Entrepreneurial Student Motivation Analysis Through Online Media at Universities in Jakarta: Binary Logistic Regression Approach

The goal of this research is to find out the purpose of predicting the probability of entrepreneurship motivation of private universities in East Jakarta towards blended learning and social media learning which includes model feasibility and overall model fit. The research method is carried out with a quantitative approach that uses Binary x'Logistic Regression or Binary Multiple Regression. The analytical tests here are Case processing summary, Simultaneous Test (Omnibus Test), Expectation and measurement of association, Hosmer and Lemeshow model test, and Fit model test. Data analysis techniques include the simultaneous test based on the omnibus table, the hypothesis rejects H0. The conclusion is that there is at least one independent variable that is significantly correlated with the response variable so that the model can be analyzed. model summary for the Nagelkerke R-value of 0.641 that the entrepreneurial motivation variable is explained in the form of a model of 64.1 %. From the t-test output, blended learning and social media learning are statistically significant because they have a probability below 0.05. Therefore, the regression model shown is very good at predicting entrepreneurial motivation in the use of blended learning and social media learning media.