Application of ANP Method and Fuzzy Inference System on New Product Selection and Production Capacity Determination of Fish Canning

Jember State Polytechnic has a fish canning teaching factory with a productivity of 7 q of fish per production. The canned fish product is a superior product, but the quality and type of products produced are low quality and less desirable. Therefore, product diversification is needed to increase the added value of canned fish. The fluctuating production capacity at teaching factory (TeFa) Fish Canning is an obstacle in determining production capacity according to market demand. The aim of this research is to diversify products and optimize fish canning products. This research was carried out using two methods, namely selecting superior products for TeFa fish canning using the Analytical Network Process (ANP) method and determining production capacity using the Fuzzy Inference System (FIS)-Tsukamoto method. The research results show that TeFa fish canning's superior product was determined by considering 4 criteria and 12 sub-criteria to produce tongkol balado with the highest weight value and followed by sardines with chili sauce, yellow seasoning tuna, and tuna salt solution. Simulation results for optimizing canned fish production are 5.7863 q/day which provides the optimum supply of canned fish. Keywords: Analytic Network Process (ANP), Fish canning, Fuzzy Inference System (FIS) Tsukamoto, New product selection, Production capacity.