DOUW method is an outlier detection procedure which also can produce robust parameter estimation in Binary Logistic Regression. In DOUW method, there are four things that must be completed, namely: determination of optimal g1, the number of iterations, the choice of ? (weight), and the choice of c (level of cut-off). Source data used is the result of Inter-Census Population Survey (SUPAS) in 2005 in Sukabumi Regency and West Java Province. Variables used are as follows: Response Variable (Y) is a type of Marriage and Regressor Variables(Xi) are Religion (X1), Residence Status (X2), Working Status (X3), Migrant Status (X4), and the Old School (X5). From the results of outlier detection, choice of mate value of ? and c can be concluded that for certain ? value and the value of c is getting closer to one the number of observations that are detected as outliers more and more. While for certain c value and the ? value of getting closer to 0 then the number of observations that are detected as outliers less. Whereas, if viewed from the estimated parameters produced, it can be concluded that changes in the value of the estimated parameters in the regressor variables, from the initial iteration to iteration end, changing the very significance. From these results demonstrate that the presence of outliers greatly affect the estimated parameters are obtained, especially on binary logistic regression. Estimated parameters produced by DOUW method, for the pair ? and c value whatever, basically get the value that is not too much different, although the number of outliers that are detected are not the same.