ANALISIS SENTIMEN ULASAN PRODUK SPEAKER BLUETOOTH PORTABLE DI SHOPEE MENGGUNAKAN NAIVE BAYES
Authors
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Nelgi Pinando
Program Studi Informatika, Fakultas Sains dan Teknologi, Universitas Nurul Huda
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Indra Lesmana
Program Studi Informatika, Fakultas Sains dan Teknologi, Universitas Nurul Huda
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Indra Susena
Program Studi Informatika, Fakultas Sains dan Teknologi, Universitas Nurul Huda
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Wardianto
Program Studi Informatika, Fakultas Sains dan Teknologi, Universitas Nurul Huda
Keywords:
Sentiment Analysis, Multinomial Naive Bayes, Bluetooth SpeakerAbstract
The e-commerce sector in Indonesia, particularly Shopee, contains vast consumer reviews for electronic products like portable Bluetooth speakers. These reviews are valuable but too numerous for manual analysis. This research applies the Multinomial Naive Bayes method to classify sentiment in these reviews. Using 3,021 data points from Kaggle, the research involved text preprocessing, rating-based labeling, TF-IDF feature extraction, and an 80:20 data split. Results show a global accuracy of 88.31%. However, the model exhibits bias toward the positive majority class, with low recall for negative and neutral classes due to data imbalance. Findings confirm text mining is effective for large-scale opinion mapping, but future research should utilize data balancing techniques or alternative algorithms to improve precision for minority classes.
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