This study aims to analyze the effect of inflation, interest rates, and exchange rates on the money supply using a quantitative approach with time series data from 2004–2023. The analytical method employed is multiple linear regression with second-order differencing transformation after conducting stationarity tests using the Augmented Dickey–Fuller (ADF) method. The results indicate that all variables are integrated at order two I(2), thus the model estimation is performed using second difference data to avoid spurious regression. The regression results show that partially inflation, interest rates, and exchange rates do not have a significant effect on the money supply at the 5% significance level. Simultaneously, these variables also do not significantly affect the money supply, as indicated by the F-statistic probability value of 0.2249. The coefficient of determination value of 0.2602 indicates that the model explains only about 26% of the variation in the money supply, while the remaining 74% is influenced by other variables outside the model. Classical assumption tests show that the model satisfies normality, homoscedasticity, no autocorrelation, and no multicollinearity assumptions. Therefore, the regression model is econometrically valid, although the independent variables have not been proven to be the main determinants of changes in the money supply.