Aturan Asosiasi Antar Item Terjual pada Data Penjualan Minimarket Milik Komunitas di Hari Besar Tertentu Menggunakan Algoritma Apriori

  • Luky Fabrianto Universitas Nusa Mandiri
  • Novianti Madhona Faizah Universitas Tama Jagakarsa
  • Johan Hendri Prasetyo Universitas Nusa Mandiri
  • Bobby Suryo Prakoso Universitas Nusa Mandiri
  • Gani Wiharso Universitas Nusa Mandiri
Keywords: Data mining, Aturan Asosiasi, Support, Confidence, Rule, Frequent item


The popular data mining methods to find the relationship between an item and another item is the association rule method using A Priori algorithm, this method is precise to generate a pattern of relationship rules between the types of items sold based on sales data. Support values ​​on frequent items and confidence in the rules obtained can be an actionable insight that can be follow up by minimarket managers, cooperatives and etc. The categorization of product types in minimarkets is much while the total number of transactions in one year is also very large, but the number of types of items sold in a transaction is very few, thus the threshold value cannot be high. In this study, the association rule method was carried out per event or certain period related to Muslim holidays, the highest rule was obtained is Makanan ringan => Sembako with 46% confidence and 16% support which occurred in the month of Ramadan.


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