Sistem Pendukung Keputusan Menentukan Sales Terbaik Menerapkan Metode Simple Additive Weighting

Abstract

In this research, the author uses the SAW (Simple Additive Weighting) Method to determine the best salesperson at company. The SAW method is considered appropriate because it performs a weighted sum of the performance ratings for each alternative on all attributes. This research involves structured steps, starting with determining criteria, alternatives and weights that are relevant to the company context. The next process involves matrix preparation, normalization, and preference calculation. First of all, significant criteria for assessing sales performance have been determined. The sales alternatives to be evaluated have also been identified, and the weight given to each criterion is according to its importance in the company context. Then, a matrix containing sales performance data is created for the next calculation process. Each value in the matrix is normalized so that it can be compared fairly. After the normalization process is complete, the next step is to calculate preferences for each sales alternative. This involves multiplying each normalized value by the appropriate weight, then adding them to get a total preference value for each alternative. From these results, the best alternative is determined through a ranking process. The research results show that the 6th alternative, represented by Rahman Rianto, has the highest score with 0.879, making it the best seller. These recommendations are based on detailed analysis using the SAW Method, which provides valuable insight for company management in making decisions regarding the assessment and development of their sales performance. Thus, this research not only provides an understanding of the best sales performance, but also provides a strong foundation for sustainable decision making in the context of this company.