Klasifikasi Pengguna Shopee Berdasarkan Promosi Menggunakan Naïve Bayes
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Abstract
Online shopping is a transaction of buying and selling goods or services through intermediary media, namely social networks. There has been a change in consumption patterns and the way people spend their money, which was originally conventional to switch to E-Commerce services due to several factors, namely the increasing public interest in online shopping due to the COVID-19 virus outbreak, and throughout 2019 E-Commerce users who made transactions reached 168.3 million people. . Based on iprice report data in 2020, Shopee is the most visited E-Commerce with a total of 129,320,800 visitors. Shopee is only a third party that provides a place to sell and payment facilities, therefore Shopee is not responsible for marketing the products sold. To attract consumers, sellers need attractive promotions. Therefore, research is needed to classify E-Commerce users. The purpose of this research is to classify E-Commerce users based on the promotion used using the Naïve Bayes algorithm with the Knowledge Discovery in Database (KDD) methodology. Nine test scenarios were carried out with cross validation which showed that the best performance was a test scenario using 3 folds which resulted in performance with an accuracy value of 88.73%, and with a kappa value of 0.451 which was included in the moderate category. Based on these results, the model generated by the Naïve Bayes algorithm is quite consistent.
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