Machine learning methods are very widely used in helping human work. Not all data is as we expected. Some data have missing values. Data that has a missing value must be handled first at the pre-processing stage, one of which is by the imputation of the missing value. This study is comparing the imputation method of missing value uses mode and One-Dimensional Naïve Bayes Classifier (1DNBC) to determine the performance analysis by using Support Vector Machine (SVM) for the prediction of car insurance participation. A better method is seen from the accuracy. Based on the simulation is obtained the same results for imputation using mode and One-Dimensional Naïve Bayes are 1.00, which when examined further turns out to be the imputation of each missing value with the mode and prediction of imputation with One-Dimensional Naïve Bayes are the same.