RAM-MEREC (Root Assessment Method - Method based on Removal Effects of Criteria): A Synergistic Approach to Weight Derivationand Alternative Ranking in the Selection of the Best Intern Employees
- Permata Permata Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia
- Junhai Wang Zhejiang Technical Institute of Economics, Zhejiang, China
-
Setiawansyah Setiawansyah
*
Universitas Teknokrat Indonesia, Bandar Lampung,
Indonesia
- A. Ferico Octaviansyah Pasaribu Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia
- Agung Deni Wahyudi Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia (*) Corresponding Author
Abstract
An effective intern selection process requires an objective and systematic approach to decision-making, especially when it involves multiple assessment criteria. This study proposes a combined approach of RAM-MEREC, which is a combination of Method based on Removal Effects of Criteria (MEREC) and Root Assessment Method (RAM), as a method to improve accuracy and reliability in the best internal selection. MEREC is used to objectively determine the weight of criteria based on the impact of the elimination of each criterion on the overall outcome. Meanwhile, RAM is used to generate alternative rankings by considering the root impact of value changes on each candidate's performance. The results of the application of this method show that RAM-MEREC is able to provide a more representative weighting and a more stable and consistent final ranking. The results of the application of this method show that RAM-MEREC is able to provide a more representative weighting and a more stable and consistent final ranking. The results of the calculation of the total score of all alternatives using the evaluation method that has been determined, obtained that Alternative 10 is the best candidate with the highest score of 1.4378, followed by Alternative 6 with a score of 1.4375 and Alternative 3 with a score of 1.4375. This approach not only improves the quality of decision-making, but also minimizes subjectivity and bias in the selection process.
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Copyright (c) 2025 Permata Permata, Junhai Wang, Setiawansyah Setiawansyah, A. Ferico Octaviansyah Pasaribu, Agung Deni Wahyudi
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