Penerapan Fuzzy Multiple Attribute Decision Making (FMADM) dengan Pendekatan Simple Additive Weighting (SAW) dalam Pemilihan Investasi Saham Sektor Perbankan di Indonesia

Abstract

This research aims to develop a decision support system model for stock investment selection using the Fuzzy Multiple Attribute Decision Making (FMADM) method with a Simple Additive Weighting (SAW) approach. The study utilizes fundamental data from banking sector companies listed on the Indonesia Stock Exchange during the 2022–2024 observation period. The criteria used include Return on Assets (ROA), Return on Equity (ROE), Earning per Share (EPS), Net Profit Margin (NPM), Price to Book Value (PBV), Debt to Equity Ratio (DER), and Dividend Yield (DY). The results show that the integration of FMADM and SAW is capable of producing an investment evaluation process that is more objective, systematic, and transparent compared to conventional approaches. The developed model can assist investors in identifying stocks with the best fundamental performance based on various financial indicators simultaneously. This study contributes to the development of multi-criteria-based investment decision support systems and offers an effective alternative method to support investment decision-making in the Indonesian capital market.