Implementation of Data Mining in Shopping Cart Analysis using the Apriori Algorithm

Abstract

Market basket analysis is one of the techniques of knowledge mining used in a broad dataset or database to find a collection of items that are interwoven. Generally used in a sale, the most relevant shopping cart data is used. This methodology has been widely applied in different multinational or foreign industries and is very useful in consumer buying preferences. Technology advances change business trends dramatically, shifting customer demands require increased surgical accuracy of business. In this research, the writer wants to analyze the shopping cart using a priori algorithm, with a dataset from the Kaggle web. Using anaconda software features with the Python programming language which is expected to create knowledge overwriting consumer buying patterns. In conclusion, this pattern can be used to support an industry in managing its company activities.