INVESTMENT GOLD DURING THE COVID-19 PANDEMIC WITH LINEAR REGRESSION, NONLINEAR REGRESSION AND ARIMA - Tarigan, Enita Dewi; Yanti, Maulida; Hasibuan, Citra Dewi; Siringoringo, Yan Batara Putra; Erwin, Erwin (Journal of Mathematics, Computations and Statistics, 2025)
As a result of the COVID-19 pandemic, many individuals have turned to low-risk investment options. Common choices include gold, stocks, deposits, and foreign currencies, with gold emerging as a particularly popular investment. This study aims to forecast gold prices using linear regression, nonlinear regression, and ARIMA models, with the most accurate model determined by the lowest Mean Absolute Percentage Error (MAPE). Gold price data was sourced from www.kitco.com. The MAPE for the Linear Regression model was 4.362, the Nonlinear Regression model 3.3428, and the Time Series (ARIMA) model 2.727. Consequently, the ARIMA model demonstrated superior accuracy in forecasting gold prices compared to the Linear and Nonlinear Regression models.