Analisis Sentimen Review Film Pada Website Rotten Tomatoes Menggunakan Metode Svm Dengan Mengimplementasikan Fitur Extraction Word2vec
DOI:
https://doi.org/10.34818/eoe.v9i3.18150Abstract
Abstrak Berkembang pesatnya teknologi jaringan internet menyebabkan masyarakat lebih mudah dalam mengakses berbagai macam film yang ingin mereka tonton. Berkaitan dengan hal tersebut, ulasan film menjadi salah satu yang paling penting untuk diperhatikan dalam industri film. Hal ini didasari karena berdasarkan ulasan penonton dapat diketahui tingkat kepuasan mereka terhadap film yang telah mereka saksikan. Analisis Sentiment adalah salah satu solusi bidang penelitian yang berbasis teks yang cocok untuk membahas masalah kepuasan berdasarkan ulasan penonton film. Analisis yang dilakukan didasarkan pada kelas ulasan positif dan negatif yang diberikan oleh pengguna. Dalam penelitian ini, permasalahan tersebut diselesaikan menggunakan metode Support Vector Machine (SVM) dan Word2Vec. Data yang diambil dari website Rotten Tomatoes menggunakan bahasa inggris yang sudah diolah dan diberi label. Model terbaik dari penelitian ini dengan menggunakan kernel RBF dengan menggunakan K-Fold menghasilkan rata – rata precission sebesar 77,2%, recall 68,2%, F1-Score 70,2% dan accuracy 79,0% Kata Kunci: analisis sentimen, SVM, word2vec, ulasan, RBFReferences
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