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      "abstract": "Seiring dengan meningkatnya penggunaan internet, ancaman serangan siber\r\nberupa URL phishing semakin berkembang dan berpotensi mencuri informasi\r\nsensitif pengguna. Untuk mengatasi permasalahan tersebut, pendekatan machine\r\nlearning dapat digunakan untuk mengklasifikasikan URL ke dalam kategori\r\nphishing dan legitimate. Penelitian ini bertujuan untuk meningkatkan performa\r\nalgoritma Decision Tree melalui penerapan metode ensemble learning berbasis\r\nboosting, yaitu Adaptive Boosting dan Gradient Boosting.\r\nDataset yang digunakan terdiri dari dua kelas yaitu phishing dan legitimate\r\nyang telah melalui tahap preprocessing dan transformasi ke dalam fitur numerik\r\nagar dapat diproses oleh model klasifikasi. Tahapan penelitian meliputi pembagian\r\ndata menjadi training, validasi, dan testing, proses pelatihan model, penyesuaian\r\nparameter seperti learning rate, serta evaluasi menggunakan metrik akurasi, presisi,\r\nrecall, dan F1-score.\r\nHasil penelitian menunjukkan bahwa model Decision Tree tanpa boosting\r\nmemperoleh akurasi sebesar 0,94 dengan nilai presisi, recall, dan F1-score sebesar\r\n0,94. Setelah diterapkan Adaptive Boosting, akurasi meningkat menjadi 0,97\r\ndengan peningkatan yang konsisten pada seluruh metrik evaluasi. Model Gradient\r\nBoosting juga menghasilkan akurasi sebesar 0,97 dengan performa evaluasi yang\r\nseimbang. Hasil ini menunjukkan bahwa metode boosting efektif dalam\r\nmeningkatkan akurasi dan kemampuan generalisasi Decision Tree dalam\r\nmendeteksi URL phishing.",
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      "title": "MODEL KLASIFIKASI URL PHISHING MENGGUNAKAN\r\nDECISION TREE DENGAN ADAPTIVE \r\nDAN GRADIENT BOOSTING",
      "rev_number": 15,
      "thesis_type": "bachelor",
      "department": "Fakultas Ilmu Komputer",
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      "keywords": "URL phishing, Decision Tree, Adaptive Boosting, Gradient\r\nBoosting, Machine Learning.",
      "date": "2026-02-25",
      "uri": "http:\/\/eprints.amikom.ac.id\/id\/eprint\/31862",
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            "lineage": null,
            "given": "Krisna Yogi",
            "family": "Saputra",
            "honourific": null
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