Analysis of The Most Effective Advertising Platform Selection Decision Support System Using The Analytical Hierarchy Process (AHP) Method - Laela Rahmawati; Wahit Desta Prastowo (novamindpress, 2026)
This study aims to determine the most effective digital advertising platform among Google Ads, Meta Ads, and TikTok Ads by applying a Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) method. The research addresses the growing challenge faced by digital marketers in allocating advertising budgets effectively across multiple platforms with different strengths and audience characteristics. Analytical Hierarchy Process (AHP) was selected because of its ability to decompose complex multi-criteria decision-making problems into a structured hierarchical model. The analysis employed three main criteria: Cost, Target Audience, and Conversion. Pairwise comparisons and consistency testing were conducted based on expert judgments to ensure reliable evaluation results. The findings revealed that Conversion was the most influential criterion with the highest Eigen Vector (EV) value of 0.545, followed by Target Audience (0.273) and Cost (0.182). Through Global Synthesis analysis, Meta Ads achieved the highest total EV value of 0.3832, slightly outperforming Google Ads (0.3806), while TikTok Ads ranked third (0.2366). The results indicate that strong audience-targeting capabilities combined with competitive conversion performance make Meta Ads the most effective platform overall. This study provides strategic recommendations for advertisers and digital marketers to optimize advertising budget allocation based on business priorities and campaign objectives based on decision support system.