Penerapan TF-IDF dan Naive Bayes untuk Analisis Sentimen Ulasan pada Website NUQAR.COM
DOI:
https://doi.org/10.29407/rzr42625Abstract
Perkembangan teknologi digital mendorong perusahaan memanfaatkan platform online sebagai media pelayanan dan komunikasi dengan pelanggan. Penelitian ini bertujuan menganalisis sentimen ulasan pelanggan pada Nuqar.com menggunakan algoritma Naïve Bayes. Data penelitian berupa 836 ulasan pelanggan yang dikumpulkan selama tahun 2024. Tahapan penelitian meliputi pengumpulan data, pra-proses data, pelabelan sentimen, pembobotan kata menggunakan TF-IDF, klasifikasi, evaluasi, dan visualisasi. Pra-proses data terdiri dari case folding, tokenizing, stopword removal, dan stemming. Hasil pelabelan menunjukkan sentimen positif sebanyak 61,0%, netral 38,3%, dan negatif 0,7%. Berdasarkan evaluasi menggunakan confusion matrix, model memperoleh nilai accuracy sebesar 82%. Hasil tersebut menunjukkan bahwa algoritma Naïve Bayes mampu mengklasifikasikan sentimen ulasan pelanggan dengan cukup baik serta membantu perusahaan memahami persepsi pelanggan secara lebih efisien dan objektif..
Keywords:
Analisis Sentimen, Naïve Bayes, TF-IDF, Ulasan Pelanggan, Klasifikasi Teks##plugins.themes.default.displayStats.downloads##
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