Analisis Sentimen Ulasan Produk Sneakers Lokal Pada Tokopedia Menggunakan Algoritma Naïve Bayes dan Support Vector Machine
DOI:
https://doi.org/10.31599/5wew3w31Keywords:
Local Sneakers, Naive Bayes, Sentiment Analysis, Support Vector Machine, TokopediaAbstract
transformation in various sectors, including the fashion industry, especially sneakers. Sneakers are now a symbol of modern lifestyle and global trends, with brands such as Nike and Adidas dominating the market. However, high prices are an obstacle for many Indonesian consumers. This opens up opportunities for local brands to offer quality products at affordable prices through e-commerce such as Tokopedia, the second highest traffic platform in Indonesia. The research analyzed sentiment from 1,032 consumer reviews of local sneakers from five stores: NAH Project, Aerostreet, Geoff Max, Ventela, and Brodo. The analysis was conducted using Naïve Bayes and Support Vector Machine (SVM) algorithms. The SVM evaluation results produced the highest accuracy of 98%, compared to Naïve Bayes which reached 96%. This best model is implemented in a web-based application to analyze the sentiment of new reviews, to assess the perceived quality and consumer satisfaction of local sneakers products on Tokopedia.










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