Aplikasi Data Mining Market Basket Analysis untuk Menemukan Pola Pembelian di Toko Metro Utama Balikpapan - Nadya Rahmawati; Yuki Novia Nasution; Fidia Deny Tisna Amijaya (Program Studi Statistika FMIPA Universitas Mulawarman, 2017)
The development of information technology in the transaction process in supermarkets compete to improve the quality and utility in order to achieve dissemination of information easily and quickly which is accurate and effective. This situation encourages the development of techniques that automatically find the relationship between item in the database. This study aims to analyzing and knowing association rules formed by using apriori algorithm. Market basket analysis’s steps are doing descriptive analysis, grouping the data transactions, applying apriori algorithm on the data, calculating the value of support and calculating the value of confidence. With the value of the minimum support 10% and minimum value of confidence 40%, the results obtained are one rule of association on the first day, four rules of association on the second day, one rule of association on the third day, four rules of association on the fourth day, six rules of association on the fifth day, nine rules of association on the sixth day, and four rules of association on the seventh day.