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OPTIMASI ALGORITMA DEEP NEURAL NETWORK MENGGUNAKAN INISIALISASI WEIGHT KAIMING HE UNTUK KLASIFIKASI PENYAKIT SERANGAN JANTUNG

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The Disease of the heart or cardiovascular organs is the number one cause of death in 17.7 million deaths in the world. Coronary Heart Disease (CHD) is increasing every year with a significant number of deaths. In Indonesia, the highest percentage of cardiovascular disease is coronary heart disease, coronary heart disease, which is 1.5 percent. The aim of this study is to minimize the expert diagnosis time and increase the accuracy of diagnosis. DNN is a neural network-based algorithm that can be used for decisions that have more than one hidden neural layer. This algorithm is the development of intelligence, namely the Artificial Neural Network (ANN) algorithm. To achieve high accuracy in this algorithm, the amount of data needs to be trained first. The accuracy of the system to be developed can be improved by adding a Kaiming He weight initialization optimization technique to the DNN structure. Therefore, this study proposes that DNN be optimized with a Kaiming He weight initialization technique so that it can increase the accuracy, sensitivity, and specificity values, and can overcome weaknesses in large data variants between classes. This is evidenced by the results of the accuracy performance of 98.73%, 99.21% precision, 99.11% sensitivity, and 98.36% specificity.

Availability
Inventory Code Barcode Call Number Location Status
2007000053T42988T429882020Central Library (REFERENSI)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T429882020
Publisher
Inderalaya : Prodi Magister Ilmu Komputer, Universitas Sriwijaya.,
Collation
x, 73 hlm, 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
005.12
Content Type
Text
Media Type
other
Carrier Type
-
Edition
-
Subject(s)
Pemograman Komputer
Magister Ilmu Komputer
Specific Detail Info
-
Statement of Responsibility
Other version/related

No other version available

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