Penerapan metode fuzzy sugeno untuk prediksi persediaan bahan baku
Author(s) -
Julio Warmansyah,
Dida Hilpiah
Publication year - 2019
Publication title -
teknois jurnal ilmiah teknologi informasi dan sains
Language(s) - English
Resource type - Journals
eISSN - 2597-8918
pISSN - 2087-3891
DOI - 10.36350/jbs.v9i2.58
Subject(s) - fuzzy logic , raw material , defuzzification , statistics , operations research , safety stock , computer science , mean absolute percentage error , stock (firearms) , fuzzy number , operations management , mathematics , engineering , fuzzy set , business , mean squared error , artificial intelligence , mechanical engineering , supply chain , marketing , chemistry , organic chemistry
PT. Cahaya Boxindo Prasetya is a company engaged in the manufacture of carton boxes or boxes. The company's activities also include cutting and printing services using machinery and human power. The problem faced in this company is the difficulty of predicting the amount of inventory of raw materials that will be included in the production. The remaining raw materials for production will be used as the final stock to get the minimum, the goal is to reduce excess stock Overcoming this problem, fuzzy logic is used to predict raw material inventories by focusing on the final stock. In this study using Fuzzy Sugeno, with three input variables, namely: initial inventory, purchase, production, while the output is the final stock. Determination of prediction results using defuzzification using the average concept of MAPE (Mean Absolute Percentage Error). The results obtained, using the Fuzzy Sugeno method can predict the inventory of raw materials with a MAPE value of 38%.
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