Made Dona Wahyu Aristana
Fakultas Teknologi dan Informatika, Program Studi Teknik Informatika, Institut Bisnis dan Teknologi Indonesia

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Trend Forecasting of the Top 3 Indonesian Bank Stocks Using the ARIMA Method I Gede Iwan Sudipa; Roni Riana; I Nyoman Tri Anindia Putra; Christina Purnama Yanti; Made Dona Wahyu Aristana
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2023): Article Research Volume 8 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12773

Abstract

The number of investors in Indonesia increases annually. This is due to the growing popularity of investing, particularly stock investment. There are currently three largest equities in the banking industry, namely BBCA, BBRI, and BMRI. Stock prices fluctuate and form multiple patterns of price movements; therefore, investors must be able to recognize the patterns and trends of securities on the capital market in order to plan long-term investments, maximize potential profits, and reduce the risk of investment losses. In addition to knowing the trajectory of the stock market's trend, investors rely heavily on forecasting. Forecasting is necessary so that investors can anticipate future prices. The Autoregressive Integrated Moving Average (ARIMA) method is a frequently used method for forecasting time series data. In general, ARIMA is represented by the formula ARIMA (p, d, q), where p represents the Autoregressive (AR) order, d represents the difference, and q represents the Moving Average (MA) order. The trend of BBCA, BBRI, and BMRI stock data was effectively predicted using the ARIMA method. The results of this study are presented as diagrams of actual and forecasted data for the next 12 periods, as well as predictions of the optimal purchase price points for stocks. The ARIMA model of each stock also generates a low MAPE error value, with MAPE values of 4% for BBCA, 5% for BBRI, and 7% for BMRI. The MAPE value derived by each model is incorporated into the MAPE value with a high degree of precision, as it falls below 10%.