Sistem Pendukung Keputusan Pemilihan Saham Investor Pemula Berbasis Web Fuzzy TOPSIS - Bagas Tri Pamungkas; Abdullah Muhajir (Sekolah Tinggi Manajemen Informatika dan Komputer AUB - Indonesia, 2026)
Novice investors often experience difficulties in selecting appropriate stocks due to limited understanding of fundamental analysis and high subjectivity in decision-making. This condition may lead to suboptimal investment decisions. This study aims to develop a web-based Decision Support System (DSS) to assist novice investors in stock selection using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) method. The Fuzzy TOPSIS method is applied to handle uncertainty in data and criteria assessment through a fuzzy logic approach. The criteria used include Price Earning Ratio (PER), Price to Book Value (PBV), Earnings Per Share (EPS), Net Profit Margin (NPM), Debt to Equity Ratio (DER), Return on Equity (ROE), and Dividend Payout Ratio (DPR). The system was developed using the Extreme Programming (XP) method and implemented as a web-based application. The results show that the system is able to generate objective and measurable stock rankings based on their closeness to the ideal solution. Therefore, this system is expected to improve investment decision quality and enhance financial literacy among novice investors.