PENGARUH JUMLAH KUNJUNGAN WISATAWAN DAN KREATIVITAS USAHA TERHADAP PENDAPATAN MASYARAKAT DI PANTAI BEBAS PARAPAT SIMALUNGUN - Gurning, Relamhot; Sihombing, Natalia ET; Sinaga, Kepler; Rajagukguk, Jonson (Lembaga Kajian Ilmu Sosial dan Politik (LKISPOL), 2024)
This study aims to evaluate the Influence of the Number of Tourist Visits and Business Creativity on Community Income in Parapat Simalungun Free Beach. The research method used involves community surveys, tourists and statistical data analysis to identify the relationship between the number of tourist visits and the level of community business creativity. The findings of this study are expected to provide strategic insight to the community to increase the effectiveness of the number of tourists and encourage better business creativity in order to increase overall community income. Data collection techniques using questionnaires. The data analysis method used is an instrument test consisting of a validity test and a reliability test, a classical assumption test consisting of a normality test, a heterosdecadasticity test, a multiple linear regression analysis test and a hypothesis test consisting of a t-test and a determination coefficient test (R2). Based on Multiple Linear Regression Analysis Y = 2.945 + 0.333 X1 + 0.520 X2 +e which means that if the variable Number of Tourist Visits, Business Creativity is 0, then the Income value will remain at 2.945. The regression coefficient value of the Number of Tourist Visits is 0.333, which means that if the Number of Tourist Visits increases by 1 unit, then Income will increase by 0.333. Based on the hypothesis testing with the t test, the t count value is 7.835> t table, which is 1.985 and the significant value of the variable Number of Tourist Visits is 0.000 <0.05. So it can be concluded that the Number of Tourist Visits has a positive and significant effect on Community Income in Parapat Simalungun Free Beach. The result of the determination coefficient (R Square) is 0.529 so that the ability of the independent variable to explain the dependent variable is 52.9%. and the remaining 47.1% is explained by other variables that are not included in this research model