期刊名称：International Journal of Computer and Information Technology
印刷版ISSN：2279-0764
出版年度：2021
卷号：10
期号：5
页码：1-9
语种：English
出版社：International Journal of Computer and Information Technology
摘要：The stock price changes at any time within seconds. The stock price is a time series data. Thus, it is necessary to have the best analysis model in predicting the stock price to make decisions to avoid losses in investing. In this research, the method used two models Deep Learning namely Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) in predicting Indonesia Composite Stock Price Index (IHSG). The dataset used is historical data from the Jakarta Composite Index (^JKSE) stock price in 2013-2020 obtained through Yahoo Finance. The results suggest that Deep learning methods with LSTM and GRU models can predict Indonesia Composite Stock Price Index (IHSG). Based on the test results obtained RMSE value of 71.28959454502723 with an accuracy rate of 92.39% for LSTM models and obtained RMSE value of 70.61870739073838 with an accuracy rate of 96.77% on GRU models.
关键词：Composite Stock Price Index (IHSG);Deep learning;GRU;Jakarta Composite Index (^JKSE);LSTM;predicting;stock p
