Pengembangan Sistem Pendukung Keputusan Diagnosis Kanker Payudara Menggunakan Regresi Logistik
DOI:
https://doi.org/10.55382/jurnalpustakaai.v5i3.1344Keywords:
kanker payudara, sistem pendukung keputusan, regresi logistik, kalibrasi probabilitas, optimasi ambang batasAbstract
Kanker payudara merupakan salah satu penyebab kematian tertinggi pada wanita di Indonesia. Diagnosis yang akurat dan cepat sangat penting untuk meningkatkan tingkat kesembuhan pasien. Penelitian ini bertujuan mengembangkan sistem pendukung keputusan untuk diagnosis kanker payudara menggunakan model regresi logistik yang dioptimasi. Metode penelitian menggunakan dataset Wisconsin Diagnostic Breast Cancer yang terdiri dari 569 sampel dengan 30 fitur morfologis sel. Data dibagi menjadi 75% data latih dan 25% data uji. Model regresi logistik diimplementasikan dengan regularisasi L2 dan dievaluasi menggunakan analisis ROC, optimasi ambang batas dengan Indeks Youden, serta kalibrasi probabilitas menggunakan Expected Calibration Error (ECE). Hasil penelitian menunjukkan model mencapai akurasi 95,8%, sensitivitas 96,2%, dan spesifisitas 95,6% dengan nilai AUC-ROC 0,993. Optimasi ambang batas menghasilkan nilai optimal 0,560 yang menyeimbangkan sensitivitas dan spesifisitas. Kalibrasi probabilitas menunjukkan ECE sebesar 0,0390 yang dapat ditingkatkan menjadi 0,0328 menggunakan regresi isotonik.
Kata kunci: kanker payudara, sistem pendukung keputusan, regresi logistik, kalibrasi probabilitas, optimasi ambang batas
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Copyright (c) 2025 Rayendra, Ikhsan, Rozi Meri, Ismael, Dian Eka Putra, Rostam Ahmad Efendi, Riyan Ikhbal Salam
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