Implementasi Metode Naive Bayes Classifier (NBC) Pada Komentar Warga Sekolah Mengenai Pelaksanaan Pembelajaran Jarak Jauh (PJJ)

Abstract

Many credit card issuing companies experience problems related to bill payments by their customers or also known as bad credit payments that are not according to the agreement so that they are detrimental to the company itself. In this case, there is still a pile of unclassified credit cardholder customer data and problem-solving patterns are found. The C4.5 algorithm is used to predict whether a customer is a credit default payment or not. This study uses a data set that has determining criteria, namely the amount of credit, status, age, and payment status for 1-3 months. From the results of research using 4199 customer data results in an evaluation that the C4.5 algorithm is applied accurately to predict whether or not customer credit card payments are bad with an accuracy level of 70.93%.