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A Cognitive Ability based Decision System for Enhancing the Industry Growth using Data Mining Techniques


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1 Department of IT, Al Musanna College of Technology, Muladdah Musanna, Sultanate of Oman, Oman
     

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This research work focuses on industry objectives like employees’ performance study based on personality and Emotional behavior. The major objective is to identify the potential of employees in the working environment. The sub objectives are analyzing the employees’ personalities and draw out the information person’s motivation, preferences, a person’s interests, identifying the emotional make-up with people and situations. Eynseck Personality Inventory (EPI) is used to classify the employees’ personality. Likert scale is used to measure the emotionality of an employee. Association rule mining is used to identify the hidden patterns among the set of attributes based on interesting measures. The multilayer perception technique helps to classify employees’ ability by applying cross-validation. This analysis can be used to improve the employees’ capability and their behavior in the working environment. This study can be used to determine the employees’ performance and helps the industry management people to improve the industry growth by identifying the various capabilities of employees and their emotionality.


Keywords

Personality traits, Emotional Quotient, Association Rule, Multi-Layer Perceptron.
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  • Lewandowski, Gary; Strohmetz, David , "Actions can speak as loud as words: Measuring behavior in psychological science". Social and Personality Psychology Compass. 3 (6): 992–1002,2009
  • Petrides K. V., “The Trait Emotional Intelligence Questionnaire (TEIQue)”, URL: http://www.eiconsortium.org/measures/teique.html 2011.
  • Thagard, Paul., "Cognitive Science", The Stanford Encyclopedia of Philosophy, Edition, URL: http://plato.stanford.edu/entries/cognitive-science/ 1st October 2011.
  • Perry SJ, Hunter EM, Witt LA, Harris KJ. “P = f (conscientiousness x ability): examining the facets of conscientiousness”. Hum. Perform. 23:343–60,2010.
  • Vinai Viriyavidhayavongs, Satita Jiamsuchon., “The Relationship between Emotional Quotient (EQ) and Leadership Effectiveness in Life insurance Business Organizations”, ABAC Journal, Vol. 21, No. 2, pp.22-34.2001.
  • Sabine BergnerAljoscha C. NeubauerAljoscha C. NeubauerArmin KreuzthalerArmin Kreuzthaler, "Broad and narrow personality traits for predicting managerial success European Journal of Work and Organizational Psychology 19(2):177-199,April 2010
  • Hastings SE, O’Neill TA. “Predicting workplace deviance using broad versus narrow personality variables. Personal. Individ. Differ”. 47:289– 93,2009.
  • Hough LM, Dilchert S.. Personality: its measurement and validity. , pp. 299–320,2010.
  • Farr JL, Tippins NT. Handbook of Employee Selection. New York: Routledge,2010.
  • Abdolghani Abdollahimohammad1,* and Rogayah Ja’afar, "Learning Style Scales: a valid and reliable questionnaire", Journal of Education Evaluation Health Professions,doi: 10.3352/jeehp.2014.11.22, 2014.
  • Blake-Beard, S. D. “The costs of living as an outsider within: An analysis of the mentoring relationships and career success of black and white women in the corporate sector”. Journal of Career Development, 26, 21– 36, 1999.
  • Jime´nez, P. The profile analysis of job satisfaction: Reliability, validity and benefits of a new measurement. Paper presented at the eighth European Congress of Psychology, Vienna. 2003.
  • Borman, W. C., Hanson, M. A., & Hedge, J. W. (1997).
  • Personnel Selection. Annual Review of Psychology, 48, 299–337.
  • Robertson, I. T., & Smith, M. (2001). Personnel selection. Journal of Occupational and Organizational Psychology, 74(4), 441–472.
  • Hough, L. M., & Oswald, F. L. (2000). Personnel selection: Looking toward the future – remembering the past. Annual Review of Psychology, 51, 631–664.
  • Lievens, F., Van Dam, K., & Anderson, N. (2002). Recent trends and challenges in personnel selection. Personnel Review, 31(5–6), 580–601.
  • Beckers, A. M., & Bsat, M. Z. (2002). A DSS classification model for research in Human Resource Information Systems. Information Systems Management, 19(3), 41–50.
  • Kovach, K. A., & Cathcart, C. E. (1999). Human Resource Information Systems (HRIS): Providing business with rapid data access, information exchange and strategic advantage. Public Personnel Management, 28(2), 275–282.
  • Hooper, R. S., Galvin, T. P., Kilmer, R. A., & Liebowitz, J. (1998). Use of an expert system in a personnel selection process. Expert Systems with Applications, 14(4), 425–432.
  • Nussbaum, M., Singer, M., Rosas, R., Castillo, M., Flies, E., Lara, R., et al. (1999). Decision support system for conflict diagnosis in personnel selection. Information & Management, 36(1), 55–62.
  • Liao, S. H. (2003). Knowledge management technologies and applications – literature review from 1995 to 2002. Expert Systems with Applications, 25, 155–164.

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  • A Cognitive Ability based Decision System for Enhancing the Industry Growth using Data Mining Techniques

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Authors

Charles Savarimuthu
Department of IT, Al Musanna College of Technology, Muladdah Musanna, Sultanate of Oman, Oman
Lenin Jeevanantham
Department of IT, Al Musanna College of Technology, Muladdah Musanna, Sultanate of Oman, Oman
C. Kavitha
Department of IT, Al Musanna College of Technology, Muladdah Musanna, Sultanate of Oman, Oman

Abstract


This research work focuses on industry objectives like employees’ performance study based on personality and Emotional behavior. The major objective is to identify the potential of employees in the working environment. The sub objectives are analyzing the employees’ personalities and draw out the information person’s motivation, preferences, a person’s interests, identifying the emotional make-up with people and situations. Eynseck Personality Inventory (EPI) is used to classify the employees’ personality. Likert scale is used to measure the emotionality of an employee. Association rule mining is used to identify the hidden patterns among the set of attributes based on interesting measures. The multilayer perception technique helps to classify employees’ ability by applying cross-validation. This analysis can be used to improve the employees’ capability and their behavior in the working environment. This study can be used to determine the employees’ performance and helps the industry management people to improve the industry growth by identifying the various capabilities of employees and their emotionality.


Keywords


Personality traits, Emotional Quotient, Association Rule, Multi-Layer Perceptron.

References