Jurnal ELTIKOM · 2018 · 10 citations · 7 references
ComputingComputer ScienceFinanceArtificial IntelligenceForecastingMachine LearningGradient-based OptimizationNeural NetworksTime Series ForecastingTime Series PredictionBackpropagationNeural ForecastingNeural Network PredictionPrecious Metals MarketsPredictive Price Modeling
Artificial Neural Network Backpropagation is known as one of the most reliable methods of predicting. The algorithm used in this research is Conjugate Gradient algorithm, with gold data data of input data for training data. The price of gold becomes an issue in the market, as a precious metal that can be used for investment is very interesting to make a gold price prediction application. Gold prices continue to increase in the world market, making investors interested to invest in this precious metal. The application of gold price prediction will be very useful for investors of precious metals. Gold price data used in this research is daily data, taken 3 (three) last year and divided into test data and data testing. Test data is used to generate new weights for data testing. The parameters used in the measurement of evaluation of predicted results from Conjugate Gradient algorithm Artificial Neural Network Backpropagation method is Meant Square Error (MSE), where the result of MSE from this research is 0.0313651
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