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ANALISIS FUNGSI AKTIVASI JARINGAN SYARAF TIRUAN UNTUK MENDETEKSI KARAKTERISTIK BENTUK GELOMBANG SPEKTRA BABI DAN SAPI

Unisda Journal of Mathematics and Computer Science (UJMC)

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ISSN 2579-907X
2460-3333
 
Authentication Code dc
 
Title Statement ANALISIS FUNGSI AKTIVASI JARINGAN SYARAF TIRUAN UNTUK MENDETEKSI KARAKTERISTIK BENTUK GELOMBANG SPEKTRA BABI DAN SAPI
 
Added Entry - Uncontrolled Name Fauji, Shofwan Ali
Kusumastuti, Ari
Universitas Islam Darul 'Ulum Lamongan
UIN Maulana Malik Ibrahim Malang
 
Summary, etc. Artificial Neural Network (ANN) is beginning little by little to replace the task of an expert, even with the ANN can be a tool to replace a doctor. One of kind of ANN is backpropagation networks, this network can be used to training programs in order to be able to recognize whether it is pig or cow wave spectra. To determine the output in backpropagation training required suitable activation functions. Therefore, in this research will be compared to some of the activation function that can be used in training. Activation functions will be tested with the ratio test to determine the interval convergence. After tested with the ratio test it was found that the activation function tanh z was the best activation function to use the backpropagation network training, because it has a weight range that can meet the methods used in the determination of weights. When tested with the data, the activation function tanh z is able to recognize correctly all trial datas. An expected in future research to examine the weight that makes the interval training to achieve fast convergence and the error bit.
 
Publication, Distribution, Etc. Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan
 
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http://e-jurnal.unisda.ac.id/index.php/ujmc/article/view/437
 
Data Source Entry Unisda Journal of Mathematics and Computer Science (UJMC); Vol 1 No 01 (2015): Unisda Journal of Mathematics and Computer Science
 
Language Note eng
 
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