CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Prediction of Study Track using Decision Tree and Aptitude Test

by Deepali Joshi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 152 - Number 8
Year of Publication: 2016
Authors: Deepali Joshi
10.5120/ijca2016911911

Deepali Joshi . Prediction of Study Track using Decision Tree and Aptitude Test. International Journal of Computer Applications. 152, 8 ( Oct 2016), 33-36. DOI=10.5120/ijca2016911911

@article{ 10.5120/ijca2016911911,
author = { Deepali Joshi },
title = { Prediction of Study Track using Decision Tree and Aptitude Test },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2016 },
volume = { 152 },
number = { 8 },
month = { Oct },
year = { 2016 },
issn = { 0975-8887 },
pages = { 33-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume152/number8/26343-2016911911/ },
doi = { 10.5120/ijca2016911911 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:57:41.194484+05:30
%A Deepali Joshi
%T Prediction of Study Track using Decision Tree and Aptitude Test
%J International Journal of Computer Applications
%@ 0975-8887
%V 152
%N 8
%P 33-36
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In order to succeed in the competitive environment it is essential to be successful in academics. The basic education is from 1st to 10th standard and once 10th standard is complete there are various courses that can be selected by the students such as Science, Commerce, Arts and Diploma. It becomes difficult to identify the suitable stream. The proposed system can be used to solve the problem. The proposed system implements two methods to generate solution. The Aptitude Test predicts the suitable stream depending upon the intellectual capability of the student. Apart from this prediction is done depending on the ssc marks obtained by the student. The combination of these two methods is also implemented to get more accurate results. The proposed system not only predicts the stream but also specifies the colleges for the predicted stream depending upon the location of student and also gives information about vocational courses that the student can pursue after 10th.

