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 |
Character, Employee, Data Mining, Clustering, Kmeans
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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
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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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}
}
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 -
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