Penerapan Metode Asosiasi Datamining Market Basket Analysis Menggunakan Algoritma Apriori Untuk Melakukan Pola Analisis Belanja Konsumen

Abstract

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%.