APPLICATION OF FUZZY LOGIC TO DETERMINE DAMAGE LEVELS IN PASTEURIZED MILK BASED ON RAW MILK QUALITY - Novianty Fauziyah; Chika Hayya Sabillah; Muhammad Faiz Assariy; Andity Indira Marchiana; Daffa Zulqisthi; Avril Berlian Dima; Nadya Nafilah; Diva Nurina Aurelia; Raissa Nelvandra Putri; Muchammad Adham Nugraha; Mrr. Lukie Trianawat (Batrisya Education, 2025)
Milk is a highly nutritious food obtained from milking animals. One way to process milk so that it lasts a long time is by pasteurization. This study aims to develop a pasteurized milk damage level assessment system based on fuzzy logic based by considering factors such as temperature, storage time, pH, and the number of social cells. The method used in this study is a qualitative descriptive method with a literature study approach to collect secondary data from various relevant sources. The milk damage assessment system is designed using Fuzzy Inference System Mamdani, where each input variable is regulated by a trainee membership function. The results show that the system can provide a more accurate and adaptive assessment in determining the risk of milk damage, specified through the fuzzy rule evaluation designed for each combination of input conditions. This system is expected to support better decision making in maintaining the quality of pasteurization.