REKOMENDASI DRAMA KOREA MENGGUNAKAN CONTENT-BASED FILTERING DENGAN WEIGHTED TREE SIMILARITY
DOI:
https://doi.org/10.23960/jitet.v13i1.6050Abstract Views: 475 File Views: 350
Abstract
Setiap tahun, ratusan drama Korea dirilis, menghadirkan tantangan bagi penonton untuk memilih tontonan yang sesuai dengan preferensi mereka. Fenomena Paradox of Choice menggambarkan bagaimana manusia cenderung bingung saat dihadapkan dengan banyak pilihan dan salah satu cara mengatasinya adalah dengan sistem rekomendasi yang dapat membantu pengguna dalam mempercepat pengambilan keputusan dan mencapai kenyamanan pengguna. Penelitian ini bertujuan membangun sistem rekomendasi drama Korea menggunakan metode Content Based Filtering (CBF) dengan algoritma Weighted Tree Similarity untuk membantu penonton memilih drama berdasarkan kesamaan konten. Model dikembangkan dengan pembobotan fitur, di mana screenwriter memiliki bobot tertinggi (6), diikuti synopsis (2), actor (1), dan director (1). Evaluasi model dilakukan menggunakan ground truth dari rekomendasi MyDramaList dengan metrik precision, recall, dan F1-score. Hasil evaluasi menunjukkan nilai precision 0,80 dan recall 0,75, dengan F1-score sebesar 0,774.Downloads
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