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Arif Jumarwanto
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Electrical & Electronics Engineering

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APLIKASI JARINGAN SARAF TIRUAN BACKPROPAGATION UNTUK MEMPREDIKSI PENYAKIT THT DI RUMAH SAKIT MARDI RAHAYU KUDUS Jumarwanto, Arif; Hartanto, Rudi; Prastiyanto, Dhihik
Jurnal Teknik Elektro Vol 1, No 1 (2009): Jurnal Teknik Elektro
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Negeri Semarang

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Abstract

Artificial neural network (ANN) is a modern computing paradigm. That can be used for the pattern recognition and other. Backpropagation is artificial neural network which using hidden layer addition. Computation of artificial neural network through some certain step like training phase and examination. After both the step reached, so a neural network capable to recognize pattern to be entered will be found.The purpose of this research is simulation of artificial neural network that capable to pattern recognition from output of electrocardiogram by helped of MATLAB program. Input of result electrocardiogram record, then input of data can be normalization after that data can be proccesed by backpropagation computing with two step (training phase and examination phase). Output of ANN is like explaning condition of patient is normal, rhinitis kronis or epistaksis.Keyword : rhinitis kronis, epistaksis, artificial neural network.
APLIKASI JARINGAN SARAF TIRUAN BACKPROPAGATION UNTUK MEMPREDIKSI PENYAKIT THT DI RUMAH SAKIT MARDI RAHAYU KUDUS Jumarwanto, Arif; Hartanto, Rudi; Prastiyanto, Dhihik
Jurnal Teknik Elektro Vol 1, No 1 (2009): Jurnal Teknik Elektro
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jte.v1i1.1601

Abstract

Artificial neural network (ANN) is a modern computing paradigm. That can be used for the pattern recognition and other. Backpropagation is artificial neural network which using hidden layer addition. Computation of artificial neural network through some certain step like training phase and examination. After both the step reached, so a neural network capable to recognize pattern to be entered will be found.The purpose of this research is simulation of artificial neural network that capable to pattern recognition from output of electrocardiogram by helped of MATLAB program. Input of result electrocardiogram record, then input of data can be normalization after that data can be proccesed by backpropagation computing with two step (training phase and examination phase). Output of ANN is like explaning condition of patient is normal, rhinitis kronis or epistaksis.Keyword : rhinitis kronis, epistaksis, artificial neural network.
Co-Authors Dhihik Prastiyanto Rudi Hartanto