COMBINATION OF LOGARITHMIC PERCENTAGE CHANGE-DRIVEN OBJECTIVE WEIGHTING AND MULTI-ATTRIBUTIVE IDEAL-REAL COMPARATIVE ANALYSIS IN DETERMINING THE BEST PRODUCTION EMPLOYEES

Sitna Hajar Hadad; Subhan Subhan; Setiawansyah Setiawansyah; Muhammad Waqas Arshad; Aditia Yudhistira; Yuri Rahmanto

doi:10.52436/1.jutif.2024.5.3.2057

Sitna Hajar Hadad Computer Engineering, Akademi Ilmu Komputer Ternate, Indonesia
Subhan Informatics Management, Akademi Ilmu Komputer Ternate, Indonesia
Setiawansyah Informatics, Faculty Engineering and Computer Science, Universitas Teknokrat Indonesia, Indonesia
Muhammad Waqas Arshad Department of Computer Science and Engineering, University of Bologna, Bologna, Italy
Aditia Yudhistira Informatics, Faculty Engineering and Computer Science, Universitas Teknokrat Indonesia, Indonesia
Yuri Rahmanto Computer Engineering, Faculty Engineering and Computer Science, Universitas Teknokrat Indonesia, Indonesia

DOI: https://doi.org/10.52436/1.jutif.2024.5.3.2057

Keywords: Combination, Employees, LOPCOW, MAIRCA, Selection

Abstract

The problem that occurs in the selection of the best production employees is the lack of transparency and objectivity in the selection process. Without clear procedures and well-defined criteria, employee selection decisions can be influenced by subjective preferences or irrelevant non-performance factors. This can result in injustice in employee selection and lower the morale and motivation of unselected employees. The purpose of the combination of LOPCOW and MAIRCA in determining the best production employees is to provide a holistic and adaptive framework in the employee performance evaluation process. LOPCOW allows decision makers to dynamically adjust the weight of criteria according to the level of volatility or change in the relevant environment or situation. LOPCOW offers an adaptive and responsive approach in determining the weight of criteria, enabling decision makers to respond quickly to changes occurring in the relevant environment or situation. MAIRCA is an analytical method used to assist decision makers in evaluating and selecting alternatives based on several relevant criteria or attributes. MAIRCA provides a strong framework for decision makers to make more informed and informed decisions. Combining these two methods results in a more comprehensive and accurate understanding of production employee performance, thus enabling managers to identify the most effective employees and provide rewards or development accordingly. The final results of the ranking of the best production employees obtained by JR employees get 1^st place, YP employees get 2^nd place, and AJL employees get 3^rd place.

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