Faktor–Faktor Yang Mempengaruhi Keputusan Nasabah Non-muslim Menabung Di Bank BNI Syariah Pekanbaru

This research is motivated by the large number of non-Muslim customers saving at Syariah Banks, especially at BNI Syariah Bank Pekanbaru. The formulation of the problem in this study is whether the marketing mix factor and the excellence factor of Islamic banks affect the decision of non-Muslim customers to save at BNI Syariah Pekanbaru bank. The population in this study is the non-Muslim customers of BNI Syariah Pekanbaru. The samples used were 93 samples. The sampling technique in this study with incidental sampling technique. The data collection method uses a questionnaire. Analysis of the data in this study is a quantitative analysis using multiple linear regression methods and the data is analyzed using the SPSS Version.23.0 program. Then an analysis of the data is performed. This analysis includes several tests: validity test, reliability test, classic assumption test, multiple linear regression analysis, hypothesis testing through t test and F test, as well as correlation coefficient, and coefficient of determination. The results of the study obtained by the multiple linear regression equation: Y = 5.197 + 0.233 X1 + 0.331 X2 + e. Where the marketing mix factor (X1), Bank Syariah excellence factor (X2) has a positive effect on customer decisions. The most dominant factor is the excellence factor of Islamic Banks (0.331) being the biggest factor influencing the decisions of non-Muslim customers. Hypothesis testing using the t test shows that the factors that influence the decision of non-Muslim customers to save are the marketing mix factor 2,144, and the excellence factor of Syariah Bank 3.048. Through the F test it is also known to have a significant effect seen from the calculated F value greater than Ftable (14,698> 3.10). Through the correlation coefficient that the independent variable with the dependent variable known R value of 0.496 or equivalent to 49.6% which means the interpretation is medium. Judging from the coefficient of determination that Figures Adjusted R Square of 0.229 indicates that 22.9% can be explained by the two independent variables in the multiple linear regression equation