Klasifikasi Sentimen Wisatawan Candi Borobudur pada Situs TripAdvisor Menggunakan Support Vector Machine dan K-Nearest Neighbor

Rahayu Prihatini Saputri, Wiwiek Setya Winahju, Kartika Fithriasari
Submission Date: 2019-07-23 17:13:52
Accepted Date: 2020-02-04 00:00:00

Abstract


Candi Borobudur merupakan salah satu destinasi wisata di Indonesia yang telah dikenal hingga dunia internasional dan kini menjadi satu dari sepuluh destinasi prioritas yang ditetapkan oleh Kementerian Pariwisata. Oleh sebab itu pengelola wisata Candi Borobudur perlu memperhatikan berbagai persepsi wisatawan sebagai bagian dari proses evaluasi. Klasifikasi sentimen wisatawan berdasarkan data ulasan yang tersedia di situs TripAdvisor dilakukan dengan metode Support Vector Machine (SVM) dan K-Nearest Neighbor (K-NN), dengan penerapan teknik N-gram di kedua metode tersebut. Selain itu digunakan pula metode Synthetic Minority Oversampling Technique (SMOTE) untuk menangani kasus data imbalance. Hasil yang diperoleh dari penelitian ini adalah SVM kernel Radial Basis Function (RBF) dengan penerapan unigram merupakan metode terbaik untuk kasus klasifikasi sentimen wisatawan Candi Borobudur. Kinerja klasifikasi yang dihasilkan oleh metode tersebut tergolong sangat baik.

Keywords


K-Nearest Neighbor; N-gram; Sentimen; Synthetic Minority Oversampling Technique; Support Vector Machine

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