Penerapan Metode Asosiasi Datamining Market Basket Analysis Menggunakan Algoritma Apriori Untuk Melakukan Pola Analisis Belanja Konsumen - hidayatullah Al Islami (Journal of Artificial Intelligence and Innovative Applications (JOAIIA), 2020)
Application Of Data Mining Association Method Market Basket Analysis Using Apriori Algorithm For Consumer Shopping Analysis Purpose (Case Study: Sbmart Bukit Nusa Indah) Data Mining is a discipline that studies techniques from patterns, statistics, databases, which aims to extract information useful and valuable. Transaction data within 1 year is very unfortunate if not analyzed and reprocessed to obtain useful information data such as to be able to know the product with the most sales and product linkage with each other. For that we need one of the data mining algorithm that is Market Basket Analysis and Apriori algorithm because algorithm apriori is the most famous algorithm to find high frequency pattern. The purpose of this research is to analyze sales sales data at SBmart Bukit Nusa Indah Store. The results of the implementation and testing obtained from the processing of sales transaction data in the form of itemset data by applying the concept of association analysis of known mining support values on each item, item combination, and confidence value in the formation of frequent itemset using RapidMiner Studio 5. The most purchased item simultaneously by consumers of SBMart Bukit Nusa Indah, if buying Biscuit to eat will buy Mineral Water with 70,43% confidence, Liquid Milk Tetra-Instant Noodles with 73,16% confidence, Liquid Tea & Cofee-Instant Noodles with confidence 79,33 %, Mineral Water - Instant Noodles with 72.69% confidence, Modern Snack Pack-Instant Noodles with 74.22% confidence, Instant Noodles Bread with 83.78% confidence, Egg-Instant Noodles with 84.02% confidence, Modern Snack Pack - Mineral Water with confidence 72.02% Egg-Mineral Water with a confidence73.36%.