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Optimizing Fresh Orange Juice Production at XYZ MSME Bogor Using Forecasting and Sugeno Fuzzy Logic Yusup Cahyadi; Wuliddah Tamsil Barokah; Annisa Raihanah Maimun; Mrr Lukie Trianawati; Najla Athaya; Khaula Amanda; Farhana Adinda Zuhro; Dinar Lukmanudin; Devi Suryani; Christine Amara Tirza; Azhara Paramita; Roma Juliana Arios
Journal of Applied Science, Technology & Humanities | JASTH Vol. 2 No. 5 (2025): November 2025
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/ed1av543

Abstract

Determining the optimal daily production quantity is a major challenge for XYZ MSME, a small-scale fresh orange juice producer in Bogor, due to fluctuating demand and the perishable nature of its products. The purpose of this research is to forecast daily production using the Sugeno fuzzy logic method to minimize overproduction and underproduction. The study employs a Sugeno fuzzy inference system (FIS) with input variables including previous day sales and available raw materials. A set of fuzzy rules maps these inputs to recommended production quantities. The results show that the Sugeno FIS produces accurate and adaptive forecasts that closely match actual demand patterns, enabling XYZ MSME to adjust production efficiently. This method helps reduce raw material waste, optimize resource use, and improve overall production efficiency. The study concludes that applying the Sugeno fuzzy logic approach is effective for short-term production planning in MSMEs, particularly for perishable food products.