Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
Volume 13 Issue 1 April 2025

Perbandingan Akurasi Metode Autoregressive Integrated Moving Average dan Geometric Brownian Motion untuk Peramalan Harga Saham Indonesia

Hamdani, Aldan Maulana (Unknown)
Widhiatmoko, Fery (Unknown)
Fitri, Sa'adatul (Unknown)



Article Info

Publish Date
03 Apr 2025

Abstract

Investment is an activity of managing sources of funds with the goal of increasing profits within a certain period of time. The number of investors in the capital market, especially stock investments continue to increase. Stock movements result in returns that investors can obtain. Randomly fluctuating share prices make it difficult for investors to forecast share prices. This research helps investors in forecasting stock price movements based on PT. Gudang Garam Tbk. (GGRM) for the period 2022. This research aims to determine the level accuracy of the Geometric Brownian Motion (GBM) and Autoregressive Integrated Moving Average (ARIMA) methods in forecasting stock price movements. The accuracy level of the Mean Absolute Percentage Error (MAPE) for the GBM method is 1.68% and the ARIMA method forecasting results is 3.37%. The MAPE value of both methods is less than 10\%, so it can be said that both methods are best fitting and have a high level of accuracy in forecasting stock price movements. The GBM method is better at forecasting stock prices because it is more realistic for financial asset price models because it includes volatility in the model.

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Journal Info

Abbrev

Euler

Publisher

Subject

Computer Science & IT Mathematics

Description

Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi is a national journal intended as a communication forum for mathematicians and other scientists from many practitioners who use mathematics in the research. Euler disseminates new research results in all areas of mathematics and their ...