Image of KLASIFIKASI PENYAKIT JANTUNG BERBASIS CONVOLUTIONAL NEURAL NETWORK MENGGUNAKAN BASIS DATA THE PHYSIKALISCH-TECHNISCHE BUNDESANSTALT-XL (PTB-XL)

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KLASIFIKASI PENYAKIT JANTUNG BERBASIS CONVOLUTIONAL NEURAL NETWORK MENGGUNAKAN BASIS DATA THE PHYSIKALISCH-TECHNISCHE BUNDESANSTALT-XL (PTB-XL)

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Heart disease is one of the leading causes of death worldwide and can be identified based on the patterns of electrical activity in the heart using an Electrocardiogram (ECG). The importance of early detection and classification of heart disease has led to the use of innovative methods, such as Convolutional Neural Networks (CNN). The PTB-XL ECG data has been processed and prepared to train and test the CNN model. This deep learning approach aims to recognize characteristic patterns in ECG signals that indicate specific types of heart disease.In this research, the CNN network structure was optimized and designe, and then trained using the PTB-XL ECG data. The research was divided into several models, and the best model was obtained. The experimental results showed that the best model achieved an accuracy of 86.86%, sensitivity of 75.28%, specificity of 75.28%, precision of 83.56%, F1 Score of 75.25%, and an error of 13.14%.

Availability
Inventory Code Barcode Call Number Location Status
2307005017T126223T1262232023Central Library (Referens)Available
Detail Information
Series Title
-
Call Number
T1262232023
Publisher
Indralaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya.,
Collation
xvi, 100 hlm.; Ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
004.650 7
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Jurusan Sistem Komputer
Networks
Specific Detail Info
-
Statement of Responsibility
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No other version available

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