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Based on the formula (k—1; n—k), the value of obtained to find f table (5—1;100—5) = (4;95), then distribution f table obtained value 2,47. In Table 8 the calculated f value of 69.139 is greater than the f table value of 2.47. Significance value is 0.00 less than 0.05 according to the basis of decision making, it can be concluded that the variables of product quality (X,), service quality (X2), price(X3), and trust (X4) simultaneously and have a positive directionin influencing purchase decisions (Y).

Table 8 Based on the formula (k—1; n—k), the value of obtained to find f table (5—1;100—5) = (4;95), then distribution f table obtained value 2,47. In Table 8 the calculated f value of 69.139 is greater than the f table value of 2.47. Significance value is 0.00 less than 0.05 according to the basis of decision making, it can be concluded that the variables of product quality (X,), service quality (X2), price(X3), and trust (X4) simultaneously and have a positive directionin influencing purchase decisions (Y).

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Table 1
Table 1
Analysis model in this research can be described as follows:
Analysis model in this research can be described as follows:
One Sample Kolmogorov Smirnov Test Normality test is used to determine whether in the regression model the independent variable and the dependent variable have a normal distribution or not. ‘One-Sample Kolmogorov-Smirnov Test IME JOURNAL Vol 1 No. 3 September 2022 — pISSN: 2829-0399, elSSN: 2829-0526, Page 01-12
One Sample Kolmogorov Smirnov Test Normality test is used to determine whether in the regression model the independent variable and the dependent variable have a normal distribution or not. ‘One-Sample Kolmogorov-Smirnov Test IME JOURNAL Vol 1 No. 3 September 2022 — pISSN: 2829-0399, elSSN: 2829-0526, Page 01-12
Source: Processed data SPSS 25 (2022) Based on the results of the normality test using one sample Kolmogorov Smirnov, Table 3 states that the effect of the independent variable on the dependent variable has a significant level of > 0.05,which is 0.200. So this study is declarednormally distributed.
Source: Processed data SPSS 25 (2022) Based on the results of the normality test using one sample Kolmogorov Smirnov, Table 3 states that the effect of the independent variable on the dependent variable has a significant level of > 0.05,which is 0.200. So this study is declarednormally distributed.
Based on the multicollinearity test in Table 4 shows that each variable has a VIF value < 10 and a Tolerance value > 0.10. it can be said that there is no multicollinearity in the regression model.
Based on the multicollinearity test in Table 4 shows that each variable has a VIF value < 10 and a Tolerance value > 0.10. it can be said that there is no multicollinearity in the regression model.
BOARS ee EON AALS LENE REET NTS AARON ESET meTIEC eR = MANY SUM Onee Multiple linear regression analysis was used to determine the relationship orinfluence between the independen variables on the dependent variable.
BOARS ee EON AALS LENE REET NTS AARON ESET meTIEC eR = MANY SUM Onee Multiple linear regression analysis was used to determine the relationship orinfluence between the independen variables on the dependent variable.
SRS AED ae en ee TRS Eat ENN NET Nae ene Ct rs Heteroscedasticity test is used to test whether in the regression model there is a similarity of variance from one observation to another. Based on the glejser test in Table 5 shows that each independent variable(product quality, service quality, price, and trust) has a significant value > 0.05. It canbe said that there is no heteroscedasticity in the regression model.
SRS AED ae en ee TRS Eat ENN NET Nae ene Ct rs Heteroscedasticity test is used to test whether in the regression model there is a similarity of variance from one observation to another. Based on the glejser test in Table 5 shows that each independent variable(product quality, service quality, price, and trust) has a significant value > 0.05. It canbe said that there is no heteroscedasticity in the regression model.
SO ES en A es RS Ras EA RRS ERS 4 SAENGER, RI ae A ci test is a test to determine thesignificance of the independent variablewhether it has a partial effect on the dependent variable. In the t-test you can do acomparison between arithmetic and t tables. While the testing criteria are as follows, the significant level (a = 0.05) where if the significance value <0.05, it can be concluded that the independent variablepartially has a significant effect on the dependent variable. Basic criteria fordecision making if t arithmetic> t table, then HO is rejected and H1 is accepted and if t arithmetic < t table, then HO is accepted and H1 is rejected. It is known that df = n - k where n is the number of samples, namely 100 and k is the number of research variables. Then we get df = 100 — 5 = 95. With a significant level of 0.05 the t table value obtained is 1.985. Based on the results of the t test in Table 7, the explanation can be stated asfollows:
SO ES en A es RS Ras EA RRS ERS 4 SAENGER, RI ae A ci test is a test to determine thesignificance of the independent variablewhether it has a partial effect on the dependent variable. In the t-test you can do acomparison between arithmetic and t tables. While the testing criteria are as follows, the significant level (a = 0.05) where if the significance value <0.05, it can be concluded that the independent variablepartially has a significant effect on the dependent variable. Basic criteria fordecision making if t arithmetic> t table, then HO is rejected and H1 is accepted and if t arithmetic < t table, then HO is accepted and H1 is rejected. It is known that df = n - k where n is the number of samples, namely 100 and k is the number of research variables. Then we get df = 100 — 5 = 95. With a significant level of 0.05 the t table value obtained is 1.985. Based on the results of the t test in Table 7, the explanation can be stated asfollows:
The coefficient of determination (R2) is used to measure how much the ability of independent variables in explaining the dependent variable. In thiscalculation the R2 value used is Adjusted R Square. The value of the coefficient of determination is between 0 and 1 or 0 < R’ < 1 if the coefficient of determination is getting closer to 1, then the regression modelis considered to be better. Based on table 9, Adjusted R square value of 0,734 it means 73,4% shows that the independent variables, namely productquality (X;), service quality (X2), price(X3), and trust (X4) can explain the dependent variable, namely the purchase decision (Y). While the rest 26,6% is explained by other independent variables not included in thisstudy, such as promotion, security, or brand image.
The coefficient of determination (R2) is used to measure how much the ability of independent variables in explaining the dependent variable. In thiscalculation the R2 value used is Adjusted R Square. The value of the coefficient of determination is between 0 and 1 or 0 < R’ < 1 if the coefficient of determination is getting closer to 1, then the regression modelis considered to be better. Based on table 9, Adjusted R square value of 0,734 it means 73,4% shows that the independent variables, namely productquality (X;), service quality (X2), price(X3), and trust (X4) can explain the dependent variable, namely the purchase decision (Y). While the rest 26,6% is explained by other independent variables not included in thisstudy, such as promotion, security, or brand image.
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