Analisis Sentimen Review Pengunjung Pantai Pasir Putih Kabupaten Situbondo Menggunakan Metode Support Vector Machine (SVM)

Pangestu, Setia Nanda (2026) Analisis Sentimen Review Pengunjung Pantai Pasir Putih Kabupaten Situbondo Menggunakan Metode Support Vector Machine (SVM). Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

Managing visitor reviews on the Google Maps platform is a strategic step in evaluating the quality of tourism services. However, the large volume of review data often makes it difficult for manual analysis to accurately map visitor satisfaction levels. This study aims to conduct sentiment analysis of the Pasir Putih Beach tourist attraction in Situbondo using the Support Vector Machine (SVM) method. The dataset used consists of 1,848 reviews processed using the Term Frequency-Inverse Document Frequency (TF-IDF) weighting technique. Testing was carried out by dividing the data into training data and test data with a ratio of 90%:10%. The results showed that the SVM model was able to classify sentiment into positive, negative, and neutral categories with an accuracy level of 84%. This finding indicates a tendency for high satisfaction from tourists towards the Pasir Putih Beach tourist destination

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