Analisis Sentimen Analisis Sentimen Publik Terhadap Pariwisata Aceh di Media Sosial X Menggunakan Algoritma Naive Bayes Classifier
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Susilawati Yahya
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Universitas Pembangunan Panca Budi Medan,
Indonesia
- Sri Wahyuni Universitas Pembangunan Panca Budi Medan , Indonesia
Abstract
Aceh has been synonymous with negative perceptions among people outside the province. This is due to the prolonged armed conflict and the devastating tsunami in 2004. Despite these challenges, Aceh possesses abundant potential for tourism, including natural attractions, historical sites, cultural arts, and religious tourism. However, negative perceptions continue to influence tourists' decisions to visit Aceh. Therefore, this study aims to analyze public sentiment or public opinion towards Aceh's tourism using the Naive Bayes algorithm on the X (Twitter) social media platform. Data for this study was collected from tweets on X (Twitter) using the keyword "Aceh tourism" and then underwent several data pre-processing stages to improve data quality, including text cleaning, case folding, word normalization, tokenization, stop word removal, and stemming. Afterward, the Naive Bayes algorithm was applied to classify tweet sentiment into positive and negative categories. Model evaluation was conducted using a confusion matrix, accuracy, and classification report. The results showed that Naive Bayes performed well in classifying public sentiment with an accuracy of 81%. This analysis indicates that public perception towards Aceh's tourism has begun to shift positively, presenting a promising opportunity for the future development of Aceh's tourism sector.
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