Fuzzy Logic Design for Mocaf and Green Bean Flour Substitution Effect on Noodle Protein Content - Alysha Revalina Nugraha; Adinda Dwi Wahyuni; Ananti Nur Mala; Arifi Keisya Azahra; Aurelia Salsabila; Daffa Athallah Umbara; Naila Nabiha Fidzri; Soelthan Ramzy Kastio; Mrr. Lukie Trianawati; Wuliddah Tamsil Barokah; Annisa Raihanah Maimun; Roma Juliana Arios (Batrisya Education, 2025)
Wet noodles are widely consumed in Indonesia but have low protein content because they are made from wheat flour. Their nutritional value can be improved by substituting part of the flour with local ingredients such as protein-rich green bean flour and mocaf, which enhances texture. Previous studies showed that green bean flour increases protein, while mocaf has little effect. This study models the relationship between green bean flour and mocaf composition on protein content using Mamdani fuzzy logic, which effectively handles uncertain and non-linear data. Secondary data from three treatments MB2 (50:10), MB4 (30:30), and MB6 (10:50) were used. Two input variables (percentages of mocaf and green bean flour) and one output variable (protein content) were divided into three categories: low, medium, and high. The fuzzy process included fuzzification, rule formulation, inference using the min–max operator, and centroid defuzzification. Results showed that increasing green bean flour raised protein content, while excessive mocaf reduced it. The Mamdani method effectively modeled the relationship between ingredient composition and protein levels in wet noodles.