The Influence of the Indonesia Pintar Program (PIP) on Student Participation in Bali Province
DOI:
https://doi.org/10.61132/ijema.v1i2.96Keywords:
Smart Indonesia Program (PIP), number of household members, employment status of head of family, education of head of family, student participationAbstract
Education is the most basic development goal. The biggest challenge for Indonesia's education development today is how education services can be accessed by all levels of society, especially the poor. School participation is one of the indicators in education that is used to see the population's access to educational facilities, especially for the school age population . The aim of this research is to determine the influence of the Smart Indonesia Program (PIP) on student participation in Bali Province. This research was conducted in Bali Province. The sample in this study was school age children aged 7 to 18 years who received or did not receive the Smart Indonesia Program (PIP) in Bali Province. The number of observations using the SUSENAS data source in 2015 was 4,260 samples, in 2018 there were 5,169 samples and in 2021 there were 5,783 samples. This research uses data collection methods with non-participant observation techniques. The variables examined in this research are student participation, the Smart Indonesia Program (PIP), gender, number of household members, employment status of the head of the family, and education of the head of the family. The data analysis technique uses logit regression. The results of the research state that 1) All variables in the regression model simultaneously have a positive and significant effect on student participation in Bali Province. 2) The Smart Indonesia Program (PIP) as an interest variable has a positive and significant effect on student participation in Bali Province as shown in regression model 1 and regression model 4. 3) Another important variable, namely the education of the head of the family, partially has a positive and significant effect on student participation in Bali Province which is shown in each regression model.
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