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dc.contributor.advisorArif, Hossain
dc.contributor.authorAhmed, Istear
dc.contributor.authorKarmakar, Tushar
dc.contributor.authorAnadi, Iffat Sumaita
dc.contributor.authorAzad, MD.Shahriar
dc.contributor.authorSharif, Faiza Ibnat
dc.date.accessioned2023-02-28T05:56:10Z
dc.date.available2023-02-28T05:56:10Z
dc.date.copyright2021
dc.date.issued2021-09
dc.identifier.otherID: 19101662
dc.identifier.otherID: 19101663
dc.identifier.otherID: 17101353
dc.identifier.otherID: 17101181
dc.identifier.otherID: 18301287
dc.identifier.urihttp://hdl.handle.net/10361/17924
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 31-32).
dc.description.abstractThe students are at a loss when it comes to choosing their major or field of work due to inefficient school system and decision making of the parents. This problem can be resolved to some extent by using classifiers. The accuracy of the decision the students will take can be gauged these using classifiers. These classifiers such as KNeighbor classifier and Decision tree classifier help to gauge the accuracy of the prediction. Decision tree classifier is more accurate in predicting the correct outcome. This use of classifier will help the students to take the right decision in case of their study and career field. Based on a student’s extra-curricular activity, Olympiad and HSC grade it predicts the major subject of an undergraduate student. Again, based on an undergraduate student’s major subject, CGPA and extra-curricular activity it predicts job of the student.en_US
dc.description.statementofresponsibilityIstear Ahmed
dc.description.statementofresponsibilityTushar Karmakar
dc.description.statementofresponsibilityIffatSumaitaAnadi
dc.description.statementofresponsibilityMD.Shahriar Azad
dc.description.statementofresponsibilityFaiza Ibnat Sharif
dc.format.extent32 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectData analysisen_US
dc.subjectUniversity studenten_US
dc.subjectMajor subjecten_US
dc.subjectJob sector predictionen_US
dc.subjectKNNen_US
dc.subjectDecision tree algorithmen_US
dc.subject.lcshComputer algorithms.
dc.titleAccuracy of data analysis on university student's major subject and job sector prediction using KNN and decision tree algorithmen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science and Engineering


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