Analisis Penjualan Produk Online UMKM melalui Marketplace dan E-Commerce dengan Pendekatan Binary Logistic Regression
Abstract
This study is to determine the purpose of predicting the probability of online sales SMEs in the municipality of East Jakarta, including the feasibility of the model and the overall model fit. The research method is carried out with a quantitative approach which uses Binary Logistic Regression or Binary Multiple Regression. Data were collected with the main data, namely questionnaires and supporting data, namely books and journals, for primary data using questionnaires or questionnaires, while secondary data using data from books and journals. 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 on the omnibus table reject H0. The conclusion is that at least one independent variable (marketplace or eCommerce) is significantly correlated with the response variable (sales) so that the model can be analyzed. Model summary for the Nagelkerke R-value of 0.595, that the sales variable is explained in the form of a model of 59.5%. The t-test output obtained by marketplace and eCommerce is statistically significant because it has a probability below 0.05. Therefore, the regression model shown is very good in predicting the sales of MSME online products
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