<![CDATA[This research is descriptive qualitative. Classical assumption test was conducted to determine the normality of the data obtained and multiple linear regression test. In addition, a hypothesis test was conducted which consisted of t test, F test and R2 test. The results of the multiple linear regression equation are as follows: Y = 0.255 + 0.627X1 + 0.314X2. The results of the t-test for the location variable tcount value is greater than ttable value 7.996>1.991 with a significance value of 0.000 <0.05 and the value of the tcount price variable is greater than the t-table value 4.018>1.991 with a significance value of 0.000 <0.05. The results of the F test obtained Fcount > Ftable, Ftable value = 3.12, Fcount = (363.771> 3.12) and the level of significance (0.000 < 0.05) it can be concluded that the independent variables are Location (X1) and Price (X2) together the same positive and significant effect on the variable Consumer Decision (Y). The results of the R2 test show that the value of Adjusted R Square = 0.902 or 90.2% of the price and location variables affect consumer decisions in choosing a house.]]>
Copyrights © 2021
