ANALISIS SENTIMEN ULASAN PRODUK AMAZON MENGGUNAKAN ALGORITMA NAIVE BAYES UNTUK PREDIKSI RATING PRODUK
DOI:
https://doi.org/10.29407/3jgdj120Abstract
Perkembangan teknologi e-commerce seperti Amazon menghasilkan data ulasan produk yang sangat besar dan menjadi referensi utama bagi konsumen. Studi ini mengeksplorasi klasifikasi sentimen dari ulasan pengguna terhadap produk di platform Amazon, dengan pendekatan probabilistik Naive Bayes untuk mengidentifikasi hubungan antara kata-kata dan penilaian bintang. Data yang digunakan berasal dari dataset ulasan makanan premium Amazon yang mencakup lebih dari 500.000 ulasan. Metode penelitian melibatkan pra- pemrosesan teks, termasuk penghapusan stopwords, tokenisasi, dan stemming. Dengan menggunakan algoritma naive Bayes, dapat membuat klasifikasi sentimen yang lebih akurat. Hasil penelitian ini menunjukkan bahwa algoritma Naive Bayes dapat digunakan dengan baik untuk analisis sentimen. dalam jumlah besar dan dapat digunakan untuk sistem rekomendasi produk atau umpan balik konsumen di platform e-commerce.
Keywords:
Naive Bayes, Analisis Sentimen, Prediksi##plugins.themes.default.displayStats.downloads##
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