PENERAPAN ELMAN RECURRENT NEURAL NETWORK UNTUK DIAGNOSIS GANGGUAN AUTIS PADA ANAK
Current developments in information technology has penetrated all sectors of life. Many problems in various sectors that require ease, speed and accuracy can be solved with the help of information technology. In the field of psychology, psychologists to help diagnose developmental disorders in child...
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| Main Authors: | , |
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| 格式: | Theses and Dissertations NonPeerReviewed |
| 出版: |
[Yogyakarta] : Universitas Gadjah Mada
2012
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| 主題: | |
| 在線閱讀: | https://repository.ugm.ac.id/97414/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=54275 |
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| 機構: | Universitas Gadjah Mada |
| 總結: | Current developments in information technology has penetrated all sectors
of life. Many problems in various sectors that require ease, speed and accuracy
can be solved with the help of information technology. In the field of psychology,
psychologists to help diagnose developmental disorders in children. This study
makes an artificial neural network applications to be able to diagnose autistic
disorder in children with Elman Recurrent Neural Network. This application is
created as a tool for diagnosing autistic disorder based on physical symptoms
suffered by the child.
Artificial neural network method used is the method of Elman Recurrent
Neural Network, which is an unsupervised learning. This software is created using
the Matlab programming language with MySQL database. The symptoms of
autistic disorder are used as input for the diagnosis consists of 48 variables.
This study uses 75 units of neurons in the hidden layer with the
assumption that the number of these errors reached the optimum (minimum error).
This configuration produces MSE 2.96 e-21 and the iteration process runtime 510
with 161.06 seconds and the learning rate is 0.025
Testing the neural network is working well, which reached 80.83% testing
accuracy. These results show that the network has been recognized by both the
pattern that has been drilled, although there are some data that do not fit with the
target. |
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