PENGARUH KUALITAS PRODUK, PROMOSI DAN DESAIN TERHADAP KEPUTUSAN PEMBELIAN KENDARAAN BERMOTOR YAMAHA MIO DI BANJARBARU KALIMANTAN SELATAN

Abstract

This study aims to analyze the effect of product quality, promotion and design towards Yamaha Mio motorcycles product purchase decisions as well as to analyze the variables that have the most dominant influence on product purchasing decisions on a Yamaha Mio motorcycle community in the region Banjarbaru. The populations in this study are all consumers Yamaha Mio motorcycle in the region Banjarbaru. The samples used are 100 respondents with Accidental Quota Sampling techniques. Data collection techniques with questionnaires, while data analysis techniques using regression analysis multiple linear, classical assumptions (normality test, multicollinearity test, heteroskedastisity test), statistical tests (t test, F test and coefficient of determination). From the analysis of classical assumptions, the normality test with kolmogorovsmirnov obtained significantly greater than 0.05, which means the distribution of data is normal. Multicollinearity test VIF and Tolerance values obtained are close to each other so that it can be concluded there is no multicollinearity problem in the regression model, while heteroskedastisity test with Glejser method declare no problem. Based on the results of multiple linear regression analysis obtained from the t test findings that the partial product quality significantly influence Yamaha Mio motorcycle products purchase decisions, while the promotion and design have a significant effect on 5% level. From the results of the F test that product quality, promotion and design simultaneously significantly influence purchase decisions Yamaha Mio motorcycle products where the value of F calculated > F table. Product quality has the most dominant influence on Yamaha Mio motorcycles product purchase decisions. It is obtained that value of R square of 0.365, which means that the dependent variable can be explained by the independent variable amounting to 36.5% while the remaining amount of 63.5% is explained by other variables outside the model.