Image of KLASIFIKASI MULTICLASS SINYAL ELEKTROKARDIOGRAM BERBASIS DEEP LEARNING MENGGUNAKAN DENOISING AUTOENCODER DAN CONVOLUTIONAL NEURAL NETWORK

Skripsi

KLASIFIKASI MULTICLASS SINYAL ELEKTROKARDIOGRAM BERBASIS DEEP LEARNING MENGGUNAKAN DENOISING AUTOENCODER DAN CONVOLUTIONAL NEURAL NETWORK

Penilaian

0,0

dari 5
Penilaian anda saat ini :  

The use of Deep Learning (DL) models in signal processing aims to improve efficiency and effectiveness in extracting information from available data. This research aims to classify heart disease classes in a dataset of medical signals derived from Electrocardiograms. In this study, classification is performed on three heart disease classes: Normal, AF, and AFL. The method used in this research is Denoising Autoencoder, which reduces noise in the dataset, and Convolutional Neural Network (CNN), used for the classification process. The constructed model will be trained and validated with 9,222 signal recordings and tested with 1,025 signal recordings. The best results obtained for the 2-class classification model have average values of Accuracy 97.09%, Sensitivity 95.54%, Specificity 95.54%, Precision 94.40%, F1 Score 94.92%, and Error 2.90%. While for the 3-class classification model, the average values are Accuracy 97.22%, Sensitivity 93.56%, Specificity 96.93%, Precision 92.98%, F1 Score 93.24%, and Error 2.78%. Meanwhile, the best result when tested using unseen data, the model achieves accuracy values of 66.34% for the Normal class, 68.68% for the AF class, and 93.17% for the AFL class.

Availability
Inventory Code Barcode Call Number Location Status
2307002714T115844T1158442023Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1158442023
Publisher
Inderalaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya.,
Collation
xiv, 50 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
004.650 7
Content Type
Text
Media Type
unmediated
Carrier Type
-
Edition
-
Subject(s)
Jurusan Sistem Komputer
Jaringan Komunikasi Komputer
Specific Detail Info
-
Statement of Responsibility
Other version/related

No other version available

File Attachment
Comments
You must be logged in to post a comment