Implementation of Data Mining for Relayout Finish Goods in Warehouses Using the Apriori Method
Case Study of Oyster Mushroom Cultivation in Mulyosari Hamlet
DOI:
https://doi.org/10.31961/positif.v8i1.1125Keywords:
Data Mining, Apriori Algorithm, WarehouseAbstract
Every manufacturing industry should have supporting facilities and infrastructure for its business continuity. Infrastructure is very important and is part of the final placement of the production process is storage warehouses, storage can be temporary or long-term depending on the needs of the company. Problems that often occur in warehouses are generally the placement of finished goods that are still not well organized so that a lot of time and effort needed by the pic rack in the activity of preparing the goods to be sent because the location of the goods requested to be sent simultaneously the location is still far away. Based on the above problems the author intends to conduct research to provide alternative thinking to the company by conducting data testing with a priori algorithm to obtain new information on the layout of goods more effectively. From the calculation results that have been done can be concluded that the most frequent transactions simultaneously with a minimum support of 40% and a minimum confidence of 80% are 4 items namely COVER ADF SUB C, COVER PAPER GUIDE ASF, PAPER GUIDE DUPLEX LOWER (MASUO) and PAPER GUIDE UPPER ADF. From the test results above, a new combination model has been formed so that the pic rack can change the old layout with the new one
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