Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Applied Science, Technology & Humanities
Fannan Cakti Wibisono
College of Vocational Studies, IPB University
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Social Sciences

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
The Effect of Temperature, Weight and Roasting Time on the Roasted Level of Coffee Beans Using Fuzzy Logic Fannan Cakti Wibisono; Chika Hayya Sabillah; Muhammad Faiz Assariy; Daffa Zulqisthi; Amanda Catur Sukmarani; Putri Alya Faisal; Muhammad; Cut Mesya Meuthia; Farida Fadhilatun Nisa; Nuriah Nurani Muhsin; Lukie Trianawati
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 3 (2025): June 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/crtn5j19

Abstract

This study examines the effect of temperature, roasting time, and coffee bean weight on the maturity level of roasted coffee beans, utilizing fuzzy logic to model and predict optimal roast outcomes. Coffee bean roasting level, a critical factor in determining flavor, is assessed using Mamdani-type fuzzy logic, which takes three input parameters—temperature, time, and weight—divided into ranges for specific roast outcomes. Case study parameters, including a coffee bean weight of 450 grams, roasting time of 39 minutes, and temperature of 130°C, were analyzed to classify the roast maturity. The fuzzy logic output indicates that this specific case falls within the medium roast level by the similarity of centroid between moment calculation and matlab calculation is 10,7, demonstrating the model's capability to provide precise roast classifications. This structured approach to evaluating coffee roasting parameters contributes to enhancing consistency and quality in the coffee industry, highlighting the potential of fuzzy logic for robust decision support in coffee quality control.
Co-Authors Amanda Catur Sukmarani Chika Hayya Sabillah Cut Mesya Meuthia Daffa Zulqisthi Farida Fadhilatun Nisa Lukie Trianawati Muhammad Muhammad Faiz Assariy Nuriah Nurani Muhsin Putri Alya Faisal