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Suggestion System for Matriculation Exam Result using Decision Tree Induction

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dc.contributor.author Khaing, Khwar Nyo
dc.contributor.author Yee, Myint Myint
dc.date.accessioned 2019-07-12T04:03:04Z
dc.date.available 2019-07-12T04:03:04Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/815
dc.description.abstract This paper implements suggestion for matriculation examination result using decision tree induction algorithm. To be a well-developed human society, there must not be a great gap among the youths and so it is very necessary to carry out various measures for knowledge skills in Myanmar. Many basic education high schools are opened to promote educational Standard in all states and divisions, and setting the effective guardianship plans for increasing matriculation students’ exam result, our society as well as our country will be developed. The progress makes the basic education to be developed. This paper intends to develop effective preplanning process for matriculation exam result based on data mining approach. Decision tree is a flow-chart-like tree structure, where each internal node denotes a test on an attribute, each branch represents an outcome of the test, and the leaf nodes represent classes or class distributions. Depending on the attribute values of the data set, this system can classify the result of the matriculation students’ exam whether it is in serious or normal conditions. Thus, the user can test a student’s conditions for a student’s matriculation exam result according to monitoring board of supervision committee. This system is based on Guardianship System for Basic Education Schools, Ministry of Education, Myanmar. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject Data mining en_US
dc.subject Classification en_US
dc.subject Decision tree induction en_US
dc.subject Matriculation exam en_US
dc.title Suggestion System for Matriculation Exam Result using Decision Tree Induction en_US
dc.type Article en_US

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