Left branch bundle block (LBBB) detection system have been done and tested. The system created by using Artificial Neural Network (ANN). Some ANN methods have been investigated.  Electrocardiogram features that represent the characteristic of LBBB which were QR interval and RS interval used as input. Output of the system was electrocardiogram status to detect LBBB and normal beat. LBBB detection has been done with various input with QR interval, RS interval, QR and RS interval. Detection system have been tested using chlinical data and shown that MLP method gave the best performance. Its performance shown by sensitivity, specificity, and accuracy up to 99,92%, 100%, and 99,94% . Keywords: LBBB, artificial neural network, QR interval, RS interval

Published by Universitas Diponegoro
Journal Name BERKALA FISIKA
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Location Kota semarang, Jawa tengah INDONESIA
Website berkala_fisika| https://ejournal.undip.ac.id/index.php/berkala_fisika|
ISSN ISSN : -, EISSN : -, DOI : -,
Core Subject Science,
Meta Subject Physics,
Meta DescBERKALA FISIKA adalah jurnal saintifik yang diterbitkan secara periodik 3 bulanan. Jurnal ini memuat kajian-kajian Fisika baik kajian teoretik maupun hasil eksperimen. Jurnal ini juga memberi ruang yang luas bagi kajian – kajian aplikasi fisika dalam bidang teknologi, ilmu-ilmu hayati dan kedokteran.
PenulisPrimadyanie, Nistya Rischa , Nuryani, Nuryani , Purwanto, Hery , Yahya, Iwan , Lestari, Anik
Publisher ArticleBERKALA FISIKA
Subtitle Article BERKALA FISIKA 2014: Berkala Fisika Vol. 17 No. 3 Tahun 2014
Scholar Googlehttp://scholar.google.com/scholar?q=%2Bintitle%3A&…
View Articlehttps://ejournal.undip.ac.id/i…
DOIhttp://download.garuda.ristekdikti.…
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Download Article [2] http://download.garuda.ristekdikti.go.id…

 

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