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All Journal International Journal of Informatics and Computation
Rainbow Tambunan
Universitas Respati Yogyakarta
Computer Science & IT

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Robust Stock Price Prediction using Gated Recurrent Unit (GRU) Hamzah; Sugeng Winardi; Poly Endrayanto Eko Chrismawan; Rainbow Tambunan
International Journal of Informatics and Computation Vol. 5 No. 1 (2023): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v5i1.56

Abstract

Forecasting the direction of price movement of the stock market could yield significant profits. Traders use technical analysis, which is the study of price by scrutinizing past prices, to forecast the future price of the nickel stock price. Therefore, in this study, we propose Gated Recurrent Units (GRU) to predict nickel stock price trends. This research aims to produce an accurate nickel stock price trend prediction model. The research method utilized historical data on nickel stock prices from Yahoo Finance. The research results show that the model developed accurately predicted nickel stock price trends. From the RMSE, MAE, and MSE analysis results, the RMSE value was 0.0123, the MAE value was 0.0089, and the MSE value was 0.0002 on the test data.
Co-Authors Hamzah Poly Endrayanto Eko Chrismawan Sugeng Winardi