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dc.contributor.authorMarufuzzaman, Mohammad-
dc.contributor.authorGomes, Dipta-
dc.contributor.authorRupai, Aneem Al Ahsan-
dc.contributor.authorSidek, Lariyah Mohd-
dc.date.accessioned2023-11-05T08:16:43Z-
dc.date.available2023-11-05T08:16:43Z-
dc.date.issued2020-02-01-
dc.identifier.citationMarufuzzaman, M., Gomes, D., Rupai, A. A. A., & Sidek, L. M. (2020). Discovering rules for nursery students using apriori algorithm. Bulletin of Electrical Engineering and Informatics, 9(1), 298-303.en_US
dc.identifier.issn2302-9285-
dc.identifier.urihttp://dspace.aiub.edu:8080/jspui/handle/123456789/1650-
dc.description.abstractOver recent years, there has been a rise in the number of students completing nursery education in Bangladesh. However, in order to achieve a sustainable education goal, the dropout rate in education needs to be reduced. Therefore, this research worked on providing insights that would help to understand the possible causes of dropout from education. Since primary education is the starting point for every student, this research has been conducted on this part of education. The research used data obtained from a European country, Slovenia to use the insights of a developed country. The study was conducted using association rule mining where several mining rules were generated using the Apriori algorithm. The rules obtained had the confidence of 0.95 and support of 0.04. The result showed three major rules of dropping out children in nursery education and eventually helps to ensure higher education for all childrenen_US
dc.language.isoenen_US
dc.publisherBulletin of Electrical Engineering and Informatics (BEEI)en_US
dc.subjectApriori algorithmen_US
dc.subjectAssociation rulesen_US
dc.subjectData analysisen_US
dc.subjectInformation technologyen_US
dc.subjectNursery educationen_US
dc.titleDiscovering rules for nursery students using apriori algorithmen_US
dc.typeArticleen_US
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