An Analysis of Tourist Preferences For Luxury Resort Stays In Bali Based On Tripadvisor Reviews: A Big Data Perspective

Abstract

This study aims to analyze guest satisfaction trends at The Ubud Village Resort & Spa based on reviews from TripAdvisor using the time series ARIMA (AutoRegressive Integrated Moving Average) approach. The data used consists of historical customer ratings, analyzed to identify satisfaction trends and the factors contributing to rating fluctuations over time. The findings indicate that Sleep Quality and Cleanliness have lower ratings compared to other categories, highlighting the need for improvement to enhance the guest experience. Additionally, it was found that NONE travelers provided lower ratings than other customer categories, suggesting the necessity for more personalized service strategies to address this segment's needs. The time series analysis also reveals the presence of seasonal patterns in customer satisfaction levels, showing fluctuations in ratings based on specific periods. This study provides forecasts on future guest satisfaction trends, enabling hotel management to anticipate changes and develop more effective service improvement strategies. Based on these findings, strategic recommendations include enhancing sleep quality and cleanliness, improving services for lower-rated customer segments, and optimizing operational strategies based on seasonal patterns and ARIMA projections. This research insight for the company to improve guest satisfaction, maintain customer loyalty, and strengthen its positive reputation in the hospitality industry.