Decision Support System Perspective Using Entropy and Multi-Attribute Utility Theory in the Selection of the Best Division Head
DOI:
https://doi.org/10.30865/mib.v8i2.7603Keywords:
Combination, Decision-Making, Division Head, Entropy Weighting, MAUT Method,Abstract
The Division Head is a figure responsible for the management, coordination, and supervision of a division in an organization. Its main tasks include the development of strategy, planning, and implementation of operational activities of the division in accordance with organizational objectives. Problems in choosing the best Division Head often arise due to various complex factors. One of the main problems is the lack of clear and objective criteria in determining the suitability of candidates to the duties and responsibilities of the division's leadership. The combination of entropy weighting with the MAUT (Multi-Attribute Utility Theory) method is an approach that combines two decision-making analysis techniques. First, entropy weighting is used to determine the relative weight of each attribute used in the analysis. This technique helps measure the degree of uncertainty or randomness in the data, so attributes that have higher variation will be given a lower weight. Once attribute weights are determined, the MAUT method is used to evaluate and compare decision alternatives based on the subjective preferences of the decision maker. MAUT allows decision makers to assess and assign the relative utility value of each decision alternative to each attribute taken into account. By combining these two techniques, decision makers can obtain more accurate and structured results in complex decision making, taking into account both data variation and subjective preferences. The results of the alternative ranking of the best division head selection showed results for the Head of Information Technology (IT) Division with a value of 0.6918 ranked 1, Head of Quality Division with a value of 0.5242 got rank 2, and Head of Human Resources (HR) Division with a value of 0.4221 got rank 3.
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