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All Journal Journal of Computer System and Informatics (JoSYC) Jurnal Teknologi Informatika dan Komputer Jurnal Ekonomi dan Perbankan Syariah SAGA: Journal of Technology and Information Systems Jurnal Sistem Informasi dan Teknologi Informasi
Soepriyono, Gatot
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science Social Sciences

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Journal : Journal of Computer System and Informatics (JoSYC)

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Penerapan Market Basket Analysis Data Mining Pada Penjualan Batik dengan Menerapkan Algoritma Apriori Soepriyono, Gatot
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5198

Abstract

Batik is a cloth that is depicted by applying wax to the cloth and processing it in a certain way. In certain batik companies, there are products that are characteristic of that company. As time goes by, problems arise with the sale of batik due to lack of proper stock availability in shops, making it difficult for customers to order batik. This problem that occurs is certainly a problem that must be resolved. If the available stock of goods does not match the customer's wishes, the goods will be piled up in the shop's stock. Apart from that, if the customer does not find a batik model that suits his wishes, it will cause the customer to switch to another shop. The sales results are reported in the form of a ledger or entered into a computer. The report produced is a sales transaction data report. Data mining itself is a process of processing quite large amounts of data. In the future, the data recorded in the ledger can be used as information in determining business strategies for batik sales. Market Basket Analysis aims to manage customer data or sales data. The a priori algorithm is an association part of mining data. A priori algorithms can help in forming candidate item combinations. From the results of the research carried out, there is 1 combination of items that meets the support value of 30%, namely items T09 and T12, where the support value obtained is 30.76% and with a confidence value of 100%.
Co-Authors Agung Triayudi Andrianingsih Bani, Ahmad Syah Faisal, Andri Rais Rabtsani, Muhamad setiawan, Danis Winarsih Winarsih