To find the optimal ridge parameter for solving multicollinearity problem between the independent variables in binary logistic regression. This study scopes on 2 and 3 independent variables, low, medium and high correlations, Poisson Normal and Gamma distribution and which the logistic regression coeffcients, are 2,3, and 4, sample sizes are 40 and 70 for the two independent variables, 60 and 100 for the three independent variables. Simulating and analyzing data in this study use R 2.9.0 and PSS for Windows ver.19. The coefficient of logistic regression uses Newton-Raphson methods. Mean absolute pecentage error (MAPE) and standard deviation (SD) are the criteria for selecting the optimal ridge parameter. Studying under these assumptions can gain many useful results. In case of two and three independent variables, the results are the same. When we increase the correlation or the sample size, the value of ridge parameters are increase. If we consider on the increased percents of ridge parameter, the distributions that have the highest percent increased to the lowest percent are Gamma, Normal and Poisson distribution, respectively. On the other hand, when we consider from the view of the coefficient, the ridge paramenters are decreased. If we focus on the decreased percents of ridge parameter, the distributions that have the highest percent to the lowest percent are Gamma, Normal and Poisson distribution for the coefficients that equal 2 and 3, but when the coefficients are equal 4, the highest percent increased to the lowest are Normal, Gamma and Poisson distribution.
