ANALISIS SENTIMEN TERHADAP ULASAN PADA WHIZ PRIME HOTEL SUDIRMAN PEKANBARU MENGGUNAKAN SUPPORT VECTOR MACHINE DAN NAIVE BAYES
DOI:
https://doi.org/10.31849/zn.v7i2.25888Keywords:
Analisis Sentimen, Support Vector Machine, Naive Bayes, Hotel, Machine LearningAbstract
Kemajuan teknologi informasi telah mengubah cara manusia menjalankan bisnis, termasuk dalam industri perhotelan melalui platform E-Commerce seperti Traveloka. Ulasan pelanggan menjadi sumber informasi penting yang dapat memengaruhi keputusan calon pelanggan. Penelitian ini menganalisis sentimen ulasan pelanggan terhadap Whiz Prime Hotel Sudirman Pekanbaru menggunakan algoritma Support Vector Machine (SVM) dan Naive Bayes. Data sebanyak 4336 ulasan dikumpulkan dari situs Traveloka, kemudian diproses menggunakan metode Term Frequency-Inverse Document Frequency (TF-IDF). Setelah tahap praproses, sebanyak 2165 ulasan dianalisis dengan hasil distribusi sentimen positif sebesar 72,79%, negatif 15,38%, dan netral 11,82%. Algoritma SVM menunjukkan akurasi tertinggi sebesar 77%, sementara Naive Bayes mencapai akurasi 73%. Hasil ini memberikan wawasan bagi pihak hotel untuk memahami kekuatan dan kelemahan layanan, sehingga dapat meningkatkan kepuasan pelanggan secara keseluruhan.
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