Model Recommender System untuk Personalisasi Pesan Dakwah Digital Berbasis AI dan Data Mining
Keywords:
Dakwah Digital, Recommender System, Artificial Intelligence, Data Mining, PersonalisasiAbstract
Pergeseran dakwah ke platform digital menimbulkan tantangan relevansi konten akibat keragaman audiens dan kelebihan informasi. Penelitian ini bertujuan mengembangkan dan mengevaluasi sistem rekomendasi berbasis Artificial Intelligence dan data mining untuk mempersonalisasi pesan dakwah. Metode kuantitatif diterapkan pada korpus 1.000 teks dakwah, membandingkan kinerja algoritma Content-Based Filtering dan Collaborative Filtering. Evaluasi menggunakan metrik Precision, Recall, F1-Score, serta survei terhadap 50 responden. Hasil menunjukkan model Collaborative Filtering (Precision = 0,82; F1-Score = 0,78) memiliki kinerja lebih tinggi dibandingkan Content-Based Filtering (Precision = 0,78; F1-Score = 0,75). Survei pengguna mengonfirmasi bahwa 82% responden merasa rekomendasi yang diberikan sesuai dengan kebutuhan personal mereka. Penelitian ini menyimpulkan bahwa sistem rekomendasi efektif meningkatkan relevansi dan personalisasi konten dakwah digital.
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Copyright (c) 2025 Riza Mirza, Khairuni Khairuni, Taufiq Taufiq, martunis@uinsuna.ac.id (Author)
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