THE EFFECT OF ONLINE ADVERTISING (ONLINE ADVERTISING) ON CONSUMER BUYING INTEREST IN BUYING APPLICATIONS ONLINE WITH CUSTOMER SATISFACTION AS INTERVENING VARIABLE

The results of this study show. (1) It can be seen that the adjusted R square value is 0.758 or 75.8%. This shows that consumer satisfaction (Y1) and advertising (X) can explain buying interest (Y2) by 75.8%, the remaining 24.2% (100% - 75.8%) is explained by other variables outside the research model. this. Such as service, price and buying interest. (2) The results of the t-test (partial) can be seen that the obtained tcount (7.413) > ttable (1.685), as well as the significance value of 0.00 <0.05, it can be concluded that the first hypothesis is accepted, meaning that the advertising variable (X) has a positive and significant effect on consumer satisfaction (Y1). (3) The results of the t-test (partial) can be seen that the value of tcount (3.059) > ttable (1.685), and the significance value of 0.00 <0.05, it can be concluded that the second hypothesis is accepted, meaning that advertisement (X) has a positive and significant effect on buying interest (Y2). (4) obtained tcount value of 7.413 With = 5%, ttable (5%; nk = 38) obtained ttable value of 2.024 From the description it can be seen that tcount (7.413) > ttable (2.024), as well as the significance value of 0.00 < 0.05 then it can be concluded that the first hypothesis is accepted, meaning that the advertising variable (X) has a positive and significant effect on consumer satisfaction (Z). obtained tcount value of 3,059 With = 5%, ttable (5%; nk = 38) obtained ttable value of 2,024 From this description it can be seen that tcount (3,059) > ttable (2,024), and the significance value is 0,004 < 0,05 then it can be concluded that the second hypothesis is accepted, meaning that advertising (X) has a positive and significant effect on buying interest (Y). obtained tcount value of 4.492 With = 5%, ttable (5%; nk = 38) obtained ttable value of 2.024 From the description it can be seen that tcount (4.492) > ttable (2.024), and the significance value is 0.00 < 0 0.05, it can be concluded that the third hypothesis is accepted, meaning that consumer satisfaction (Z)positive and significant effecton buying interest (Y). In the path analysis test it can be seen that the direct effect of advertising (X) on buying interest (Y) is greater than the indirect effect through advertising variable (X), on buying interest (Y) through consumer satisfaction (Z). This means that consumer satisfaction advertising is an intervening variable on the relationship between the influence of advertising on buying interest.