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Eva Khudzaeva
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Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Syarif Hidayatullah Jakarta Jl. Ir. H. Juanda No.95, Cempaka Putih, Ciputat Timur. Kota Tangerang Selatan, Banten 15412
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Applied Information System and Management
Published by Universitas Islam Negeri Syarif Hidayatullah Jakarta
ISSN : 26212536     EISSN : 26212544     DOI : 10.15408/aism
Core Subject : Education,
Languange, Linguistic, Communication & Media
Arjuna Subject : -
Articles 1 Documents
 1 
Search results for , issue "Vol. 4 No. 2 (2021): Applied Information System and Management (AISM)" : 1 Documents clear
Credit Card Fraud Detection Using Machine Learning Approach Soni, Kanal Bhadresh
Applied Information System and Management (AISM) Vol. 4 No. 2 (2021): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v4i2.20570

Abstract

Using new spam technologies to carry out internet banking fraud refers to shifting and withdrawing money from the user’s balance account without it’s authorization. Credit card fraud pops into the mind so far in the current scenario when the concept of fraud bursts into some conversation. Credit card fraud has escalated tremendously in recent times due to the incredible growth in credit card purchases. In order to assess, identify or prevent undesirable conduct, fraud detection requires tracking the purchase behavior of users/customers. The purpose of this project is to predict the genuine and fraud transactions with respect to the amount of the transaction utilizing various machine learning approaches like Logistic Regression, Decision Trees, Support Vector Machine, Naïve Bayes, Random Forest and K-Nearest Neighbor. The model built who has greater accuracy and precision is considered to be best fit for this system.

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