The Influence of School Strategy and Innovation in Enhancing Parental Interest at SDN 07 Koto Besar Nagari Koto Tinggi - Saputri, Yulnida; Arsis , Asi Noflanda; Andre , Lesis; Yunanda , B.R.E. (The Future of Education Journal, 2025)
The background of this research is that, in essence, every parent will choose and compare schools, considering both the advantages and disadvantages of each school. The goal is to provide a good education for their child, selecting the best and highest quality school to prepare the child for the future. Public perception is derived from society's judgment of whatever they see, understand, and feel. Therefore, schools must be able to build trust within the community to create a positive perception of the school. This study uses a quantitative descriptive approach, with data collection techniques through the distribution of questionnaires to 35 respondents, measured using a Likert scale. The data analysis techniques employed are multiple linear regression analysis and hypothesis testing, with data processing using SPSS 2.5, presented descriptively. Based on the data processing results, the multiple linear regression equation obtained is Y = 43.491 + 0.237X1 + 0.304X2. From this equation, it can be concluded that the constant value is 43.491, the regression coefficient for the School Strategy variable is 0.237, and the regression coefficient for the School Innovation variable is 0.304. Based on the F-test results, it is known that the F-table value is 3.29, and the F-calculated value is 7.384 with a significance level of 0.00. Since the F-calculated value (7.384) is greater than the F-table value (3.29) and the significance level (0.00) is less than 0.05, it can be concluded that the School Strategy variable (X1) and the School Innovation variable (X2) simultaneously have a positive and significant effect on parents' interest (Y). Therefore, the hypothesis that school strategy and school innovation affect parents' interest is supported. The coefficient of determination (r²) is 0.316, which indicates that the independent variables time management and learning motivation can influence the dependent variable (academic achievement of working students) by 31.6%, while the remaining 68.4% is influenced by other variables not included in the regression model.