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Machine learning approach to uncover customer plastic bag usage patterns in a grocery store
Summary
Researchers applied machine learning to grocery store transaction data to uncover patterns in customer plastic bag use and identify who is most likely to use reusable bags. Understanding consumer behavior is key to designing effective policies that reduce plastic bag consumption and, ultimately, plastic waste entering the environment.
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.
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