This study addresses the lack of structured, data-driven approaches for selecting social media platforms in higher education marketing, focusing on Universitas Klabat. Although platforms such as Instagram, Facebook, WhatsApp, TikTok, and YouTube reach millions of Generation Z users in Indonesia, decisions about which platforms to prioritize are often intuitive rather than based on measurable criteria. To overcome this, a hybrid fuzzy multi-criteria decision-making model combining Fuzzy-Best Worst Method (Fuzzy-BWM) and Fuzzy-MARCOS is proposed. Three marketing experts evaluated five platforms against five criteria: Engagement, Target Audience, Send/Receive Message, Content Richness, and Cost, using linguistic terms converted into triangular fuzzy numbers. Fuzzy-BWM was used to derive criteria weights with a Consistency Ratio below 0.025; the defuzzified weights show Engagement as the most influential criterion (0.362), followed by Target Audience, Send/Receive Message, and Content Richness (0.182 each), while Cost is least important (0.092). Fuzzy-MARCOS then normalized, weighted, and aggregated platform performances to compute utility scores. The final crisp utilities indicate that Instagram and Facebook are the best platforms (1.2045), followed by WhatsApp (1.0906), with TikTok (0.9778) and YouTube (0.9689) ranking lowest. The model offers a reusable, transparent decision-support tool for university digital marketing
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