Application of Decision Tree Algorithm for prediction of Student’s Academic Performance
Jeromie Reggie Ebenezer1, R Venkatesan2, K Ramalakshmi3, Jewel Johnson4, Glen P I5, Vibin Vinod6
1Jeromie Reggie Ebenezer, Department of Computer Science and Technology, Karunya Institute of Technology and Sciences, Coimbatore, India.
2R Venkatesan, Department of Computer Science and Technology, Karunya Institute of Technology and Sciences, Coimbatore, India.
3K Ramalakshmi, Department of Computer Science and Technology, Karunya Institute of Technology and Sciences, Coimbatore, India.
4Jewel Johnson, Department of Computer Science and Technology, Karunya Institute of Technology and Sciences, Coimbatore, India.
5Glen P I, Department of Computer Science and Technology, Karunya Institute of Technology and Sciences, Coimbatore, India.
6Vibin Vinod, Department of Computer Science and Technology, Karunya Institute of Technology and Sciences, Coimbatore, India.
Manuscript received on 08 April 2019 | Revised Manuscript received on 15 April 2019 | Manuscript Published on 26 April 2019 | PP: 561-564 | Volume-8 Issue-6S April 2019 | Retrieval Number: F61140486S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With the increasing need of imparting quality education and evaluating students on all round development and performance, researchers and academicians have started applying data mining in the educational field, which now is also called as Educational Data Mining. The technique of educational data mining is used to evaluate and to extract facts, hidden knowledge and pat-terns from the available data of students which are used by researchers, academicians, educational panels to improve academic policies and student’s academic performance. Student details such as gender, marks, attendance, attitude towards study, family income etc. have been used by various re-searchers to analyze and extract facts to improve the education system. In this paper we use student’s attendance and various marks scored to evaluate and predict their performance. The model being created will be very useful for all the stakeholders of education system in improving student performance, teaching methodologies and Institution ranking.
Keywords: Academic Performance, Data Mining.
Scope of the Article: Computer Science and Its Applications