Abstract
The rise of social media, particularly Twitter, has enabled sentiment analysis in tourism. This study examines tourist sentiments toward Gili, Lombok, using K-Means Clustering on 6,030 tweets, refined to 3,156 after cleaning. The clustering yielded Silhouette Coefficient scores of 0.4382 (positive-English), 0.4173 (positive-Indonesian), 0.4258 (negative-English), and 0.4535 (negative-Indonesian), indicating well-structured clusters. Tourists expressed positive views on natural beauty and activities but raised concerns about water supply issues. This study demonstrates K-Means Clustering’s effectiveness in revealing sentiment trends, offering valuable insights for local governments and tourism stakeholders to enhance visitor experiences and address challenges.
Concepts :
Citations by Year
| Year | Count |
|---|---|
| 2025 | 0 |