Kurniawan, Angga2021-10-212021-10-212021-04wahyu sari yenihttps://repository.unri.ac.id/handle/123456789/10290Multiple linear regressions are analytical methods used to determine the relationship between a variable and another. One of the assumptions in multiple linear regression analysis is the absence of multicolinearity in the regression model. If there is a multicolinearity problem, there are several ways that can be used by using the ridge regression method which is a modification of the smallest squared method by adding the a bias constanta c. This study aims to suspect ridge regression parameters using Hoerl, Kennard & Baldwin and Lawless &Wang methods to address multicolinearity problems in the analysis of economic factors in Riau Province. The factors tested in this study are the oil and gas sector into gross regional domestic product commodities, other factors namely exports, consumer price index and rupiah exchange rate. In practice done by comparing two methods of bias rated values Hoerl, Kennard & Baldwin and metohods Lawless & Wang. . The study showed that there is at least one ridge regression method that has MSE, smaller and and value, adjusted larger than Hoerl Kennard & Baldwin method, is obtained Lawless & Wang ridge regression method with bias = 0,288.enMultiple linear regressionmulticolinearityridge regressionHoerl Kennard & Baldwin methodLawless & Wang methodArticle