Diversity Balancing pada Two-stage Collaborative Filtering untuk Mengatur Less Popular Item dalam Domain Film
Abstract
Abstrak-Sistem pemberi rekomendasi film adalah sistem yang bertanggung jawab untuk memberikan rekomendasi kepada penonton film tentang judul film lain yang relevan, menarik, dan mungkin disukai oleh penonton. Salah satu metode yang paling sering digunakan pada system pemberi rekomendasi adalah Collaborative Filtering (CF). CF unggul dalam tingkat accuracy terhadap item yang direkomendasikan kepada pengguna meskipun dalam keadaan konten yang sulit dianalisis sekalipun. Kelemahannya, CF hanya merekomendasikan item yang populer saja. Maka karena itu, dibutuhkan system pemberi rekomendasi yang dapat memberikan rekomendasi item yang kurang popular dengan tingkat accuracy yang masih dapat diterima. Tugas akhir ini mengusulkan sistem pemberi rekomendasi film berbasis Two-stages CF dengan menggunakan metode Diversity Balancing. Sistem ini bekerja dengan memprediksi rating pengguna kemudian menghasilkan daftar kandidat untuk selanjutnya dilakukan Diversity Balancing. Diversity Balancing dilakukan dengan cara mengganti item yang populer dengan item yang kurang populer namun relevan. Hasil pengujian dengan metode precision, recall, personal diversity dan aggregate diversity menunjukkan nilai tertinggi masing-masing adalah 0.8000, 0.5366, 0.5301. 0.3709. Berdasarkan hasil tersebut didapatkan keseimbangan antara accuracy dan diversity di parameter k=7 dan threshold rating sebesar 3.0.
Kata kunci-sistem pemberi rekomendasi, collaborative filtering, diversity, less popular item
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