Prediksi Diagnosis Hepatitis B Virus Menggunakan Gated Graph Neural Network
Abstract
Abstrak— Hepatitis merupakan infeksi virus pada hati dan dapat menyebabkan komplikasi terhadap penyakit lain yang dialami oleh pasien. Diagnosis dini dan penanganan yang tepat sangat penting untuk mencegah progresi penyakit dan komplikasi lebih lanjut.Diperlukan sebuah sistem prediksi diagnosis hepatitis yang akurat untuk menangani dan mengatasi kemungkinan terjangkitnya seseorang akan hepatitis. Penelitian ini melakukan prediksi model Gated Graph Neural Network terhadap pilihan data Hepatitis UCI Machine Learning Repository. Pada penelitian ini dilakukan pemodelan dan penelitian model dengan dua model graph neural network lainnya dan menghasilkan evaluasi yang baik pada prediksi klasifikasi node Hepatitis, dengan menggunakan Gated Graph Neural Network model menunjukan nilai yang superior terhadap 2 metode lain yaitu GAT dan GCN. Dimana GGNN mendapatkan nilai Accuracy, Precision, dan Recall diatas 90%.
Kata Kunci: Hepatitis, Gated Graph Neural Network, Prediksi.
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