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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Alika, Zalfani
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Computer Science & IT Engineering

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Forecasting the Stock Price of PT Astra International Using the LSTM Method Nugraha, Edwin Setiawan; Alika, Zalfani; Amir Hamzah, Dadang
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 3 (2024): June 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i3.5699

Abstract

Stocks are one of the long-term investment options and represent ownership in a company that can be acquired through buying and selling. Investment carries both the profit potential and the risks that investors must face when providing their capital to companies. Accurate stock price forecasts are very important because they provide an estimate of risk. This research aims to forecast the stock price of PT Astra International Tbk (ASII.JK) using a Long Short-Term Memory (LSTM) method. Data set closing stock prices were taken from January 2, 2015, to December 30, 2020, with a total observation of 1506. This data set is divided into 80% for training and 20% for training. The forecasting results show that the best performances have MSE, MSE, MAE and MAPE are 151.910, 23076.561, 118.128, and 2.3%, respectively. The model has a batch size of 4 and epochs of 50. This research recommends that other parties consider this method when they need to manage their investment risk in stocks.
Co-Authors Hamzah, Dadang Amir Nugraha, Edwin Setiawan