PERBANDINGAN PERFORMA PERAMALAN HARGA SAHAM 5 PERUSAHAAN PADA INDEKS LQ45 MENGGUNAKAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE DAN LONG SHORT - TERM MEMORY - Fajar Akbardipura, (2022)
In the era of the industrial revolution 4.0, technological developments are growing rapidly. Today's technology can be used to make predictions or forecasts. Stock price forecasting can be implemented by utilizing technology that is intended to predict data. In the world of stocks there are investors and traders. The type of trader targeted in this study is a swing trader who trades stocks on a daily or even monthly basis. The transaction of selling and buying shares by swing traders is quite difficult because there is a correction point that can hold you back from selling at the highest stock price point. Based on these problems, research was conducted using ARIMA and also LSTM to predict stock prices. Stock data using ANTM, ADRO, ICBP, KLBF, and TLKM from January 2021 - 2022 obtained from yahoo finance. The research process was carried out by knowing the problem, studying literature, collecting data, pre-processing data, creating an ARIMA plot model, normalizing data, testing the model, and evaluating the final comparison of the results of the two algorithms used in the study.