Sistem Pendukung Keputusan Pemilihan Saham Terbaik Indonesia Dengan Menggunakan Metode Weighted Product dan ELECTRE

This study develops a Decision Support System (DSS) for Selecting the Best Stocks using the ELECTRE and Weighted Product (WP) methods based on six financial criteria, namely Net Profit Margin (NPM), Return on Equity (ROE), Earnings per Share (EPS), Price-to-Earnings Ratio (PER), Debt-to-Equity Ratio (DER), and Price-to-Book Value (PBV), and develops a Python CLI-based application. The research subjects are companies listed on the main board of the Indonesia Stock Exchange (IDX) that have published their financial reports for the last quarter of 2025 and have non-negative PER, EPS, and PBV values, resulting in a sample of 109 stocks. The accuracy and relevance of the method were tested by comparing the ranking results against actual stock returns for the first quarter of 2026 using Spearman’s correlation. The results show that WP method obtained a coefficient of 0.27777, while ELECTRE obtained 0.10994. Both methods showed a weak to very weak correlation with actual returns, but WP consistently produced a higher correlation. Thus, WP method is more suitable for a stock selection decision support system based on the research dataset and criteria than ELECTRE method.