American Journal of Software Engineering and Applications

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Analyzing Personality Behavior at Work Environment Using Data Mining Techniques

Received: 12 September 2016    Accepted: 17 September 2016    Published: 20 October 2016
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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.

DOI 10.11648/j.ajsea.s.2016050301.15
Published in American Journal of Software Engineering and Applications (Volume 5, Issue 3-1, May 2016)

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

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), 2024. 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.
Author Information
  • Faculty of Computer Engineering, Islamic Azad University, Islamshahr Branch, Terhan, Iran

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

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  • 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

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    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

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    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

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  • @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://download.sciencepg.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}
    }
    

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    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.
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