Recently, tourism villages are central to Indonesia’s tourism development strategy, contributing significantly to local, regional, and even national economic growth. With the increasing number of tourism villages, understanding tourists’ perspectives is essential for ensuring their sustainability. Tourist reviews on platforms provide valuable insights into their experiences and expectations. Sentiment analysis, widely used in tourism research, enables the extraction and identification of opinions from these unstructured data sources, offering a deeper understanding of visitor sentiments. This study employs Large Language Models (LLM) to analyze tourist reviews of Indonesian tourism villages. Unlike common methods, LLMs provide advanced capabilities for both sentiment analysis and the evaluation of the 4A tourism components—Attraction, Accessibility, Amenities, and Ancillary services. By examining positive, neutral, and negative reviews, the research identifies key factors that shape tourist experiences. The findings offer practical recommendations for tourism village managers, not only enhances visitor satisfaction but also supports the government’s goal of fostering economic growth in tourism and rural areas. The study demonstrates the potential of LLM-based sentiment analysis as a valuable tool for advancing Indonesia’s tourism industry.