Implementation of the Multi Attribute Utility Theory (MAUT) Method for Selecting the Best Affiliate Marketing - Mubarok, Wahib; Efendi, Tino Feri; Rokhmah, Siti (Jurnal Bumigora Information Technology (BITe), 2024)
Background: Digital marketing has become crucial for companies to remain relevant and grow. One common marketing strategy used is through collaboration with affiliate marketing. However, many companies still need help selecting the best affiliate marketing, often relying on subjective approaches. Objective: This research aims to develop a Decision Support System (DSS) using the MAUT method to choose the best affiliate marketing in the digital marketing industry. Method: This research method involves applying the MAUT method to identify normalization value variations among affiliate marketing options, resulting in a ranking of affiliate marketers. Result: The results of this research show that Sugiharto, Rifan Jauhari, and Nina Dwi Lestari rank the highest, with respective preference values of 0.8750 and 0.8625. Conclusion: The developed DSS successfully manages affiliate marketing data, providing valuable information for decision-making processes. This study contributes significantly to data management and marketing and has potential applications in various business contexts.