Application of OCRA Method with ROC Weighting in Selection of Best Prudential Agent
DOI:
https://doi.org/10.64366/ijids.v1i1.12Keywords:
Agent; OCRA Method; ROC Method; Decision Support SystemAbstract
The problem that often arises is the gap in the selection of the best agents which was previously influenced by a lack of objectivity in recruiting, and many agents do not match the existing knowledge and criteria. The impact is a discrepancy in selecting the best agent with predetermined criteria, resulting in stagnation and disrupting overall operations. This condition risks damaging the smooth operation and disrupting the achievement of the desired goals. Thus, it is necessary (DSS) to assist in the process of selecting the best agent. The solution is to apply the OCRA method using ROC weighting. The application of the OCRA method with ROC weighting is expected to provide an optimal solution in selecting the best agent based on predetermined criteria. This method was chosen because it is able to determine the weight value for each attribute. From the preference assessment, it can be seen that the value of 0.833 has the highest value. Therefore, it can be concluded that in the tenth alternative (A10), there is a choice that is considered the best agent. This choice was given to Lastri Simbolon, who was ranked as the best agent.
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