Discovering rules for nursery students using apriori algorithm
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 unders...
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Institute of Advanced Engineering and Science
2023
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my.uniten.dspace-255792023-05-29T16:11:13Z Discovering rules for nursery students using apriori algorithm Marufuzzaman M. Gomes D.J. Rupai A.A.A. Sidek L.M. 57205234835 57216082774 57216349325 35070506500 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. � 2020, Institute of Advanced Engineering and Science. All rights reserved. Final 2023-05-29T08:11:13Z 2023-05-29T08:11:13Z 2020 Article 10.11591/eei.v9i1.1665 2-s2.0-85083179754 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083179754&doi=10.11591%2feei.v9i1.1665&partnerID=40&md5=73ca89fe30af0b457da0b56f8d241904 https://irepository.uniten.edu.my/handle/123456789/25579 9 1 298 303 All Open Access, Bronze, Green Institute of Advanced Engineering and Science Scopus |
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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. � 2020, Institute of Advanced Engineering and Science. All rights reserved. |
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57205234835 |
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57205234835 Marufuzzaman M. Gomes D.J. Rupai A.A.A. Sidek L.M. |
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Marufuzzaman M. Gomes D.J. Rupai A.A.A. Sidek L.M. |
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Marufuzzaman M. Gomes D.J. Rupai A.A.A. Sidek L.M. Discovering rules for nursery students using apriori algorithm |
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Marufuzzaman M. |
title |
Discovering rules for nursery students using apriori algorithm |
title_short |
Discovering rules for nursery students using apriori algorithm |
title_full |
Discovering rules for nursery students using apriori algorithm |
title_fullStr |
Discovering rules for nursery students using apriori algorithm |
title_full_unstemmed |
Discovering rules for nursery students using apriori algorithm |
title_sort |
discovering rules for nursery students using apriori algorithm |
publisher |
Institute of Advanced Engineering and Science |
publishDate |
2023 |
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13.19449 |