Fuzzy Logic Approach to Determine Apple Maturity for Harvesting Decision - Muhammad Rafi Andika Wijaya; Wuliddah Tamsil Barokah; Annisa Raihanah Maimun; Mrr Lukie Trianawati; Syadza Afifah Nuri; Senja Surya Gama; Putri Nurbaiti; Nisrina Fatin Nadra; Fional Alvina Nirmala Putri; Ayu Nur Fadhila; Anindya Salsabila Hamdani Putri; Roma Juliana Arios (Batrisya Education, 2026)
This study aims to develop a fuzzy logic–based system for determining the maturity level of Anna apples as a basis for harvest decision-making. Five key parameters were used as input variables: Flesh Firmness (FF), Soluble Solid Content (SSC), Starch Pattern Index (SPI), Total Acidity (TA), and Hue°, with one output variable representing the maturity level (unripe, ripe, and overripe). The research employed a literature review method with a qualitative descriptive approach by collecting data from scientific journals and relevant documents discussing apple maturity and the application of fuzzy logic in agriculture. Data analysis was conducted using MATLAB through processes including fuzzification, formulation of If–Then rules, Mamdani inference, and defuzzification to produce a crisp output value representing apple maturity. The results indicate that the fuzzy logic system effectively models apple maturity parameters and provides accurate, objective, and efficient decisions compared to conventional subjective methods. The application of fuzzy logic offers a non-destructive classification method that assists farmers in determining the optimal harvest time, improving post-harvest quality, and maintaining product consistency.