| Peer-Reviewed

Analyzing Personality Behavior at Work Environment Using Data Mining Techniques

Received: 12 September 2016     Accepted: 17 September 2016     Published: 20 October 2016
Views:       Downloads:
Abstract

Character is the influencing factor of human behavior. This research aims to analyze the relationship between different types of characters. The statistical society sample for this study is the employees of the Iran Mahd Parta Pajhohan technical complex. Two hundred employees have been divided into four clusters including: Type D (Dominant), Type I (Influential), Type S (Steady) and Type C (Conscientious). The analysis of the data has taken place at two levels, which are known as descriptive and inferential statistics. K means algorithm has been used to cluster employees, and as a result, most of the employees are DC personality types. The results help in improving the operation of the organizations as well as leading a healthy relationship between employees.

Published in American Journal of Software Engineering and Applications (Volume 5, Issue 3-1)

This article belongs to the Special Issue Advances in Computer Science and Information Technology in Developing Countries

DOI 10.11648/j.ajsea.s.2016050301.15
Page(s) 20-24
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Character, Employee, Data Mining, Clustering, Kmeans

References
[1] Burche, A, Chandak, M. B, Zadgaonkar, A, Opinion Mining And Analysis: A Survey, International Journal on Natrual Languega Computing (IJNLC). Vol. 2, No. 3, June 2013.
[2] Liao, S-H, Chu, P. H, Hsiao, P. H, Dat mining techniques and application – A decade review from 2000 to 2011, Journal hompage: www.elsevier.com/lacate/eswa.
[3] Tehran publishing rasa Albvty. Mostafa، Karl El Cooper and Raja calimo, Management of Socio_psychological Factors at work, Tehran publishing rasa, 2005.
[4] Bruin, j. s, Cocx, T. K, Kosters, W. A, Laros, J, Kok, J. N, Data mining approaches to criminal career analysis in Proceeding of the sixth international conference on Data Mining (ICDM 06), pp, 171-177, 2006.
[5] Fodor, I. K, A survey of dimension reduction techniques, technical report, Lawrence National Laboratory, June 2002.
[6] Cambria, E, Schuller, B, Xia, Y, Havasi, C, New Avenues in opinion Mining and Sentiment Analysis, Published by the IEEE Computer Society. 2013.
[7] Adhatrao, K, Gaykar, A, Dhawan, A, Jha, R, Honrao, V, Predicting Students Performance Using ID3 And C4.5 Classification Algorithms, International Journal of International Journal Knowledge Management Process (IJDKP) Vol. 3, No. 5, September 2013.
[8] http:// persiansun.persianblog.ir/post/2015
[9] Bruin, j. s, Cocx, T. K, Kosters, W. A, Laros, J, Kok, J. N, Data mining approaches to criminal career analysis in Proceeding of the sixth international conference on Data Mining (ICDM 06), pp, 171-177, 2006.
[10] Khanifar, Hossein, Moqimi, Mohammad, Fatehi, Narges Sadat. Data Mining and Knowledge Discovery, University of Science and Industry, 2009.
[11] Fodor, I. K, A survey of dimension reduction techniques, technical report, Lawrence National Laboratory, June 2002.
[12] Tan. P. N, Steinbach. M, Kumar. V, Introduction to Data Mining, Addison-Wesley, 2005.
[13] MySql – the world most popular open source database, http://www.mysql.com/
[14] Rapid Miner, http:// rapid.com/content/view/181/190/
[15] sharma. R, Nigam. S, Jain. R, Opinion Mining In Hindi Language: A Survey, International Journal in Foundations of Computer Science & Technology (IJFCST), Vol. 4, No. 2, March 2014.
Cite This Article
  • APA Style

    Sepideh Ahmadi Maldeh, Fateme Safara. (2016). Analyzing Personality Behavior at Work Environment Using Data Mining Techniques. American Journal of Software Engineering and Applications, 5(3-1), 20-24. https://doi.org/10.11648/j.ajsea.s.2016050301.15

    Copy | Download

    ACS Style

    Sepideh Ahmadi Maldeh; Fateme Safara. Analyzing Personality Behavior at Work Environment Using Data Mining Techniques. Am. J. Softw. Eng. Appl. 2016, 5(3-1), 20-24. doi: 10.11648/j.ajsea.s.2016050301.15

    Copy | Download

    AMA Style

    Sepideh Ahmadi Maldeh, Fateme Safara. Analyzing Personality Behavior at Work Environment Using Data Mining Techniques. Am J Softw Eng Appl. 2016;5(3-1):20-24. doi: 10.11648/j.ajsea.s.2016050301.15

    Copy | Download

  • @article{10.11648/j.ajsea.s.2016050301.15,
      author = {Sepideh Ahmadi Maldeh and Fateme Safara},
      title = {Analyzing Personality Behavior at Work Environment Using Data Mining Techniques},
      journal = {American Journal of Software Engineering and Applications},
      volume = {5},
      number = {3-1},
      pages = {20-24},
      doi = {10.11648/j.ajsea.s.2016050301.15},
      url = {https://doi.org/10.11648/j.ajsea.s.2016050301.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.s.2016050301.15},
      abstract = {Character is the influencing factor of human behavior. This research aims to analyze the relationship between different types of characters. The statistical society sample for this study is the employees of the Iran Mahd Parta Pajhohan technical complex. Two hundred employees have been divided into four clusters including: Type D (Dominant), Type I (Influential), Type S (Steady) and Type C (Conscientious). The analysis of the data has taken place at two levels, which are known as descriptive and inferential statistics. K means algorithm has been used to cluster employees, and as a result, most of the employees are DC personality types. The results help in improving the operation of the organizations as well as leading a healthy relationship between employees.},
     year = {2016}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Analyzing Personality Behavior at Work Environment Using Data Mining Techniques
    AU  - Sepideh Ahmadi Maldeh
    AU  - Fateme Safara
    Y1  - 2016/10/20
    PY  - 2016
    N1  - https://doi.org/10.11648/j.ajsea.s.2016050301.15
    DO  - 10.11648/j.ajsea.s.2016050301.15
    T2  - American Journal of Software Engineering and Applications
    JF  - American Journal of Software Engineering and Applications
    JO  - American Journal of Software Engineering and Applications
    SP  - 20
    EP  - 24
    PB  - Science Publishing Group
    SN  - 2327-249X
    UR  - https://doi.org/10.11648/j.ajsea.s.2016050301.15
    AB  - Character is the influencing factor of human behavior. This research aims to analyze the relationship between different types of characters. The statistical society sample for this study is the employees of the Iran Mahd Parta Pajhohan technical complex. Two hundred employees have been divided into four clusters including: Type D (Dominant), Type I (Influential), Type S (Steady) and Type C (Conscientious). The analysis of the data has taken place at two levels, which are known as descriptive and inferential statistics. K means algorithm has been used to cluster employees, and as a result, most of the employees are DC personality types. The results help in improving the operation of the organizations as well as leading a healthy relationship between employees.
    VL  - 5
    IS  - 3-1
    ER  - 

    Copy | Download

Author Information
  • Faculty of Computer Engineering, Islamic Azad University, Islamshahr Branch, Terhan, Iran

  • Faculty of Computer Engineering, Islamic Azad University, Islamshahr Branch, Terhan, Iran

  • Sections