Implementasi Limited Tolerance Relation Untuk Sistem Informasi yang Tidak Lengkap Pada Data Mahasiswa

Authors

  • Edi Sutoyo Program Studi Sistem Informasi, Universitas Telkom, Bandung, Jawa Barat, Indonesia, 40257

DOI:

https://doi.org/10.21111/fij.v3i1.1833

Keywords:

rough set, limited tolerance relation, incomplete information system, educational data mining

Abstract

Rough set theory is one of the mathematical models for dealing with a vague, imprecise, and fuzzy knowledge that has been successfully used to handle incomplete information systems. Since, in fact in the real-world problems, often found the conditions that are the user can not provide all the necessary preference values. In this research, an implementation of extension technique of rough set theory that called limited tolerance relation is used to overcome incomplete information systems in student data at Telkom University. Based on the obtained results, the limited tolerance relation technique successfully used to handle that problem. The results show that the technique achieved the  accuracy of 96.04% with an execution time of 3.1830 seconds.

References

C. Romero and S. Ventura, “Educational data mining: A survey from 1995 to 2005,” Expert Syst. Appl., vol. 33, no. 1, pp. 135–146, 2007.

S. Kotsiantis, C. Pierrakeas, and P. Pintelas, “Predicting Students’performance In Distance Learning Using Machine Learning Techniques,” Appl. Artif. Intell., vol. 18, no. 5, pp. 411–426, 2004.

S. K. Yadav and S. Pal, “Data mining: A prediction for performance improvement of engineering students using classification,” arXiv Prepr. arXiv1203.3832, 2012.

S. Pal, “Mining educational data to reduce dropout rates of engineering students,” Int. J. Inf. Eng. Electron. Bus., vol. 4, no. 2, p. 1, 2012.

S. Borkar and K. Rajeswari, “Predicting students academic performance using education data mining,” IJCSMC Int. J. Comput. Sci. Mob. Comput. ISSN, pp. 273–279, 2013.

S. K. Yadav, B. Bharadwaj, and S. Pal, “Mining Education data to predict student’s retention: a comparative study,” arXiv Prepr. arXiv1203.2987, 2012.

B. Minaei-Bidgoli, D. A. Kashy, G. Kortemeyer, and W. F. Punch, “Predicting student performance: an application of data mining methods with an educational web-based system,” in Frontiers in education, 2003. FIE 2003 33rd annual, 2003, vol. 1, p. T2A--13.

B. P. Bunting, G. Adamson, and P. K. Mulhall, “A Monte Carlo examination of an MTMM model with planned incomplete data structures,” Struct. Equ. Model., vol. 9, no. 3, pp. 369–389, 2002.

M. R. Chmielewski, J. W. Grzymala-Busse, N. W. Peterson, and S. Than, “The rule induction system LERS-a version for personal computers,” Found. Comput. Decis. Sci., vol. 18, no. 3–4, pp. 181–212, 1993.

Z. Pawlak, “Rough sets,” Int. J. Comput. Inf. Sci., vol. 11, no. 5, pp. 341–356, 1982.

D. Molodtsov, “Soft set theory—first results,” Comput. Math. with Appl., vol. 37, no. 4–5, pp. 19–31, 1999.

E. Sutoyo, I. T. R. Yanto, R. R. Saedudin, and T. Herawan, “A soft set-based co-occurrence for clustering web user transactions,” Telkomnika (Telecommunication Comput. Electron. Control., vol. 15, no. 3, 2017.

I. T. R. Yanto, M. A. Ismail, and T. Herawan, “A modified Fuzzy k-Partition based on indiscernibility relation for categorical data clustering,” Eng. Appl. Artif. Intell., vol. 53, pp. 41–52, 2016.

Z. Pawlak, “Some remarks on conflict analysis,” Eur. J. Oper. Res., vol. 166, no. 3, pp. 649–654, 2005.

E. Sutoyo, M. Mungad, S. Hamid, and T. Herawan, “An efficient soft set-based approach for conflict analysis,” PLoS One, vol. 11, no. 2, 2016.

