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      "date": "2026-02-24",
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      "abstract": "Perkembangan portal berita digital memudahkan akses informasi, namun\r\nmeningkatnya jumlah artikel menimbulkan masalah information overload sehingga\r\npengguna kesulitan menemukan berita yang sesuai. Selain itu, ketergantungan pada\r\nAPI pihak ketiga berpotensi menghambat keberlanjutan layanan dan optimalisasi\r\npengelolaan sistem. Oleh karena itu, penelitian ini merancang sistem portal berita\r\nberbasis web yang dikembangkan secara end-to-end, mencakup backend, basis\r\ndata, dan frontend.\r\nSistem dilengkapi dengan mekanisme rekomendasi berbasis konten\r\nmenggunakan metode content-based filtering dengan TF-IDF dan cosine similarity\r\nuntuk mengukur kemiripan antarartikel. Hasil penelitian menunjukkan bahwa\r\nsistem mampu menghasilkan rekomendasi berita yang relevan berdasarkan\r\nkesamaan konten tanpa bergantung pada data interaksi pengguna dalam jumlah\r\nbesar. Pendekatan ini dinilai efektif sebagai solusi awal sistem rekomendasi berita\r\ndan berpotensi dikembangkan lebih lanjut dengan metode yang lebih kompleks.",
      "type": "thesis",
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      "keywords": "portal berita, sistem rekomendasi, content-based filtering, TF-IDF,\r\ncosine similarity, ews portal, recommendation system.",
      "thesis_name": "skripsi",
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      "department": "Fakultas Ilmu Komputer",
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