AI-BASED REVIEW ANALYSIS FOR SERVICE OPTIMIZATION AT V HOTEL AND RESIDENCE USING A PRE-TEST AND POST-TEST DESIGN

Abstract

This research examines the implementation of Artificial Intelligence (AI) for customer review analysis to improve service quality and products at V Hotel and Residence. Using a quantitative approach with pre-test and post-test design, the research was conducted over a 6-month period, comparing data from 3 months before and after AI implementation. The results showed significant improvements in various service aspects, including a 9.5% increase in overall rating, 66.7% reduction in complaint response time, and 14.6% increase in customer satisfaction. The AI system achieved 94% accuracy in identifying and categorizing customer reviews. Analysis based on SERVQUAL dimensions showed improvements across all aspects, with the highest increase in the empathy dimension (28%). AI implementation also positively impacted employee competency development with a technology adoption rate of 92%. The AI system integration resulted in improved operational efficiency in various aspects, including inventory management (42%), resource allocation (38%), and occupancy prediction (45%). This research provides empirical evidence of the effectiveness of AI implementation in improving hotel service quality and can serve as a reference for similar technology development in the hospitality industry.