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All Journal Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) KLIK: Kajian Ilmiah Informatika dan Komputer BEES: Bulletin of Electrical and Electronics Engineering Bulletin of Informatics and Data Science Jurnal Informatika dan Rekayasa Perangkat Lunak
Arshad, Muhammad Waqas
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COMBINATION OF LOGARITHMIC PERCENTAGE CHANGE-DRIVEN OBJECTIVE WEIGHTING AND MULTI-ATTRIBUTIVE IDEAL-REAL COMPARATIVE ANALYSIS IN DETERMINING THE BEST PRODUCTION EMPLOYEES Hadad, Sitna Hajar; Subhan, Subhan; Setiawansyah, Setiawansyah; Arshad, Muhammad Waqas; Yudhistira, Aditia; Rahmanto, Yuri
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.3.2057

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 1st place, YP employees get 2nd place, and AJL employees get 3rd place.
Co-Authors Aditia Yudhistira Asistyasari, Ayuni Desyanti Heni Sulistiani Iryanto Chandra Mesran, Mesran Palupiningsih, Pritasari Putra, Ade Dwi Rasli, Roznim Mohamad Ryan Randy Suryono Sanriomi Sintaro Setiawansyah Setiawansyah Sitna Hajar Hadad Subhan Subhan Sufiatul Maryana Sumanto Sumanto Very Hendra Saputra Yosep Nuryaman Yuri Rahmanto