Discovering rules for nursery students using apriori algorithm

Mohammad Marufuzzaman, Dipta Gomes, Aneem Al Ahsan Rupai, Lariyah Mohd Sidek


Over 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 children.


Apriori algorithm; Association rules; Data analysis; Information technology; Nursery education

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