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All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Fikri, Hafid Akbar
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy

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Prediksi Harga Emas Dengan Algoritma Backpropagation Fikri, Hafid Akbar
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.582

Abstract

Artificial Neural Network Backpropagation is known as one of the methods that can calculate accurately in predicting. The algorithm used in this study is the Backpropagation algorithm, with gold price data as input data for training data. The price of gold is a separate issue in the market, as a precious metal that can be used for investment. Gold is also one of the main commodities that are in great demand by investors because it is considered profitable. Unlike the currency exchange rate, gold investment is for the long term. The price of gold continues to increase in the world market so that many investors are interested in investing in gold. In predicting the price of gold, an accurate method is needed to do so, because of that the author uses one of the prediction methods from ANN (Artificial Neural Networks) namely the Backpropagation Algorithm. This case study is secondary data that already exists. The input variables are open, high, low. The output of this gold price prediction is price. This bacpropagation training process uses Matlab R2015a software with network architecture with the MSE (Mean Square Error) result is 0.0034849.
Prediksi Harga Emas Dengan Algoritma Backpropagation Fikri, Hafid Akbar
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.582

Abstract

Artificial Neural Network Backpropagation is known as one of the methods that can calculate accurately in predicting. The algorithm used in this study is the Backpropagation algorithm, with gold price data as input data for training data. The price of gold is a separate issue in the market, as a precious metal that can be used for investment. Gold is also one of the main commodities that are in great demand by investors because it is considered profitable. Unlike the currency exchange rate, gold investment is for the long term. The price of gold continues to increase in the world market so that many investors are interested in investing in gold. In predicting the price of gold, an accurate method is needed to do so, because of that the author uses one of the prediction methods from ANN (Artificial Neural Networks) namely the Backpropagation Algorithm. This case study is secondary data that already exists. The input variables are open, high, low. The output of this gold price prediction is price. This bacpropagation training process uses Matlab R2015a software with network architecture with the MSE (Mean Square Error) result is 0.0034849.
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