Sistem Pendukung Keputusan Pemilihan Broker Saham Menggunakan Metode AHP dan SAW

Abstract

The capital market, particularly stocks in Indonesia, has experienced significant growth post-COVID-19 pandemic, with the number of investors currently reaching 18 million people, dominated by Generation Z and Millennials. However, this rapid growth presents a new practical challenge: the hesitation among beginner investors in selecting the right brokerage firm due to the multitude of available alternatives, a phenomenon known as choice paralysis. An incorrect broker selection can lead to financial losses caused by unfriendly interfaces, high transaction fees, and slow service response. This research aims to develop a Decision Support System (DSS) to produce an objective, data-driven ranking of stock brokers, thereby minimizing operational loss risks and improving investment decision-making efficiency for beginner investors. The methodology employed combines Simple Additive Weighting (SAW) for ranking and Analytical Hierarchy Process (AHP) for criteria weighting, applied to seven evaluation criteria: transaction fees, virtual trading simulation, e-IPO features, educational features, popularity, minimum deposit, and community features. The AHP consistency test produced a Consistency Ratio of 0.004, confirming data validity. Results show that the minimum deposit criterion received the highest weight (33.61%), followed by virtual trading simulation (32.20%). The system ranked Stockbit first (V=0.9948), followed by IPOT (0.9533) and Ajaib (0.6265). Confusion Matrix validation yielded 60% accuracy, precision, and recall, while User Acceptance Testing produced an average acceptance score of 88.46%, categorized as highly acceptable.