Evaluate the Performance of Best Employees in Human Resources (HR) Working Using TOPSIS Method

An organization cannot be separated from the role of human resources (HR) working within it. The quality of human resources is one of the necessary factors for improving the performance of an organization. Therefore, a company should evaluate the performance of its employees to understand their potential and the importance of evaluating their abilities and qualities. This evaluation allows for judgments on the worst qualities and the significance of employees. Employees are the foundation of a strong and enduring organization, regardless of their level. Their strength, commitment, dedication, and emotional connection with the organization cannot be measured solely in monetary value. What is Research Methodology? Research methodology refers to the specific procedures or techniques used to identify, select, process, and analyze information about a topic. In a research paper, the methodology section enables the reader to critically evaluate the overall validity and reliability of the study. In this study, the TOPSIS method analyzes the ranking of Mercedes-Benz EQS as first, Audi e-tron GT as fourth, Porsche Taycan as fifth, Audi e-tron as third, Audi RS e-tron GT as second, and Mercedes-Benz EQC as sixth. Although the concept of EB is implicit within some organizations, it often appears vague. The underlying trend in the responses suggests that high skills and development were most important in consulting firms and investment banks, as well as large-scale industrial and manufacturing firms, where individuality of employees was less visible.”

Alao, D., Adeyemo, A.B.: Analyzing employee attrition using decision tree algorithms. Comput. Inf. Syst. Dev. Inform. Allied Res. J. 4 (2013) 756 Y. Zhao et al.

Al-Radaideh, Q.A., Al Nagi, E.: Using data mining techniques to build a classification model for predicting employees performance. Int. J. Adv. Comput. Sci. Appl. 3, 144–151 (2012)

Chang, H.Y.: Employee turnover: a novel prediction solution with effective feature selection. WSEAS Trans. Inf. Sci. Appl.417–426 (2009

) 4. Chien, C.F., Chen, L.F.: Data mining to improve personnel selection and enhance human capital: a case study in high-technology industry. Expert Syst. Appl. 34, 280–290 (2008)

Li, Y.M., Lai, C.Y., Kao, C.P.: Building a qualitative recruitment system via SVM with MCDM approach. Appl. Intell.

35, 75–88 (2011)

Nagadevara, V., Srinivasan, V., Valk, R.: Establishing a link between employee turnover and withdrawal behaviours: application of data mining techniques. Res. Pract. Hum. Resour. Manag. 16, 81–97 (2008)

Quinn, A., Rycraft, J.R., Schoech, D.: Building a model to predict caseworker and supervisor turnover using a neural network and logistic regression. J. Technol. Hum. Serv. 19, 65–85 (2002)

Sexton, R.S., McMurtrey, S., Michalopoulos, J.O., Smith, A.M.: Employee turnover: a neural network solution. Comput. Oper. Res. 32, 2635–2651 (2005)

Suceendran, K., Saravanan, R., Divya Ananthram, D.S., Kumar, R.K., Sarukesi, K.: Applying classifier algorithms to organizational memory to build an attrition predictor model

Tzeng, H.M., Hsieh, J.G., Lin, Y.L.: Predicting nurses’ intention to quit with a support vector machine: a new approach to set up an early warning mechanism in human resource management. CIN: Comput. Inf. Nurs. 22, 232–242 (2004)

Valle, M.A., Varas, S., Ruz, G.A.: Job performance prediction in a call center using a naive Bayes classifier. Expert Syst. Appl. 39, 9939–9945 (2012)

Haq, N.F., Onik, A.R., Shah, F.M.: An ensemble framework of anomaly detection using hybridized feature selection approach (HFSA). In: SAI Intelligent Systems Conference (IntelliSys), pp. 989–995, IEEE (2015)

Punnoose, R., Ajit, P.: Prediction of employee turnover in organizations using machine learning algorithms. Int. J. Adv. Res. Artif. Intell. 5, 22–26 (2016)

Sikaroudi, E., Mohammad, A., Ghousi, R., Sikaroudi, A.: A data mining approach to employee turnover prediction (case study: Arak automotive parts manufacturing). J. Ind. Syst. Eng. 8, 106–121 (2015)

McKinley Stacker, I.V.: IBM waston analytics. Sample data: HR employee attrition and performance [Data file]. Retrieved from https://www.ibm.com/communities/analytics/ watson-analytics-blog/hr-employee-attrition/ (2015)

Shahshahani, B.M., Landgrebe, D.A.: The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon. IEEE Trans. Geosci. R

Abbas, Anas Abdul Basit. Evaluate the performance of employees in public institutions in the Republic of Yemen and its impact on the efficiency of field-study analysis of the air transport sector of Yemen, Ph.D. thesis, Business Administration, Faculty of Economics and Rural Development, the University of the Island, Sudan, 2001.

Abbas, Suhaila Mohamed. Human Resources Management strategic entrance, the first edition, Dar Wael for Publishing and Distribution, Amman, Jordan, 2003.

Abdul Bali, Selah Al-Din, Muslim, Abdul Hadi, Hassan, narrator. Human Resources Management, the modern university office, Alexandria, Egypt, 2007.

Abdul Bali, Selah Al-Din. Human Resource Management practice and science, University House for printing, publishing and distribution, Alexandria, Egypt, 2000.

Abdul Raman, Bin Anta. Human Resources Management (Mufahim- Aloes-dimensional strategy), Arabic edition, Dar Yazouri Scientific Publishing and Distribution, Amman, Jordan, 2010.

Abu AL-Jaen, Tamer Yourself. 2010. The effect of obstacles EDM on the performance of the municipalities of Gaza-strip as applied to the study of the municipalities of Gaza-strip Gaza Strip, the study of the Master, the Islamic University, Gaza Palestine, 2010.

Abu Hate, Musa Mohammed. The reality of the performance of employees and assess its impact on the performance of employees in non-governmental health institutions in the Gaza Strip, the level of “a case study on the Patient’s Friends Society charity,” the study of the Master, the Islamic University, Gaza, Palestine, 2009.

Abu Made, Khalid Made. Impediments to the performance of employees in the Palestinian universities and ways to evaluate the treatment of his master, the Islamic University, Gaza, Palestine, 2007.

Abu Nasser SS, Al Shitake MJ, Abu Mauna YM. Knowledge Management Maturity in Universities and its Impact on Performance Excellence Comparative study, Journal of Scientific and Engineering Research. 2016; 3(4):4-14.

Abu Nasser SS, Al Shitake MJ, Abu Mauna YM. Measuring knowledge management maturity at HEI to enhance performance-an empirical study at Al-Zahra University in Palestine. International Journal of Commerce and Management Research. 2016; 2(5):55-62.

Sullivan, S. (2004). Making the business case for health and productivity management. Journal of Occupational and Environmental Medicine, 46(6), S56-S61.

Sheetal V. Hukkeri, “Evaluate the Performance of Best Employees in Human Resources (HR) Working Using TOPSIS Method”, REST Journal on Data Analytics and Artificial
Intelligence, 2(1), (2023):73-79.