dc.contributor.author | Sari, Yuslena | |
dc.date.accessioned | 2016-07-13T09:52:51Z | |
dc.date.available | 2016-07-13T09:52:51Z | |
dc.date.issued | 2016-06-01 | |
dc.identifier.issn | 2302-5581 | |
dc.identifier.uri | http://hdl.handle.net/123456789/901 | |
dc.description.abstract | This paper investigates the use of methods of propagation neural network to forecast the rupiah against the dollar in time
series . Data is divided into two parts , namely the training data test data . Having obtained the best weight training results
data then after that test data is used to see the results of MSE . Training algorithm uses basic backpropagation gradient
descent algorithm and then optimized using the conjugate gradient . The results show the value of the basic algorithm
backpropogation MSE gradient descent and conjugate gradient of 1.02159 mengsilkan MSE of 0.0198012 . From these
results indicate conjugate gradient algorithm produces smaller error. | en_US |
dc.language.iso | ina | en_US |
dc.publisher | LPPM Universitas Pelita Harapan Surabaya | en_US |
dc.relation.ispartofseries | Vol. 5 No. 1 Juni 2016; | |
dc.subject | Forecasting Rupiah | en_US |
dc.subject | Time Series | en_US |
dc.subject | Backpropagation | en_US |
dc.subject | MSE | en_US |
dc.title | Optimasi Conjugate Gradient Pada Algoritma Backpropagation Neural Network Untuk Prediksi Kurs Time Series | en_US |
dc.type | Journal | en_US |