KLASIFIKASI PENYAKIT KANKER PAYUDARA MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN)
DOI:
https://doi.org/10.65244/jggengineering.v2i2.786Keywords:
kanker payudara, CNN, klasifikasi citra, MobileNetV3, skriningAbstract
Kanker payudara dapat menurunkan kualitas hidup sehingga diperlukan skrining yang cepat dan konsisten. Penelitian ini mengembangkan sistem klasifikasi kanker payudara berbasis Convolutional Neural Network (CNN) yang diimplementasikan pada aplikasi skrining berbasis web. Dataset disusun ke dalam data latih, validasi, dan uji, kemudian citra diproses melalui penyesuaian ukuran 224×224, normalisasi, serta augmentasi pada data latih. Model dibangun menggunakan arsitektur MobileNetV3 Small dengan keluaran tiga kelas, yaitu Normal, Benign, dan Malignant. Sistem juga menerapkan validasi input untuk memastikan prediksi hanya dilakukan pada citra jaringan payudara sebelum proses inferensi. Hasil pengujian pada 300 data uji menunjukkan akurasi sebesar 88,00% dengan performa per kelas yang bervariasi, di mana kesalahan klasifikasi masih terjadi pada kelas-kelas yang memiliki kemiripan ciri visual. Hasil ini menunjukkan CNN efektif untuk mendukung skrining awal kanker payudara dan dapat ditingkatkan melalui penambahan data serta optimasi pelatihan pada penelitian selanjutnya
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Copyright (c) 2026 Rosi Susanti, Dede Brahma Arianto (Author)
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