Penerapan Metode MAUT dalam Penentuan Kelayakan Tenaga Kerja Indonesia Keluar Negeri dengan Pembobotan ROC
- Leonardo Ginting Institut Teknologi dan Bisnis Indonesia, Medan, Indonesia
- Edelweis Edelweis Institut Teknologi dan Bisnis Indonesia, Medan, Indonesia
- Irpanto Irpanto Institut Teknologi dan Bisnis Indonesia, Medan, Indonesia
- Zulima Berkat Hulu Institut Teknologi dan Bisnis Indonesia, Medan, Indonesia
-
David JM Sembiring
*
Institut Teknologi dan Bisnis Indonesia, Medan,
Indonesia
- Asprina Br Surbakti Institut Teknologi dan Bisnis Indonesia, Kabanjahe, Indonesia (*) Corresponding Author
Abstract
Determining the eligibility of Indonesian Migrant Workers (TKI) to travel abroad is a complex process because it involves many criteria that must be considered objectively. This study proposes the application of the Multi-Attribute Utility Theory (MAUT) method in decision-making by weighting criteria using the Rank Order Centroid (ROC) method. The ROC method is used to generate criteria weights based on priority levels, thus providing a fairer proportion in the calculation. Furthermore, the MAUT method is used to normalize the data, calculate utility values, and determine the final score of each alternative. The purpose of this study is to develop a Decision Support System model that can help determine the eligibility of Indonesian Migrant Workers (TKI) to travel abroad more objectively, measurably, and systematically, so that the selection process does not only rely on subjective considerations, but also uses a quantitative approach to improve the accuracy of the decision results. This study uses five assessment criteria with ten alternatives as data samples. The calculation results show that criteria with higher priorities have a significant influence on the final result. From the data processing process, it was obtained that Alternative A7 had the highest preference value of 0.945 and was recommended as the best alternative, followed by A3 with a value of 0.926 and A9 with a value of 0.865, while the alternative with the lowest score was A8 with a value of 0.608. The results of this study prove that the integration of the ROC and MAUT methods can produce an objective, transparent, and systematic decision support system in determining the feasibility of alternatives, as well as assisting decision makers in a more accurate and measurable selection process.
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Copyright (c) 2025 Leonardo Ginting, Edelweis Edelweis, Irpanto Irpanto, Zulima Berkat Hulu, David JM Sembiring, Asprina Br Surbakti
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