Decision Support Model to Determine the Best Employees (Mechanic) using Fuzzy Logic and Profile Matching

0Citations
Citations of this article
23Readers
Mendeley users who have this article in their library.

Abstract

In a company, verifying the best employees is practically very essential. Knowing the best employees or understanding each employee's performance can be an advantage for the company to evaluate the whole company's performance and improve the lack. Determining the best employees is also necessary for giving appreciation to employees and is expected to be able to expand the performance and morale of employees. This study aims to build a Decision Support Model (DSM) to determine the best employee using a combination of fuzzy logic and profile matching methods. In developing the model, there are twelve selected parameters considered; i.e., performance problem diagnosis, problem-solving, preventive action, concept, time management, disciplinary, work management, efficiency, education, support skills, and business workflow. Finally, the model has been methodologically constructed. It is operated in determining the best employee (especially for mechanic staff in workshop) thru evaluating all employees' performance

References Powered by Scopus

Is there a need for fuzzy logic?

1157Citations
N/AReaders
Get full text

Getting more work for nothing? Symbolic awards and worker performance

197Citations
N/AReaders
Get full text

A survey of decision support system applications (1988-1994)

116Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Aljofarinski, H. J. A., & Utama, D. N. (2022). Decision Support Model to Determine the Best Employees (Mechanic) using Fuzzy Logic and Profile Matching. Journal of Computer Science, 18(6), 540–554. https://doi.org/10.3844/jcssp.2022.540.554

Readers over time

‘22‘23‘240481216

Readers' Seniority

Tooltip

Lecturer / Post doc 4

57%

PhD / Post grad / Masters / Doc 3

43%

Readers' Discipline

Tooltip

Computer Science 5

71%

Business, Management and Accounting 2

29%

Save time finding and organizing research with Mendeley

Sign up for free
0