Analisis Sentimen Ulasan Wisatawan Terhadap Destinasi Gili di KLU Menggunakan K-Means Clustering - Obenu, Juanri Priskila; Suta Wijaya, I Gede Pasek; Bimantoro, Fitri (JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya), 2025)
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.