CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Appraisal Management System using Data mining Classification Technique

by Nikhil N. Salvithal, R.B. Kulkarni
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 135 - Number 12
Year of Publication: 2016
Authors: Nikhil N. Salvithal, R.B. Kulkarni
10.5120/ijca2016908596

Nikhil N. Salvithal, R.B. Kulkarni . Appraisal Management System using Data mining Classification Technique. International Journal of Computer Applications. 135, 12 ( February 2016), 45-50. DOI=10.5120/ijca2016908596

@article{ 10.5120/ijca2016908596,
author = { Nikhil N. Salvithal, R.B. Kulkarni },
title = { Appraisal Management System using Data mining Classification Technique },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 135 },
number = { 12 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 45-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume135/number12/24105-2016908596/ },
doi = { 10.5120/ijca2016908596 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:35:39.757854+05:30
%A Nikhil N. Salvithal
%A R.B. Kulkarni
%T Appraisal Management System using Data mining Classification Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 135
%N 12
%P 45-50
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Performance appraisal may be a method within which staff are rated on however well they need met performance expectations. Performance appraisals are meant to support employees’ selections, as well as promotions, terminations, training, and remuneration will increase. This task involves lots of social control selections that depends on numerous factors like human expertise, knowledge, preference and judgment. of these factors will cause inconsistent, inaccurate, difference and unpredictable selections. DM is rising knowledge analysis tool and wide utilized in order to supply valuable information for deciding. DM classification methodology are often used for talent statement, particularly for employee’s job promotion. within the planned system the assorted classifier algorithms are going to be applied on Talent dataset to spot the talent set so as to judge the performance of the individual. Finally counting on accuracy one best suited classifier is chosen this method has been used to construct classification rules to predict the potential talent that helps in determining whether or not the individual is acceptable for promotion or not.

References
  1. E. Frank, Hall, M., et al., "Data mining in bioinformatics using Weka," Bioinformatics Application Note, vol. 20, pp.2479-2481, 2004.
  2. C. Combes, Meskens, N., Rivat,, C. & Vandamme J.P., "Using a KDD process to forecast the duration of surgery,"International Journal of Production Economics, vol. 112, pp. 279-293, 2008.
  3. A. S. Chang, & Leu, S.S., "Data mining model for identifying project profitablility variables," International Journal of Project Management, vol. 24, pp. 199-206, 2006.
  4. S. H. Liao, Chen, Y.N., & Tseng, Y.Y., "Mining demand chain knowledge of life insurance market for new product development," Expert Systems with Applications, vol. 36, pp. 9422-9437, 2009.
  5. W. S. D. Chen, Y.K., "Using neural networks and data mining techniques for the financial distress prediction model" Expert System with Applications, vol. 36, pp. 4075-4086, 2009.
  6. C. Rygielski, J. C. Wang, and D. C. Yeh, "Data mining techniques for custome relationship management," Technology in Society, vol. 24, pp. 483-502, 2002.
  7. J. Ranjan and K. Malik, "Effective educational process: A data mining approach", VINE: The Journal of Information and Knowledge Management Systems, vol. 37, pp. 502-515, 2007.
  8. J. Ranjan, "Data Mining Techniques for better decisions in Human Resource Management Systems," International Journal of Business Information Systems, vol. 3, pp. 464-481, 2008.
  9. C. F. Chien and L. F. Chen, "Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry," Expert Systems and Applications, vol. 34, pp. 380-290, 2008
  10. SoumenChakrabarti, Earl Cox, Eibe Frank, Ralf HartmutGüting, Jaiwei Han, Xia Jiang, MichelineKamber, Sam S. Lightstone, Thomas P. NadeauRichard E. Neapolitan, Dorian Pyle, MamdouhRefaat, Markus Schneider, Toby J. Teorey, Ian H. Witten, “Data Mining-Know it all”, Morgan Kaufmann Publishers, 2009.
  11. J. Han and M. Kamber , - “ Data Mining; Concepts and Techniques”, Morgan Kaufmann Publishers, 2000.
  12. Anitha Mary Florence.T and Ms.Savithri.R, “Talent Knowledge Acquisition Using C4.5 Classification Algorithm” International Journal of Emerging Technologies in Computational and Applied Sciences, 4(4), March-May 2013.
  13. Hamidah Jantan , Abdul Razak Hamdan and Zulaiha Ali Othman, “Intelligent DSS for Talent Management: A Proposed Architecture using Knowledge Discovery Approach”, ICUIMC’12, February 20–22, 2012(ACM).
  14. Hamidah Jantan et al, “Human Talent Prediction in HRM using C4.5 Classification Algorithm” ,(IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 08, 2010.
  15. Nina At. Ruskova , “Decision Support System for Human Resources Appraisal and Selection”, First International IEEE Symposium“Intelligent Systems” September 2002.
  16. Huang, L.C., et al, “Applying fuzzy neural network in human resource selection system”. In Proceeding NAFIPS '04,IEEE Annual Meeting of the Fuzzy information 2004.
  17. Tai, W.S. and C.C. Hsu (2005), A Realistic Personnel Selection Tool Based on Fuzzy Data Mining Method.
  18. Jantan, H.; Hamdan, A.R.; Othman, Z.A, Potential Intelligent Techniques in Human Resource Decision Support System (HR DSS),IEEE 2008.
  19. Hamidah Jantan, Abdul Razak Hamdan,a.Zulaiha Ali Othman, Towards applyingData Mining Techniques for Talent Management, 2009International Conference on Computer Engineering and Applications.
  20. Jantan, H., Hamdan, A.R. and Othman, Z.A. (2010a), Knowledge Discovery Techniques for Talent Forecasting in Human Resource Application, International Journal of Humanities and Social Science, 5(11), pp. 694-702
  21. Jantan, H.; Hamdan, A.R.; Othman, Z.A, Classification for Talent Management Using Decision Tree Induction Techniques 2nd Conference on Data Mining and Optimization27-28 October 2009, Selangor, Malaysia.
Index Terms

Computer Science
Information Sciences

Keywords

Appraisal data mining classification J48.

Powered by PhDFocusTM