Machine learning approach to uncover customer plastic bag usage patterns in a grocery store

Abstract

Plastic bags are used by many people because they are inexpensive, lightweight, durable, and waterproof. Plastic bags, on the other hand, do not break down and can pollute the environment if not handled properly. Indonesia produces a lot of plastic waste and is one of the top ten countries that has a problem with plastic waste. In this study, we used three months of data of real transactions from a grocery store. This study shows how the decision tree can identify patterns on plastic bag usage at a small grocery store by using demography and products purchase. The attribute weights showed that in the hometown, the total of several products bought were the factors that affected the use of plastic bags.