In the
process of developing a forecasting model using MLR,
there are two main problems: multicollinearity and
correlated error terms. In this study, stepwise regression
is used in an attempt to remove the correlation between
the independent variables. The stepwise procedures had
successfully solved the problem of multicollinearity by
reducing the total number of independent variables to
four.