{
      "date": "2025-01-28",
      "corp_creators": [
        "Universitas AMIKOM Yogyakarta"
      ],
      "keywords": "kanker payudara, klasifikasi, Support Vector Machine, Decision\r\nTree, machine learning,  breast cancer, classification.",
      "rev_number": 15,
      "contributors": [
        {
          "name": {
            "lineage": null,
            "family": "Sulistiyono",
            "honourific": null,
            "given": "Mulia"
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        }
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          "name": {
            "given": "Guntur Tri",
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            "family": "Atmaja",
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      "abstract": "Kanker payudara merupakan salah satu jenis kanker yang paling umum diderita\r\noleh perempuan di seluruh dunia, dan deteksi dini sangat penting untuk\r\nmeningkatkan peluang kesembuhan. Namun, proses diagnosis yang masih\r\nkonvensional kerap membutuhkan waktu dan biaya yang tidak sedikit, serta rentan\r\nterhadap kesalahan interpretasi. Penelitian ini bertujuan untuk mengklasifikasikan\r\njenis kanker payudara menjadi jinak dan ganas secara otomatis menggunakan\r\nalgoritma machine learning, yaitu Support Vector Machine (SVM) dan Decision\r\nTree. Data yang digunakan berasal dari Breast Cancer Wisconsin Diagnostic\r\nDataset (WBCD), yang terdiri dari 569 data sampel dan 30 fitur numerik. Tahapan\r\npenelitian meliputi pengumpulan data, pra-pemrosesan (normalisasi dan pembagian\r\ndata latih-uji), implementasi model klasifikasi SVM dan Decision Tree, serta\r\nevaluasi kinerja dengan metrik akurasi, presisi, recall, F1-score, dan AUC. Hasil\r\npenelitian menunjukkan bahwa SVM memberikan performa lebih unggul dengan\r\nakurasi 98,25% dan AUC 99,37%, dibandingkan Decision Tree yang memiliki\r\nakurasi 92,11%. Penelitian ini memberikan kontribusi dalam pengembangan sistem\r\npendukung keputusan untuk deteksi kanker payudara secara lebih cepat, efisien,\r\ndan berbasis data. Hasil penelitian ini dapat dimanfaatkan oleh praktisi medis,\r\npengembang sistem kesehatan cerdas, maupun peneliti di bidang data mining dan\r\nbioinformatika.",
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      "title": "ANALISIS PERBANDINGAN ALGORITMA SUPPORT\r\nVECTOR MACHINE DAN DECISION TREE PADA\r\nKLASIFIKASI KANKER PAYUDARA",
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