<![CDATA[The method used in this study is a descriptive method with a quantitative approach, while the data collection technique used is through an open questionnaire with 5 rating scales (Likert). In connection with the unknown number of population members, the determination of the sample size, according to Sugiono, 2014:165, where multivariate analysis (correlation or multiple regression), for the sample size is 10 times the number of variables studied. Therefore, the population used as a source of data in this study for the size of the sample used as many as 96 respondents. The results of the calculations in this study are using SPSS version.25 by finding the results of the T test (partial) between the marketing mix variables that use 4 sub-variables on the buying interest variable. buy, namely Price Sub Variable (X.2) with the result 0.300 > 0.05, while the t-count value is 6,309 > t-table (1.995), while the results in the F test (simultaneous) in this study the F-count value is 8.393 while the f value -table of 2.50, it can be seen that the f-count value is 8.038 > f-table 2.50 with a significant level of 0.000 because the significant level is <0.05, then this regression model can be used for the dependent variable of Job Interest in other words it can be said that the independent variable Marketing Mix with The 4 Sub Variables together (simultaneously) have a significant effect on Purchase Interest.]]>
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