KONTRIBUSI SALURAN DISTRIBUSI DAN PELAYANAN TERHADAP KEPUASAN PELANGGAN KARGO DI GARUDA INDONESIA

Abstract

This study aims to determine the relationship between distribution channels (delivery) and service (service) with customer satisfaction cargo PT. Garuda Indonesia. Population in this research is cargo agent that use Garuda cargo service at warehousing cargo at Cengkareng Airport.

The research method used was survey method until the research was 40 cargo agents taken using simple random technique, while the data analysis used was simple correlation and regression and double technique which was recommended with t and F test.

From the results of data analysis can be submitted as follows:

1. The first hypothesis proposed in this study states that the positive relationship between Channel Distribution (X1) with Customer Satisfaction (Y).

Calculation of simple regression analysis on the data variable Customer Satisfaction over Distribution channel yields regression b direction of 0.45 and a constant of 33.63. Thus the form of relationship between the two variables can be described by the regression equation Y = 33.63 + 0.45 X1.

The price of F regression is obtained at 8.325 while the Ftable price with the dk of the numerator 1 and the denominator 38 is at a significant 0.01 level of 7.35. It turns out that Fcount> Ftable, this shows that the regression coefficient of Y over X1 is significant at alpha = 0.01.

Based on result of significance test and linearity can be concluded that regression Y = 33,63 + 0,45 X1 significant and linear. This regression means that if the Distribution Channel increases 1 unit, then the tendency of Customer Satisfaction increases by 0.45 units at constant 33.63.

The strength of the relationship between Channel Distribution (X1) and Customer Satisfaction (Y) is shown by product moment correlation coefficient of ry1 = 0.424 Furthermore the significance test of correlation coefficient is done by student t test obtained by tcount 2,61.

Based on the results of significant tests it turns out that the correlation of X1 with Y is very significant. Thus the hypothesis that there is a positive relationship between Distribution Channel variables with Customer Satisfaction variables tested the truth. This means the higher the Distribution Channel, the higher the Customer Satisfaction.

The coefficient of determination is the square of the correlation coefficient between the variables X1 with the variable Y is equal to r2y1 = (0.424) 2 = 0.18, indicating that 18.00% variation that occurs in Customer Satisfaction can be explained by Distribution Channel through regression Y = 33, 63 + 0.45 X1.

If controlled between service varable (X2) obtained partial correlation coefficient of ry1.2 = 0.3491. Test of significance with the tcount price of 2.26 and the ttable price of 1.68 at alfa = 0.05. Since thitung (2.26)> ttable (1.68), it is concluded that the partial correlation coefficient is significant.

1. The second hypothesis in this study that there is a positive relationship Service (X2) to Customer Satisfaction (Y).

Calculation of simple regression analysis between data variable Customer Satisfaction on Service result in regression b direction equal to 0,61 and constant a equal to 22,05. Thus the form of relationship between the two variables can be described by the regression equation Y = 22.05 + 061 X2.

To determine the degree of significance and kelinearan regression equation, F test is done and the result that Price F regression obtained by 9.97 while the price Ftable with dk pembilang 1 and dk denominator 38 at a significant level of 0.01 of 7.35. Apparently the price Fhitung> Ftable, this shows that the regression direction coefficient Y over X1 significant at alfa = 0,01.

Based on result of significance test and linearity can be concluded 1.68 at alfa = 0,05. Because thitung (2.11)> ttable (1.68), it is concluded that the partial correlation coefficient is significant.

1. The third hypothesis proposed in this study states that there is a positive relationship of Distribution Channels (X1) and Services (X2) together to Customer Satisfaction (Y)

Complete regression of multiple regression from Customer Satisfaction variable yields regression direction b1 equal to 0,29 for variable X1 (Distribution Channel), b2 equal to 0,45 for variable X2 (Service), and constant a equal to 14,33. Thus the form of relationship between the independent variable with the dependent variable can be described by the regression equation Y = 14.33 + 0.29 X1 + 0.45 X2.

Price F regression is obtained at 6.75 while the price of Ftable with dk numerator 1 and dk denominator 38 at significant level of 0.05 is 4.10. It turns out that Fcount> Ftable, this shows that the regression direction coefficient Y over X1 is significant at alfa = 0,05.

The calculation of double correlation between variable X1 and variable X2 with variable Y yields correlation coefficient of R = 0,517. Test of significance by using the F test of Fcount = 6.65.

From the results of significance testing as in table 6 can be concluded that the correlation coefficient plural obtained in this study is significant.

Hypothesis which states that there is a positive relationship Channel Distribution and Service together with Customer Satisfaction tested the truth.

Coefficient of determination equal to R2 = (0,517) 2 = 0,267. This shows that 26.70% of variations that occur in Customer Satisfaction can be explained by Distribution Channels and Services with regression equation Y = 14.33 + 0.29 X1 + 0.45 X2