ANALISIS PENGARUH ATRIBUT PRODUK, BAURAN PROMOSI, DAN KUALITAS PELAYANAN TERHADAP KEPUTUSAN PEMBELIAN PRODUK MERCHANDISE ( Studi pada Kedai Digital 7 di Semarang )

Abstract

This research is motivated by the increasing number of business merchandise in major cities in Indonesia. The one is Kedai Digital 7 Semarang, a business unit engaged in different fields of creative production in particular areas of merchandise and graphic design. Although Kedai Digital 7 is not the only one merchandise company in Semarang, it is able to maintain its presence in the merchandise industry competition in Indonesia, especially in Semarang. It can be seen from the number of consumers who come to the Kedai Digital 7 Semarang for buying their products. The sale of its products has been increasing for 3 years. Therefore, the research is conducted to determine how the influence of product attributes, promotional mix, and service quality variables to the purchasing decision. After doing a literature review and hypothesis formulation, data are collected through questionnaire method of 100 respondents of Kedai Digital 7 in Semarang, which is obtained by using non-probability sampling technique. Then, we analyze the data that is obtained by using multiple regression analysis. This analysis includes validity and reliability, classical assumption test, multiple regression analysis, hypothesis testing by T-test and F-test, and analysis of determination coefficien (R2). From the analysis above, we get a regression equation : Y = 0,377 X1 + 0,259 X2 + 0,378 X3 where the purchasing decision variable (Y), product attributes (X1), promotional mix (X2), and service quality (X3). Hypothesis trial by T-test show that the three examined independent variables (product attributes variable, promotional mix, and service quality) are proven having positive and significant impact toward the dependent variables of purchasing decisions. Then, from F-test can be seen that the three independent variables are proper to exmine the dependent variables of purchasing decision. Adjusted R Square of 0.555 indicates that 55.5 % of the purchasing decision variables can be explained by the three independent variables in the regression equation. While the rest 44.5 % can be explained by other variables outside of the three variables used in this study.