Abstract

Every trader or investor in buying shares will always confused with the highly volatile stock price movements, this is causes traders or investors to be careful in choosing prices on when entering to buy shares. ARIMA price forecasting method is a forecasting method that traders and investors can use to help make decisions.This study is a descriptive study with a quantitative approach with the aim of analyzing, explaining, and concluding the analysis of price forecasting using the ARIMA (Autoregressive Integrated Moving Average) method on investment decisions in banking companies listed in the LQ45 index on the Indonesia Stock Exchange. The data collection technique in this study is documentation of the LQ45 Banking Index Stock Price on the Indonesian Stock Exchange.The results obtained in this study are that the model used in forecasting banking stock prices is the best model, the models include BBCA ARIMA (5.2.0), BBRI ARIMA (5.2.0), BMRI ARIMA (5.2, 0), BBNI ARIMA (2,2,0), and BBTN ARIMA (5,2,0). BBCA's share price decreased by -14.9%. BBRI's share price decreased by -5.8%. BMRI's share price decreased by -6.8%. BBNI's share price decreased by -58.5%. BBTN's share price decreased by -18.8%.106. Investors should not buy shares in banking stocks listed in the LQ45 index. This is because prices tend to fall and make investors suffer losses. However, if trading or investing in the near future, investors will buy shares of BBRI and BBTN companies, because within 1 month the shares will increase and investors or traders can get capital gains.

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