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Kopong Pati , Gergorius
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Electrical & Electronics Engineering

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PENERAPAN DATA MINING MENGGUNAKAN ALGORITMA APRIORI DALAM MEMPREDIKSI PENJUALAN KAIN TENUN SUMBA Bulu, Elfrida; Kopong Pati , Gergorius; Wulla Rato, Karolus
JOURNAL OF ELECTRICAL AND SYSTEM CONTROL ENGINEERING Vol. 7 No. 2 (2024): Journal of Electrical and System Control Engineering
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jesce.v7i2.10552

Abstract

Weaving is one of Indonesia's traditional fabric arts and culture which is produced in various regions throughout the archipelago (NTT, Kalimantan, Bali, Sulawesi, Lombok, Sumbawa, and others). Sumba woven fabric is a collection of activities that can define the work carried out by a system and change input into output that has added value for the user. Currently sales are only around Sumba Island. Meanwhile, the sales process is carried out by buyers coming directly to the shop, apart from that, woven fabrics are also sold in local markets and at cultural exhibitions. Therefore, an a priori algorithm approach was taken in association analysis to find candidate frequency itemsets to increase sales. Based on the sales results of woven fabric products in the kalaki kambe weaving group, the ones that sell the most can be found using an a priori algorithm, namely by looking at products that meet a minimum support of 2.4% and a minimum confidence of 50%. The most sold products are sarongs, wewewa woven fabric and loura woven fabric with the results obtained that sarongs, wewewa woven fabric and loura woven fabric with a support value of 0.300 or 30% and a trust value of 0.750 or 75%.
Co-Authors Bulu, Elfrida Wulla Rato, Karolus