The researchers used ridge regression analysis to solve the problem of multicollinearity in predicting hotel tax receipts in Indonesia in 2019. By adding a bias constant to the least squares method, they found a regression equation that better fits the data, with smaller VIF values compared to the traditional method. This approach helps improve the accuracy of predicting hotel tax receipts by considering multiple factors simultaneously.