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Algorithm Implementation Of Interest Buy Apriori Data On Consumer Retail Sales In Industry
Author(s) -
Ahmad Fachrurozi,
Mufid Junaedi,
Jordy Lasmana Putra,
Windu Gata
Publication year - 2020
Publication title -
journal of informatics and telecommunication engineering
Language(s) - English
Resource type - Journals
eISSN - 2549-6255
pISSN - 2549-6247
DOI - 10.31289/jite.v4i1.3775
Subject(s) - apriori algorithm , purchasing , revenue , association rule learning , stock (firearms) , business , product (mathematics) , marketing , computer science , commerce , data mining , finance , engineering , geometry , mechanical engineering , mathematics
This data processing has the aim to increase the company's turnover, because by being aware of how the interest in buying goods works, the company can buy products other than the main products that it buys. In increasing company revenue can be done using the Data Mining process, one of which uses a priori algorithm and association techniques. With this a priori algorithm found association technique which later can be used as a pattern of purchasing goods by consumers, this study uses a data repository of 958 data consisting of 45 transactions. From the results obtained goods with the name Paper Chain Kit 50's Christmas is a product that is often bought by consumers and it is known that the most frequent combination patterns are the Retro Spot Paper Chain Kit and the Paper Chain Kit 50's Christmas. So that with known buying patterns, the company manager can predict future market needs, and can calculate the stock of goods that must be reproduced, and goods whose stock must be reduced, and also with the results of the association the manager can manage the layout of the product to be better. Keywords: Apriori Algorithm, Sales Data, Retail.

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