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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA
Lia Andiani
Universitas Sriwijaya, Palembang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Klasifikasi Coronary Heart Disease (CHD) Berbasis Optimasi DNN dan Inisialisasi Kaiming He Lia Andiani; Sukemi Sukemi; Dian Palupi; Nurul Afifah
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2559

Abstract

CHD is chest pain or discomfort that occurs if the area of the heart muscle does not get enough oxygen-rich blood. CHD is also known as coronary artery disease. CHD is increasing every year with a significant number of deaths. A learning algorithm is proposed to get better performance in accuracy, sensitivity, and specificity in CHD interpretation. Accuracy can be improved by adding a Kaiming He (2015) weight initialization optimization technique to the DNN structure. Therefore we propose that DNN is optimized with a Kaiming He weight initialization technique so that it can overcome weaknesses in the data variant. This is evidenced by the results of the accuracy performance of 98.73%. Initialization of kaiming he weights is proven to improve accuracy and overcome the problem of large data variants between classes
Co-Authors Dian Palupi Sukemi Sukemi