Economic Valuation of Senggigi Nature Tourism With The Travel Cost Approach In 2024
DOI:
https://doi.org/10.37673/jebi.v10i1.6248Keywords:
Tourism, Senggigi, Multiple Linear RegressionAbstract
This study aims to determine how much economic value of Senggigi nature tourism is seen from travel costs and to determine whether travel costs, time costs, respondent perceptions, substitution characteristics, individual income, facilities, education level, distance, and age affect the number of individual visits by domestic and foreign tourists in Gili Trawangan nature tourism in North Lombok Regency. The research method used is the survey sample method, and the respondent determination technique is the accidental sampling method where the sample is carefully selected so that it is relevant to the research design. The analysis used Multiple Regression Analysis with ten main variables, namely the number of visits (Y), travel costs (X1), time costs (X2), respondent perceptions (X3), substitution characteristics (X4), individual income (X5) Facilities (X6) Education level (X7) distance (X8) and age (X9). with the result Y = -11.026 - 1.22X1 + 1.48X2 + 1.45X3 - 2.26X4 -7.43X5 + 2.88X6 + 2.21X7 + 7.75X8 + 0.12X9. The partial test results show that the calculated Z value of the substitution characteristic variable, facility variable, education level variable and distance variable is greater than the t-table value (-2.464 > -1.960), (3.490 > 1.960), (2.564 > 1.960), (3.919 > 1.960), which means that the substitution characteristics, education level, facilities, and distance have a significant influence on the number of visits. Meanwhile, the variables of travel costs, time costs, respondent perceptions, income, and age do not have a significant effect on the number of visits. The test results simultaneously or equally show that the nine independent variables, namely travel costs, time costs, respondent perceptions, substitution characteristics, individual income, facilities, education level, distance and age have a real influence on the dependent variable (number of visits).
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