Analisis Perbandingan Metode WASPAS dan TOPSIS dengan Menggunakan Pembobotan ROC dalam Sistem Pendukung Keputusan Penentuan Sales Sepeda Motor Terbaik

Determining the best motorcycle salesperson is an important aspect in improving sales performance and motivation in automotive companies. This process must be carried out objectively by considering various criteria, such as performance achievement, discipline, teamwork, communication skills and responsibility. However, decision making is often complex because it involves many factors and varying criteria. Therefore, a Decision Support System (DSS) is needed that is able to process and analyze data effectively. This study aims to analyze the comparison of two multi-criteria methods, namely Weighted Aggregated Sum Product Assessment (WASPAS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), in determining the best motorcycle salesperson. Both methods use Rank Order Centroid (ROC) weighting to give weight to the assessment criteria. Based on the results of the analysis, it can be seen that both methods provide consistent results, although there are differences in the final ranking. The results of the study indicate that the WASPAS and TOPSIS methods are equally effective in determining the best alternative, with differences in the order of priorities that can be used as further consideration by decision makers. The results of the two methods show that the alternative with the highest performance according to both methods is Febriansyah, who is in first place both in the TOPSIS method with a value of 0.796 and in the WASPAS method with a value of 0.810.