BibTex Citation Data :
@article{JSINBIS40, author = {Ikhthison Mekongga and Rahmat Gernowo and Aris Sugiharto}, title = {The Prediction of Bandwidth On Need Computer Network Through Artificial Neural Network Method of Backpropagation}, journal = {Jurnal Sistem Informasi Bisnis}, volume = {2}, number = {2}, year = {2012}, keywords = {}, abstract = { The need for bandwidth has been increasing recently. This is because the development of internet infrastructure is also increasing so that we need an economic and efficient provider system. This can be achieved through good planning and a proper system. The prediction of the bandwidth consumption is one of the factors that support the planning for an efficient internet service provider system. Bandwidth consumption is predicted using ANN. ANN is an information processing system which has similar characteristics as the biologic al neural network. ANN is chosen to predict the consumption of the bandwidth because ANN has good approachability to non-linearity. The variable used in ANN is the historical load data. A bandwidth consumption information system was built using neural networks with a backpropagation algorithm to make the use of bandwidth more efficient in the future both in the rental rate of the bandwidth and in the usage of the bandwidth. Keywords: Forecasting, Bandwidth, Backpropagation }, issn = {2502-2377}, pages = {098--107} doi = {10.21456/vol2iss2pp098-107}, url = {https://ejournal.undip.ac.id/index.php/jsinbis/article/view/40} }
Refworks Citation Data :
The need for bandwidth has been increasing recently. This is because the development of internet infrastructure is also increasing so that we need an economic and efficient provider system. This can be achieved through good planning and a proper system. The prediction of the bandwidth consumption is one of the factors that support the planning for an efficient internet service provider system. Bandwidth consumption is predicted using ANN. ANN is an information processing system which has similar characteristics as the biologic al neural network. ANN is chosen to predict the consumption of the bandwidth because ANN has good approachability to non-linearity. The variable used in ANN is the historical load data. A bandwidth consumption information system was built using neural networks with a backpropagation algorithm to make the use of bandwidth more efficient in the future both in the rental rate of the bandwidth and in the usage of the bandwidth.
Keywords: Forecasting, Bandwidth, Backpropagation
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