Z. Kong, L. Gao, L. Wang, and S. Li, “The normal parameter reduction of soft sets and its algorithm,” Comput. Math. with Appl., vol. 56, no. 12, pp. 3029–3037, 2008.

M. A. T. Mohammed, W. M. W. Mohd, R. A. Arshah, M. Mungad, E. Sutoyo, and H. Chiroma, “ANALYSIS OF PARAMETERIZATION VALUE REDUCTION OF SOFT SETS AND ITS ALGORITHM,” Int. J. Softw. Eng. Comput. Syst., vol. 2, no. 1, pp. 51–57, 2016.

G. Wang, “Extension of rough set under incomplete information systems,” in Fuzzy Systems, 2002. FUZZ-IEEE’02. Proceedings of the 2002 IEEE International Conference on, 2002, vol. 2, pp. 1098–1103.

M. Kryszkiewicz, “Rough set approach to incomplete information systems,” Inf. Sci. (Ny)., vol. 112, no. 1, pp. 39–49, 1998.

M. Kryszkiewicz, “Rules in incomplete information systems,” Inf. Sci. (Ny)., vol. 113, no. 3, pp. 271–292, 1999.

J. Zhou and X. Yang, “Rough set model based on hybrid tolerance relation,” in International Conference on Rough Sets and Knowledge Technology, 2012, pp. 28–33.

J. Stefanowski and A. Tsoukiàs, “On the extension of rough sets under incomplete information,” in International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, 1999, pp. 73–81.

Downloads

Submitted

2018-03-30

Accepted

2018-05-03

Published

2018-05-04

Issue

Vol. 3 No. 1 (2018): Mei

Section

Articles

License

Please find the rights and licenses in the Fountain of Informatics Journal (FIJ). By submitting the article/manuscript of the article, the author(s) agree with this policy. No specific document sign-off is required.

1. License

The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. 

2. Author(s)' Warranties

The author warrants that the article is original, written by the stated author(s), has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author, and free of any third party rights, and that any necessary written permissions to quote from other sources have been obtained by the author(s).

3. User/Public Rights

FIJ's spirit is to disseminate articles published are as free as possible. Under the Creative Commons license, FIJ permits users to copy, distribute, display, and perform the work for non-commercial purposes only. Users will also need to attribute authors and FIJ on distributing works in the journal and other media of publications. Unless otherwise stated, the authors are public entities as soon as their articles got published. 

4. Rights of Authors

Authors retain all their rights to the published works, such as (but not limited to) the following rights;

  • Copyright and other proprietary rights relating to the article, such as patent rights,
  • The right to use the substance of the article in own future works, including lectures and books,
  • The right to reproduce the article for own purposes,
  • The right to self-archive the article (please read out deposit policy),
  • The right to enter into separate, additional contractual arrangements for the non-exclusive distribution of the article's published version (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal (Jurnal Optimasi Sistem Industri).

5. Co-Authorship

If the article was jointly prepared by more than one author, any authors submitting the manuscript warrants that he/she has been authorized by all co-authors to be agreed on this copyright and license notice (agreement) on their behalf, and agrees to inform his/her co-authors of the terms of this policy. FIJ will not be held liable for anything that may arise due to the author(s) internal dispute. FIJ will only communicate with the corresponding author.

6. Royalties

Being an open accessed journal and disseminating articles for free under the Creative Commons license term mentioned, author(s) aware that FIJ entitles the author(s) to no royalties or other fees. 

7. Miscellaneous

FIJ will publish the article (or have it published) in the journal if the article’s editorial process is successfully completed. FIJ's editors may modify the article to a style of punctuation, spelling, capitalization, referencing, and usage that deems appropriate. The author acknowledges that the article may be published so that it will be publicly accessible and such access will be free of charge for the readers as mentioned in point 3.