CREDIT CARD FRAUD DETECTION USING LINEAR DISCRIMINANT ANALYSIS (LDA), RANDOM FOREST, AND BINARY LOGISTIC REGRESSION

  • Muhammad Ahsan Departement of Statistics, Institut Teknologi Sepuluh Nopember
  • Tabita Yuni Susanto Departement of Statistics, Institut Teknologi Sepuluh Nopember
  • Tiza Ayu Virania Department of Statistics, Institut Teknologi Sepuluh Nopember
  • Andi Indra Jaya Departement of Statistics, Institut Teknologi Sepuluh Nopember
DOI: https://doi.org/10.30598/barekengvol16iss4pp1337-1346
Keywords: Binary Logistics Regression, Credit Card, Fraud, Linear Discriminant Analysis, Random Forests

Abstract

The growth of electronic payment usage makes the monetary tension of credit-card deception is changing into major defiance for finance and technology companies. Therefore, pressuring them to continuously advance their fraud detection system is crucial. In this research, we describe fraud detection as a classification issue by comparing three methods. The method used is Linear Discriminant Analysis (LDA), Random Forest, and Binary Logistic Regression. The dataset used is a dataset containing transactions made by credit cards. The challenge in this analysis is that the dataset is highly unbalanced, so SMOTE must perform better on the data. The dataset contains only continuous features that are transformed into Principal Component Scores (PCs). The results show that the binary regression algorithm, the Random Forest algorithm, and the Linear Discriminant Analysis with variables that have SMOTE have AUC values greater than using the original variables. The largest AUC value was obtained by binary logistic regression with 90:10 separation data and Random Forest Algorithm with 60:40 separation data.

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Published
2022-12-15
How to Cite
[1]
M. Ahsan, T. Susanto, T. Virania, and A. I. Jaya, “CREDIT CARD FRAUD DETECTION USING LINEAR DISCRIMINANT ANALYSIS (LDA), RANDOM FOREST, AND BINARY LOGISTIC REGRESSION”, BAREKENG: J. Math. & App., vol. 16, no. 4, pp. 1337-1346, Dec. 2022.
Issue
Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2022 Muhammad Ahsan, Tabita Yuni Susanto, Tiza Ayu Virania, Andi Indra Jaya

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