Implementation of Fuzzy Logic in Determining the Acceptance Status of Fresh Milk Based on pH and Density - Ahmad Daffa Naufal Ziddani; Fiqri Nurfadillah; Muhammad Danang Mukti Darmawan; Ester Angeline; Nanda Octavia; Syahla Aqilah; Salsabila Arina Pramudita; Wianda Aghnia Salsabila; Febby Aurellya; Novi Giotta Hutapea; Asochia Naomi Sitohang; Assadel Zhafif Alwaini; Ayu Shakira Nur Riawan; Aqila Asysyakur; Difa Mukmilatul Kautsar; Raisa Fasya; Luluah Sabrina Putri; Mrr Lukie Trianawati (Batrisya Education, 2024)
Fuzzy logic, known as fuzzy set theory, has become widely used to deal with uncertainty in research data processing. Fuzzy logic methods are known for their ease of implementation in machine language environments and their effectiveness in combining machine language representations with humanlanguage with an emphasis on meaning or importance. Fuzzy logic maps input space to output space, and this concept is closely related to dealing with uncertainty in data. In applying fuzzy logic in this study, the variables pH and density of milk are considered inputs whose value ranges are divided into low, medium, and high categories. The result of the fuzzy system is the acceptability state of fresh milk. By applying this method using MATLAB software, the simulation results show that at a milk pH of 6.2 and a specific gravity of 1.0320, the acceptability state of fresh milk is 30. After the defuzzification process and manual calculation, the final result is 29.30 30. From these results, fuzzy logic provides high accuracy to support progressive decision-making. This allows the system to consider the complexity of milk quality criteria that cannot always be measured in a binary way (e.g., good or bad), resulting in more precise and accurate decisions.