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
Aliya Fidella
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 
Application of Fuzzy Logic in Tempe Production Using the Tsukamoto Algorithm Daffa Zulqisthi; Muhammad Faiz Assariy; Mrr Lukie Trianawati; Syafira Aristawidya; Chandradewi Ekaputri; Hafizhah Nur Humairah; Gita Aisy Affatunnisa; Aliya Fidella; Muhammad Ghifari Fazan Putra; Chika Hayya Sabillah
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 4 (2025): September 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/aygmd359

Abstract

Fuzzy logic is widely used in various fields to formalize human behavior by considering inaccurate or partial reasoning. This study implements the Tsukamoto fuzzy logic method to analyze tempe production based on demand and inventory data. The research utilizes library research methods and data analysis using MATLAB (Matrix Laboratory). The Tsukamoto method was chosen for its high tolerance for data and flexibility. The system uses two input variables: demand and inventory, with output being production quantity. The fuzzy sets for demand are categorized as "Decrease" and "Increase" with a domain of [1000; 2000], inventory as "Few" and "Many" with a domain of [100; 600], and production as "Decrease" and "Increase" with a domain of [1520; 2100]. Using four fuzzy rules and the defuzzification process, the system can predict optimal production quantities. For example, with a demand of 1500 and inventory of 400, the system calculates a production quantity of 1823 units. This implementation demonstrates the effectiveness of the Tsukamoto method in automating production decisions based on demand and inventory variables.
Co-Authors Chandradewi Ekaputri Chika Hayya Sabillah Daffa Zulqisthi Gita Aisy Affatunnisa Hafizhah Nur Humairah Mrr Lukie Trianawati Muhammad Faiz Assariy Muhammad Ghifari Fazan Putra Syafira Aristawidya