Sentiment Analysis of Visitors to Lake Kelimutu Ende using The Naïve Bayes Method

Nia Maharani (Program Studi Informatika, Institut Bisnis dan Teknologi Indonesia (INSTIKI))
I Dewa Putu Gede Wiyata Putra (Program Studi Bisnis Digital, Institut Bisnis dan Teknologi Indonesia (INSTIKI))
Elisabeth Berliana Arianti Rey (Program Studi Bisnis Digital, Institut Bisnis dan Teknologi Indonesia (INSTIKI))
I Gede Made Yudi Antara (Program Studi Rekayasa Sistem Komputer, Institut Bisnis dan Teknologi Indonesia (INSTIKI))

Jurnal Krisnadana
Vol 4 No 3 (2025): Jurnal Krisnadana May - July 2025

Sentiment analysis is the process of identifying and categorizing opinions expressed in a text to determine the attitude of the writer towards a particular topic, whether positive or negative. The data used in this study were collected from Twitter media and reviews related to Kelimutu Lake. The Naïve Bayes method was chosen because of its simplicity and effectiveness in text classification. The data collected was processed through several stages, namely crawling, Preprocessing consisting of Cleazing, case folding, tokenization, stemming, filtering, after which the data was trained using the Naïve Bayes method. The results showed that the majority of visitor reviews of Kelimutu Lake were positive, with the main factors influencing positive sentiment being the natural beauty and unique experiences offered by the lake. This study provides valuable insights for Kelimutu Lake tourist destination managers in understanding visitor perceptions and improving service quality based on the feedback provided. In addition, this study also shows that the Naïve Bayes method can be used effectively in sentiment analysis, which is positive 472 and negative 472. Where the analysis results obtained are balanced.