Prediksi Harga Emas di Indonesia Menggunakan Gated Recurrent Unit - Handhayani, Teny; Tanudy, Clara; Hendryli, Janson (JURNAL FASILKOM, 2023)
Prediction system for the price of gold in Indonesia using a machine learning algorithm, namely the Gated Recurrent Unit (GRU), with influencing variables being the closing price of PT. Aneka Tambang's stock and the closing price of the US dollar exchange rate. The main objective of developing this system is to provide accurate and reliable information about the gold price trends for the next 7 days to the general public, investors, and other relevant parties. The dataset used consists of historical data for the closing prices of gold, the closing prices of PT. Aneka Tambang's stock, and the closing prices of the US dollar exchange rate, obtained from Yahoo Finance's website from January 2018 to October 2023. The dataset was pre-processed by extracting the dates from the three data sources used. In the results of training the GRU model for prediction, the best results were achieved with hyperparameters of 70% training data, 30% testing data, a timestep of 20, 50 epochs, and a batch size of 16, with an R-Squared value of 0.97, an MAE of 300.17, and an RMSE of 17.33. With the development of this system, it is expected to provide guidance for the general public, investors, and related parties in making timely decisions regarding gold purchases and to enhance their understanding of gold price movements in Indonesia.