DLNN dan BPNN-GA Pada Prediksi Penyakit Diabetes di Bojonegoro
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https://doi.org/10.32665/james.v6i1.416Keywords:
Diabetes, Deep Learning Neural Network, Backpropagation Neural Network, Genetic AlgorithmAbstract
Diabetes terjadi ketika kadar gula darah lebih tinggi dari biasanya. Di sisi lain, produksi insulin dianggap tidak mencukupi. telah dicatat dalam beberapa hari terakhir bahwa pangsa pasien yang menderita diabetes telah meningkat ke tingkat yang lebih besar di seluruh dunia. Masalah ini harus ditanggapi lebih serius untuk memastikan bahwa persentase tipikal orang yang menderita diabetes berkurang. Penelitian ini bertujuan untuk mendeteksi lebih dini penyakit diabetes khususnya di Bojonegoro dengan cara memprediksi penyakit tersebut, sehingga dapat mengurangi penderita penyakit diabetes. Digunakan 2 metode dalam penelitian ini, yaitu Deep Learning Neural Network (DLNN) dan menggunakan metode optimasi bobot pada pelatihan Backpropagation Neural Network (BPNN) dengan Algoritma Genetika (GA) (BPNNGA) untuk memprediksi diabetes di Bojonegoro. Hasil penelitian ini menyajikan bahwa dengan menggunakan metode DLNN dan BPNNGA menghasilkan tingkat akurasi sebesar 94%.
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