Open AccessImplementation of Data Mining in Shopping Cart Analysis using the Apriori Algorithm
Author(s) -
Susy Rahmawati,
Miftahul Nuril Silviyah,
Nur Syifa’ul Husna
Publication year - 2021
Publication title -
international journal of data science, engineering, and analytics
Language(s) - English
Resource type - Journals
eISSN - 2807-1689
pISSN - 2798-9208
DOI - 10.33005/ijdasea.v1i1.5
Subject(s) - cart , python (programming language) , computer science , affinity analysis , apriori algorithm , data mining , multinational corporation , software , sentiment analysis , data science , business intelligence , a priori and a posteriori , machine learning , association rule learning , business , mechanical engineering , finance , engineering , philosophy , epistemology , programming language , operating system
Market basket analysis is one of the techniques of knowledge mining used in a broad dataset ordatabase to find a collection of items that are interwoven. Generally used in a sale, the most relevantshopping cart data is used. This methodology has been widely applied in different multinational or foreignindustries and is very useful in consumer buying preferences. Technology advances change business trendsdramatically, shifting customer demands require increased surgical accuracy of business. In this research,the writer wants to analyze the shopping cart using apriori algorithm, with a dataset from the Kaggle web.Using anaconda software features with the Python programming language is expected to create knowledgeoverwriting consumer buying patterns. In conclusion, this pattern can be used to support industry inmanaging its company activities.