discovery in Databases (KDD) framework, the research systematically collected, cleaned, and analyzed 1,239 customer reviews from the Agoda platform. Through a thorough data cleaning process, 642 verified reviews were identified as authentic, providing a robust dataset for in-depth analysis. Sentiment analysis was employed to extract key insights, revealing both positive aspects of the hotel experience, such as staff friendliness and beach amenities, as well as areas requiring improvement, particularly related to room conditions and breakfast offerings. Trend analysis indicated an upward trend in customer satisfaction from 2018 to 2023, with a minor decline observed in 2024, suggesting the need for ongoing service enhancements. The findings emphasize the critical role of leveraging verified customer feedback to inform strategic improvements, ultimately aiming to enhance guest satisfaction and maintain a competitive edge in the hospitality industry. This research contributes to the field by demonstrating how data-driven approaches can optimize service quality and align organizational strategies with evolving customer expectations