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All Journal Scientica: Jurnal Ilmiah Sains dan Teknologi
Muhammad Rafif Novanil
Universitas Logistik dan Bisnis Internasional
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences Other

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OPTIMALISASI JUMLAH PRODUKSI TEH BOTOL SOSRO DAN FRUIT TEA MENGGUNAKAN METODE FUZZY INFERENCE SYSTEM TSUKAMOTO : (STUDI KASUS : PT. SINAR SOSRO PALEMBANG) Dudi Hendra Fachrudin; Nurlaela Kumala Dewi; Muhammad Rafif Novanil
Scientica: Jurnal Ilmiah Sains dan Teknologi Vol. 1 No. 3 (2023): Scientica: Jurnal Ilmiah Sains dan Teknologi
Publisher : Komunitas Menulis dan Meneliti (Kolibi)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.572349/scientica.v1i3.362

Abstract

PT Sinar Sosro Palembang, a manufacturing company of packaged ready-to-drink beverages, is experiencing constraints in the amount of production that is not optimal, causing excess inventory stock and potential losses. Demand fluctuations are the main factor affecting production instability. To overcome this problem, researchers used the Tsukamoto Fuzzy Inference System method in this study. This method utilizes fuzzy sets to represent rules in real-world problems. With input variables of demand and inventory, this method generates output variables of production. The fuzzy set on each variable is applied with a defuzzification process using a centered average calculation. The results show that there are still production periods that are not optimal, as seen in the production data of Sosro Bottled Tea and Fruit Tea bottles. With 8 optimal calculations from 12 total data for Sosro Bottled Tea and 6 optimal calculations from 12 total data for Fruit Tea bottles, the Tsukamoto Fuzzy Inference System method is considered feasible as a consideration for obtaining the optimal amount of production for PT Sinar Sosro Palembang. The implementation of this method is expected to improve production efficiency and reduce excess inventory stock, resulting in more optimal production performance.
Co-Authors Dudi Hendra Fachrudin Nurlaela Kumala Dewi