References
  1. Ahmad I., Manarvi, I., Ashraf, N. “Predicting university performance in a subject based on high school majors”, 978-1-4244-4136-5/09/ ©2009 IEEE
  2. Zhiwu Liu, Xiuzhi Zhang. “Prediction and Analysis for Students' Marks Based on Decision Tree Algorithm”, Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on Digital Object Identifier:10.1109/ICINIS.2010.59.  Publication Year: 2010, Page(s): 338 – 341
  3. Anupama Kumar S, Vijayalakshmi M.N., “Mining of student academic evaluation records in higher education”, International Conference on Recent Advances in Computing and Software Systems (RACSS), 2012 Digital Object Identifier:10.1109/RACSS.2012.6212699, Publication Year: 2012 IEEE , Page(s): 67 – 70
  4. Bunkar, K, Singh U.K., Pandya B, Bunkar R, “Data mining: Prediction for performance improvement of graduate students using classification”, WOCN, 2012 Digital Object Identifier: 10.1109/WOCN.2012.6335530 Publication Year: 2012 IEEE, Page(s): 1 – 5
  5. Garcia, E.P.I. ; Mora, P.M., “Model Prediction of Academic Performance for First Year Students”, Artificial Intelligence (MICAI), 2011 10th Mexican International Conference on Digital Object Identifier: 10.1109/MICAI.2011.28 Publication Year: 2011 IEEE , Page(s): 169 – 174
  6. Pumpuang, P., Srivihok, A., Praneetpolgrang, “Comparisons of classifier algorithms: Bayesian network, C4.5, decision forest and NBTree for Course Registration Planning model of undergraduate students”, Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on Digital Object Identifier: 10.1109/ICSMC.2008.4811865  Publication Year: 2008 IEEE, Page(s): 3647 – 3651
  7. Qasem A. Al-Radaideh, Ahmad Al Ananbeh, and Emad M. Al-Shawakfa A “Classification Model For Predicting The Suitable Study Track For School Students”. IJRRAS 8 (2) August 2011
  8. Sunita Beniwal, jitender Arora “Classification and Feature Selection Techniques in Data Mining”, IJERT AUGUST 2012
  9. Heena Sharma, Navdeep Kaur Kaler “Data Mining with Improved and Efficient Mechanism in Clustering Analysis and Decision Tree as a Hybrid Approach” (IJITEE) ISSN: 2278-3075, Volume-2, Issue-5, April 2013
  10. Vaibhav P. Vasani, Rajendra D. Gawali “Classification and performance evaluation using data mining algorithms”, IJIRSET ISSN: 2319-8753, Vol. 3, Issue 3, March 2014
  11. Mr. Shridhar Kamble, Mr. Aaditya Desai “Evaluation and Performance Analysis of Machine Learning Algorithms”, IJESRT ISSN: 2277-9655, May, 2014
  12. Mohd. Mahmood Ali1, Mohd. S. Qaseem2, Lakshmi Rajamani3, A. Govardhan4, “EXTRACTING USEFUL RULES THROUGH IMPROVED DECISION TREE INDUCTION USING INFORMATION ENTROPY“, International Journal of Information Sciences and Techniques (IJIST) Vol.3, No.1, January 2013
  13. Abeer Badr El Din Ahmed, Ibrahim Sayed Elaraby, “Data Mining: A prediction for Student's Performance Using Classification Method “World Journal of Computer Application and Technology 2(2): 43-47, 2014, DOI: 10.13189/wjcat.2014.020203
  14. Dorina Kabakchieva, “Predicting Student Performance by Using Data Mining Methods for Classification”, CYBERNETICS AND INFORMATION TECHNOLOGIES • Volume 13, No 1 , ISSN: 1311-9702; Online ISSN: 1314-4081
  15. Ajay Kumar Pal , Saurabh Pal , “Classification Model of Prediction for Placement of Students”, I.J.Modern Education and Computer Science, 2013, 11, 49-56 Published Online November 2013 in MECS (http://www.mecs-press.org/)DOI: 10.5815/ijmecs.2013.11.07
  16. M. Hanumanthappa, M Narayana Swamy, “Predicting Academic Success from Student Enrolment Data using Decision Tree Technique”, International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 4– No.3, September 2012 – www.ijais.org
  17. Sunita B Aher, Mr. LOBO L.M.R.J, “Data Mining in Educational System using WEKA”, International Conference on Emerging Technology Trends (ICETT) 2011 Proceedings published by International Journal of Computer Applications® (IJCA)
  18. M.I. López, J.M Luna, C. Romero, S. Ventura, “Classification via clustering for predicting final marks based on student participation in forums”
  19. Neelamadhab Padhy 1, Dr. Pragnyaban Mishra 2, and Rasmita Panigrahi 3, “The Survey of Data Mining Applications And Feature Scope”, International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
  20. Surjeet Kumar Yadav, Saurabh Pal, “Data Mining: A Prediction for Performance Improvement of Engineering Students using Classification”, World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 2, No. 2, 51-56, 2012
  21. Surjeet Kumar Yadav 1, Brijesh Bharadwaj2, Saurabh Pal3, “Data Mining Applications: A comparative Study for Predicting Student’s performance”, INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-711) VOL.1 NO.12 DECEMBER
  22. J. Han and M. Kamber, “Data Mining: Concepts and Techniques”, Morgan Kaufmann, 2nd, 2006
  23. T.Miranda Lakshmi, A.Martin, R.Mumtaj Begum, Dr.V.Prasanna Venkatesan, “An Analysis on Performance of Decision Tree Algorithms using Student’s Qualitative Data”, I.J.Modern Education and Computer Science, 2013, 5, 18-27 Published Online June 2013 in MECS (http://www.mecs-press.org/),DOI: 10.5815/ijmecs.2013.05.03
  24. Elakia, Gayathri, Aarthi, Naren J, “Application of Data Mining in Educational Database for Predicting Behavioural Patterns of the Students”, Elakia et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (3) , 2014, 4649-4652
  25. Pimpa Cheewaprakobkit, “Study of Factors Analysis Affecting Academic Achievement of Undergraduate Students in International Program”, Proceedings of the International MultiConference of Engineers and Computer Scientists 2013 Vol I, IMECS 2013, March 13 - 15, 2013, Hong Kong
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining C4.5 NBTree ssc ssc-marks Precision Recall fMeasure

Powered by PhDFocusTM