Analisis Sentimen Wisatawan Melalui Data Ulasan Candi Borobudur di Tripadvisor Menggunakan Algoritma Naïve Bayes Classifier

A high-accuracy sentiment analysis of visitor reviews at Borobudur Temple, using the Naïve Bayes Classifier (NBC), reveals key preferences and experiences that shape tourist satisfaction. The study, analyzing 3,850 Tripadvisor reviews, achieved a 96.36% accuracy rate, with notable precision in identifying positive sentiment. Key themes emerged around the temple's physical condition, scenic beauty, and sunrise visits, highlighting Borobudur as a premier cultural and natural destination. The research employed SMOTE upsampling to balance data and evaluate algorithm performance robustly, offering actionable insights for managers to align infrastructure with tourist expectations.

Singgalen, Y. A. (2022). Analisis Sentimen Wisatawan Melalui Data Ulasan Candi Borobudur di Tripadvisor Menggunakan Algoritma Naïve Bayes Classifier. Building of Informatics, Technology and Science (BITS), 4(3). https://doi.org/10.47065/bits.v4i3.2486