Implementation and Comparison of Coffee Bean Drying Temperature SettingsBased on Fuzzy Logic - Mohammad Ghassan Alghifari; Indah Suraswati; Kenji Restan Syahuri; David Zico Rafael Sitorus; Kevin Viriya Halim; Inna Novianty; Nanda Octavia; Ivan De Nerol (Journal of Applied Science, Technology & Humanities | JASTH, 2024)
This research examines the implementation and measurement of temperature in drying coffee beansusing a fuzzy logic approach. Two main methods, namely the Mamdani Method and the SugenoMethod, were applied and evaluated in this context. Data on temperature, humidity, and water contentof coffee beans are collected during the drying process for use in the implementation of both methods.Implementation is carried out using MATLAB software, with detailed steps for each method. TheMamdani method involves fuzzification processes, inference using fuzzy rules, and defuzzification toobtain concrete values for temperature settings. Meanwhile, the Sugeno Method also involvesfuzzification of input data, but uses a linear fuzzy model for inference, so it does not require adefuzzification stage. The results and discussion of this study highlight the performance differencesbetween the two methods. Evaluation is carried out based on temperature prediction accuracy andenergy efficiency. The Mamdani Method shows good accuracy in predicting temperature, while theSugeno Method highlights efficiency and efficiency in the temperature regulation process. Therefore,this study provides valuable insight into selecting a suitable method for temperature regulation ofcoffee bean dryers