The purpose of this research and development was to produce valid and feasible canva learning media based on the flipbook maker according to the demands of student competencies in the digital era. The assignments are given in the form of making promotional media using social media Instagram and Pinterest. The research and development design used the model from Borg & Gall. In producing the product the researcher conducted material validation, media validation, and limited trials. Material validation was carried out by 2 people (1 lecturer and 1 teacher), media validation by 1 lecturer, and limited trials with 12 students. Data analysis was performed by using percentage, descriptive analysis, and analysis of the sample paired test. The results of validation and media testing were the percentage of media expert validation 93.19%, material expert validation 92.06%, limited trial results in 86.36%, and field implementation test results of 89.85%. The results of the validation and testing indicate the criteria were "very feasible". The results of the analysis of the independent samples test showed the Sig value. (2-tailed) of 0.00 <0.05, indicating that there was a significant difference between the experimental class that uses learning media and the control class that does not use media. The result of research and development was a product of Canva learning media based on the flipbook maker that was valid and feasible and can improve students' digital technopreneurship competence.
This research purposes to develop an Android-based Edupreneur media to improve students' technopreneurship competence, especially in the Business Education undergraduate study program. This media development can be applied to Entrepreneurship courses and other courses. With the development of this learning intermediary, it is hoped that it can become a reference for lecturers in making valid and appropriate learning intermediary for students according to the needs in the post-pandemic era that requires objectively good digital mastery. The development of this media can also assist students in achieving the expected competencies. This category of study is development study using the Research and Development (R&D) method which consists of eight steps, (1) preparatory study, (2) arrangement, (3) storyboard improvement, (4) limited exploratory, (5) product improvement, (6) field trials, (7) media enhancement, (8) final production. The improvement of technopreneurship competence was analyzed using paired sample t-Test analysis. The results of the validation of android-based edupreneur learning intermediary conducted by lecturers are declared valid and feasible. While the results of the validation of the edupreneur material were declared valid and feasible. There is a significant difference between students' technopreneurship competencies before and after using android-based edupreneur media. The improvement of students' technopreneurship competence can be seen from the results of product content creation projects posted through social media such as Instagram, Facebook, Twitter, YouTube, and other social media. In addition, it can also be seen from the results of creating online store accounts on e-commerce platforms such as shopee, tokopedia, and other e-commerce platforms according to the interests of each student. In other words, the Android-based Edupreneur learning intermediary can not only be used as a learning medium but also as a student learning resource.
Regression is a technique that can be used for response variables with one or more predictor variables. The purpose of this study is to model poverty in districts / cities in East Java 2015 with a spatial regression approach. In 2015, poverty in East Java has increased compared to the previous year. Therefore it is necessary to identify the factors that affect poverty. The variables used are the percentage of poor population as the response variable and the predictor variables include last elementary school education (X1), school participation rate 7-12 years (X2), informal sector workers (X3), open unemployment rate (X4), household using bamboo walls (X5), and household users of inadequate drinking water sources (X6). The result of this research is the best model to model the percentage of poor people is Spatial Error Model (SEM) with spatial weighting matrix Queen Contiguity and obtained AIC value 191,02 and R2 equal to 77,47%. Factors that have significant effect on the percentage of the poor are school enrollment (X2), informal sector workers (X3), household users of inadequate drinking water sources (X6) and there is an error dependency on one location to another.
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