<![CDATA[The technique used for this research is a quantitative. This study uses an associative hypothesis. The author uses data analysis and classical hypothesis testing and multiple linear regression to respond to the research design. This study obtained six responses from all summary statements related to products, prices, and promotions. Here are the instructions: First, product (X1), price (X2), and promotion (X3) data affect purchasing decisions (Y) are affected simultaneously. the p value of the three variables is 0,000. Second, product (X1), price (X2), and promotion (X3) can have a major effect on purchasing decisions (Y). The p value of the three variables is 0.000 < 0.05. Third, the correlation value of purchasing decisions obtained by the product, price, and promotion variables is 0.970. This value indicates a very high value regarding the independent and dependent variables. Fourth, the product gets 0.617, the price is 0.905, and the promotion is 0.815. This determines the price-related value obtained by a very strong distribution result, then a moderate product contribution, and a strong promotional contribution. Fifth, the dominant price variable value is 0.905. Sixth, the regression model is intended to predict future purchasing decisions, because the SEE value is smaller than the standard deviation, namely 1.255 ＜ 5.448.]]>
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