Sistem Rekomendasi Pemilihan Saham Blue-Chip di Bursa Efek Indonesia Menggunakan Fuzzy Mamdani - Dandi, Muhammad Khairil; Kurniawan, Rakhmat (TIN: Terapan Informatika Nusantara, 2025)
The Indonesian capital market plays an important role in supporting national economic growth, particularly through stock investments. Blue-chip stocks are considered stable and have the potential to provide long-term returns, yet selecting the right ones remains a challenge for investors. This study aims to develop a recommendation system for selecting blue-chip stocks on the Indonesia Stock Exchange (BEI) using the Fuzzy Mamdani method. The research data were collected from a set of actively traded blue-chip stocks within a specific period and analyzed using four main variables: stock price, trading volume, market capitalization, and financial ratios. The recommendation process involves fuzzification, the formulation of 15 rule bases established through expert consultation with market analysts, Mamdani inference, and defuzzification to produce recommendation scores. The implementation results show that the system achieved an accuracy level of 84.65%, indicating stable consistency with actual market conditions. These findings confirm that the Fuzzy Mamdani method is effective in generating objective and systematic recommendations for blue-chip stock selection. The developed system successfully meets the research objective by assisting investors in identifying suitable stocks based on data-driven analysis.