Implementasi Algoritma Support Vector Learning Terhadap Analisis Sentimen Penggunaan Aplikasi Tiktok Shop Seller Center
Keywords:
E-commerce, SVM, Tiktok ShopAbstract
E-commerce is experiencing rapid growth in Indonesia, followed by the increasing popularity of the Tiktok Shop application. This research aims to conduct sentiment analysis on user reviews of the Tiktok Shop Seller Center application on the Google Play Store using the Support Vector Learning (SVM) method and Text Mining techniques. This research collects review data in Indonesian from May to July 2023. This data includes ratings, comment content and review dates. The sentiment analysis results allow grouping reviews into positive or negative, and SVM with various kernels (Linear, RBF, Polynomial, and Sigmoid) is used to classify the sentiment. This research has the potential to provide important insights into users' views of the Tiktok Shop Seller Center and contribute to the development of sentiment analysis in the context of e-commerce in Indonesia.
References
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Hasna, S. K. (2021). Analisis Sentimen Data Ulasan Menggunakan Algoritma Support Vector Learning (Studi Kasus: Aplikasi Ilflix). 17522136.
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