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Multiple Linear Regression Analysis Coefficient of Determination R

132

2. Multiple Linear Regression Analysis

Table 4.53 Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 Constant 5.749 2.415 2.381 .019 Customer Service .142 .053 .277 2.691 .008 Store Design and Display -.031 .067 -.045 -.459 .647 Communication Mix -.070 .072 -.096 -.966 .336 Location -.070 .060 -.114 -1.179 .242 Merchandise Assortment .240 .130 .188 1.850 .068 Pricing .483 .136 .351 3.560 .001 a. Dependent Variable: Customer Satisfaction Source : Processed primary Data by SPSS 1.7 Based on the table above, the regression equation is as follows: Y= 5.749 + 0.142X1 – 0.031X2 – 0.070X3 – 0.070X4 + 0.240X5 + 0.483X6 Description: Y = customer satisfaction dependent a = constanta X1 = customer service independent X2 = store design display independent 133 X3 = communication mix independent X4 = location independent X5 = merchandise assortment independent X6 = pricing independent Customer service variable X1 has regression coefficient 0.142 which means customer service has positive influence towards customer satisfaction variable Y. These appropriate with the previous research by Pasaribu and Sembiring in 2013 with the title The Effect of Retail Marketing Mix Strategi Towards Satisfaction and Loyalty of Customer at Syariah MES Mart Minimarket. They stated customer service has positive and significant influence towards customer satisfaction. Pricing variable X6 has regression coefficient 0.483 which means pricing has positive influence towards customer satisfaction variable Y. This appropriate with the previous research by Wijaya et al. uploaded in 2013 with the title The Analysis of Retail Mix Toward Customer Satisfaction in 39 Store Semarang. They stated pricing has positive influence towards customer satisfaction. The better pricing policy, it will increase customer satisfaction. 134

3. Coefficient of Determination R

2 Table 4.54 Source : Processed primary Data by SPSS 1.7 From the coefficient determinati on’s view from the table above adjusted R square is 0.246 or 24.6 it means all indepedent variable like service quality, product quality, and promotion, toward customer satisfaction have significant influence about 24.6. thus the residual coefficient , around 75.4 it will expalin by the other factors that is not calculated in this research. Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate 1 .540 a .292 .246 1.50285 a. Predictors: Constant, Pricing, Location, Store Design and Display, Merchandise Assortment, Communication Mix, Customer Service b. Dependent Variable: Customer Satisfaction 135

4. Partial Test T Test

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