Analisis Sentimen Wisata Mentawai pada Media Sosial X menggunakan Algoritma Support Vector Machine (SVM)

Mulyani, Oktia Vita (2026) Analisis Sentimen Wisata Mentawai pada Media Sosial X menggunakan Algoritma Support Vector Machine (SVM). Skripsi thesis, Universitas Islam Negeri Imam Bonjol Padang.

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Abstract

This study aims to analyze public sentiment toward tourism in the Mentawai Islands on social media X using the Support Vector Machine (SVM) algorithm. The data were collected through crawling using Tweet Harvest from January 2021 to December 2025. After data preparation and relevance selection, 653 data related to Mentawai tourism were obtained. The data underwent preprocessing, sentiment labeling using lexicon-based and manual approaches, TF-IDF weighting, and SVM classification. Sentiments were classified into three categories: positive, negative, and neutral. Testing was conducted using data splitting ratios of 70:30, 80:20, and 90:10 and evaluated using accuracy, precision, recall, and F1-score. The results showed that the best model was obtained using manual labeling with an 80:20 data split, achieving an accuracy of 68.70%, precision of 69.31%, recall of 68.70%, and F1-score of 68.42%. The positive class achieved the highest F1-score of 72.73%, while the negative class obtained the lowest at 62.50%. Sentiment pattern analysis showed that positive discussions were mainly related to nature, beaches, waves, surfing, tourism, and Mentawai culture, while negative discussions reflected various issues related to Mentawai tourism. These results indicate that SVM can be used to classify public sentiment toward Mentawai tourism on social media X.

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