Analisis Sentimen Produk Sunscreen Pada Tokopedia Menggunakan Algoritma Klasifikasi Support Vector Machine
DOI:
https://doi.org/10.54367/kakifikom.v8i1.6879Keywords:
Analisis Sentimen, Support Vector Machine, TF-IDF, Sunscreen, SentimenAbstract
Perkembangan e-commerce di Indonesia meningkatkan jumlah ulasan konsumen yang dapat menjadi sumber informasi penting. Produk sunscreen merek Skintific di Tokopedia memperoleh banyak ulasan sehingga analisis manual menjadi tidak efisien. Penelitian ini bertujuan melakukan analisis sentimen terhadap ulasan konsumen dengan algoritma Support Vector Machine (SVM). Data dikumpulkan melalui web scraping dan diproses dengan tahapan preprocessing teks serta pembobotan TF-IDF. Model SVM dibangun untuk klasifikasi positif dan negatif, lalu dievaluasi menggunakan confusion matrix. Hasil penelitian menunjukkan SVM efektif dalam mengklasifikasikan ulasan dengan akurasi, presisi, recall, dan f1-score yang baik.References
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