2019
DOI: 10.24843/jmat.2019.v09.i01.p107
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Implementasi Model Fungsi Transfer dan Neural Network untuk Meramalkan Harga Penutupan Saham (Close Price)

Abstract: The multivariate forecasting model is a model of forecasting that takes into the causal relationship between a prediction factor with one or more independent variables. This study uses multivariate  forecasting model that are transfer function and neural network model. The transfer function and neural network model are used for forecasting of closing stock price data by considering the opening stock price data as the independent variable in the forecasting model. The data used in this study is the monthly clos… Show more

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“…If the number of hidden layers is too small, the training process is not easy to converge, which is likely to lead to invalid prediction results. If the number of hidden layers is too large, it will easily lead to slow convergence speed and poor fault tolerance, and the network will also record some personality characteristics of samples [18]. Therefore, the following formula can be used for comparison:…”
Section: Bp Nn Prediction Modelmentioning
confidence: 99%
“…If the number of hidden layers is too small, the training process is not easy to converge, which is likely to lead to invalid prediction results. If the number of hidden layers is too large, it will easily lead to slow convergence speed and poor fault tolerance, and the network will also record some personality characteristics of samples [18]. Therefore, the following formula can be used for comparison:…”
Section: Bp Nn Prediction Modelmentioning
confidence: 99%