Abstract

To take advantage of a very large collection of databases, a method or technique is needed that can convert a myriad of data into useful information, one of the data that can be processed is sales data at the Kamang Mart Mini Market. Kamang mart mini market is a mini market that will meet the needs of the community. As an effort to support efficient services, an orderly and thorough work procedure is needed so that it will produce fast, accurate and timely information according to the needs of consumers or the community. To facilitate the mini market in managing data, a system is needed that can produce a decision to find out which products are most in demand and needed by consumers and predict the level of stock availability. So that a lot of data can be used optimally so that later the goods needed by consumers can be fulfilled properly by the mini market and can increase sales at the Kamang Mart minimarket and can also reduce the accumulation of goods that are less desirable by consumers. The transaction data that will be processed in this study are as many as 20 transaction data. The transaction data will be examined using one of the Data Mining techniques by association rule using the Fp-Growth algorithm with a minimum support value of 30% and a confidence value of 70%. So that the pattern of product purchases is obtained which is used as information to predict the level of stock availability of goods. This research is very appropriate to be used by supermarkets in order to convey information more quickly and accurately so that sales levels are increased and well controlled.

Full Text
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