Proposed Control of Raw Material Inventory in Condition of Not Required With Fuzzy Mamdani Method in Cv. Pinus Bag's Specialist
CV. Pine Bag’s Specialist is a business engaged in the manufacturing of various types of bags. One of the bags made in the form of a backpack. Parachute fabric is the main raw material for making backpacks. Uncertain demand causes a lot of accumulation (over stock) of raw materials in the storage area, so we need a method of supporting raw material inventory control to determine the optimal order. The research objective determines the optimal ordering of raw materials using variable raw material demand, raw material inventory variables and ordering variables in January the first week to March the fourth week. The Fuzzy Mamdani method used in this study because it has a flexible nature and can overcome the problem of uncertainty. The data processing of the Fuzzy Mamdani method carried out in several stages (a) the formation of the Fuzzy set, (b) the application of the implication function, (c) the composition of the rules, (d) Defuzzification. Defuzzification in research uses the centroid method. The results of Fuzzy Mamdani's manual calculation in January of the first week with input of raw material demand of 666 meters and 126 meters of inventory resulted in an optimal prediction of ordering raw materials of 876 meters. Calculations for January the second week to March the fourth week are performed with the help of the Matlab R2013a Fuzzy Toolbox software. The results of prediction data evaluation on the number of raw material orders Fuzzy Mamdani with actual data on the raw material number ordering CV. Pine Bag’s Specialist, it is known that the average absolute error (MAE) is 193.8 meters with an average percentage of absolute error (MAPE) of 22%. So, it is said that the level of accuracy of predictions is reasonable. Future research is expected in the Fuzzy Mamdani method can be used more than two inputs and one output and the addition of linguistic variables. Combine the Fuzzy Mamdani method with other raw material inventory control methods so that the results obtained are getting better.