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Fuzzy Inference System for Evaluating Supplier in Shrimp Agroindustry
Lely Herlina (a*), Machfud (b), Elisa Anggraeni (b), Sukardi (b)

a) Industrial Engineering Department, Faculty of Engineering, University of Sultan Ageng Tirtayasa,

b) Department of Agroindustrial Technology, Faculty of Agricultural Technology, IPB University


Shrimp agroindustry deals with processing raw shrimp into various frozen shrimp products. The production of frozen shrimp products are continuously made based on consumer demand with uncertain pattern. To sustain this production, raw materials, which in this case is, raw shrimp have to be continuously available at all times. Therefore, working integratedly with suppliers to satisfy customer demand is a fundamental goal for shrimp agroindustry. A selection of suppliers in agroindustry is determined according to three criteria, namely the quality of raw materials, delivery time, and payment scheme. These criteria are used as a measurement to evaluate supplier perfomances by decision makers. To minimize uncertainty and subjectivity of decision makers when choosing suppliers, a fuzzy inference system method is proposed. The outcomes of the fuzzy inference system method are a set of rule base that is used to evaluate suppliers in shrimp agroindustry

Keywords: fuzzy inference system, supplier selection, criteria, rule base

Topic: Industrial Engineering


Conference: Broad Exposure on Science and Technology (BEST 2019)

Plain Format | Corresponding Author (Lely Herlina)

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