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      "abstract": "Banyaknya pilihan buku digital di berbagai platform sering membuat pengguna\r\nkesulitan menemukan bacaan yang sesuai dengan minat dan kebutuhannya. Untuk\r\nmengatasi hal tersebut, dibutuhkan sistem yang mampu memberikan rekomendasi\r\nbuku secara otomatis berdasarkan kesamaan konten. Penelitian ini bertujuan untuk\r\nmenganalisis penerapan algoritma Extreme Gradient Boosting (XGBoost) pada\r\nmetode Content-Based Filtering dalam klasifikasi relevansi buku. Dataset yang\r\ndigunakan memuat informasi seperti judul, penulis, genre, dan deskripsi buku. Teks\r\ndari atribut tersebut direpresentasikan menggunakan metode TF-IDF (Term\r\nFrequency–Inverse Document Frequency), kemudian tingkat kemiripan antar buku\r\ndihitung menggunakan Cosine Similarity. Hasil pengukuran ini menjadi dasar\r\ndalam proses klasifikasi menggunakan XGBoost. Melalui pendekatan ini\r\ndiharapkan diperoleh hasil analisis yang akurat dan dapat menjadi acuan bagi\r\npengembangan sistem rekomendasi berbasis konten di masa mendatang.",
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        {
          "name": {
            "family": "Verawati",
            "given": "Ike",
            "honourific": null,
            "lineage": null
          }
        }
      ],
      "department": "Fakultas Ilmu Komputer",
      "eprintid": 33026,
      "subjects": [
        "000.000.005"
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      "date": "2026-05-21",
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