Abstract
he Apriori algorithm is a data mining technique for determining associative rules for a combination of components, this study aims to find the pattern frequency of each component that has been ordered by the customer so that the order is in accordance with the number and timely delivery, therefore to support the problems faced by PT. . SMF for the combination of inventory to purchase of goods, PT SMF applies the Apriori Algorithm to predict stock of goods so that when there is an order, the goods are not lacking and the delivery is also on time. The results of the research carried out obtained the most data on goods produced every 1 month, including the Pipe Bracket and Solenoid Bracket pattern of linkages in terms of predicting the number of goods at PT. If SMF produces Pipe Brackets, it must also produce Selenoid Brackets where the resulting confidence is 60%, Nc : 4, and for the lift ratio test it is 2.307. Whereas if you produce the Selenoid Valve Bracket, you must also produce the air pipe bracket for the resulting confidence of 75%, Nc: 5, and the lift ratio test of 2.272.
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