Komparasi Tujuh Algoritma Identifikasi Fraud ATM Pada PT. Bank Central Asia Tbk - Haliem Sunata (JATISI (Jurnal Teknik Informatika dan Sistem Informasi), 2020)
The high use of ATM machines has created a loophole for fraud that can be carried out by third parties in assisting PT. Bank Central Asia Tbk to keep ATM machines ready to use by customers. Not fast and difficult identification of ATM machine fraud is a problem for PT. Bank Central Asia Tbk. With this problem, the researcher collected 5 datasets and pre-processed the dataset so that it could be used for modeling and algorithm testing, in order to answer the problems that occurred. There were seven comparisons of algorithms including decision trees, gradient boosted trees, logistic regression, naive bayes (kernels), naive bayes, random forest and random tree. After modeling and testing, the results show that the gradient boosted trees algorithm is the best algorithm with an accuracy of 99.85% and an AUC value of 1, the high result of this algorithm is due to the compatibility of each attribute tested with the gradient boosted trees character that is driven where this algorithm is save and existing results. So the gradient boosted trees algorithm is the solution to the problems that have arisen by PT. Bank Central Asia Tbk.