Klasifikasi Sentimen Ulasan pada Layanan Service HP dengan TF-IDF dan Naive Bayes
DOI:
https://doi.org/10.29407/ba2s1y27Abstract
Penelitian ini bertujuan untuk mengklasifikasikan sentimen ulasan layanan service HP menggunakan metode Naive Bayes dengan pembobotan TF-IDF. Banyaknya ulasan pelanggan serta keterbatasan analisis manual mendorong perlunya metode otomatis untuk mengetahui kecenderungan sentimen pengguna. Data penelitian diperoleh melalui proses scraping sebanyak 747 ulasan menggunakan bahasa pemrograman Python dan library SerpApi. Tahapan penelitian meliputi preprocessing data, pelabelan sentimen menggunakan metode lexicon-based, pembobotan fitur menggunakan TF-IDF, dan klasifikasi menggunakan algoritma Naive Bayes dengan pembagian data sebesar 80% data latih dan 20% data uji. Hasil pengujian menunjukkan bahwa model memperoleh nilai accuracy sebesar 85%, precision tertinggi sebesar 0,91 pada kelas sentimen negatif, recall tertinggi sebesar 0,98 pada kelas sentimen positif, dan F1-Score tertinggi sebesar 0,88. Hasil penelitian menunjukkan bahwa kombinasi TF-IDF dan Naive Bayes mampu mengklasifikasikan sentimen ulasan layanan service HP dengan baik.
Keywords:
Analisis Sentimen, Naive Bayes, TF-IDF, Service HP, Ulasan Pelanggan##plugins.themes.default.displayStats.downloads##
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