STATE OF THE ART FRAUD DETECTION PADA KARTU KREDIT DENGAN MENGGUNAKAN PENDEKATAN ALGORITMA DAN TEKNIK MACHINE LEARNING
DOI:
https://doi.org/10.56127/juit.v2i2.1728Keywords:
Fraud Detection, Credit Card, Machine LearningAbstract
This study provides an overview of fraud detection or robbery / fraud detection on credit cards using machine learning as the main technique. This review discusses some research by experts related to the theoretical foundation, advantages and disadvantages, data procedures, analysis methods, and machine learning techniques used. Before big data was widely known and used in the community, fraud detection used the meaning of text and the meaning of data to process the data. Along with the development of technology, many techniques are used in fraud detection, one of which is machine leaning. Machine learning is a branch of Artificial Intelligence that allows computers to have the ability to learn without needing to program anymore. In simple terms machine learning builds an algorithm that allows computer programs to learn and perform tasks on their own without any user features. This kind of algorithm works by building a model from the input or input to be able to produce a prediction or make a decision based on existing data. Machine learning deals with computational statistics that focus on predictions or making based on computer usage. Some of the implementations of machine learning are text analysis, image processing, finance, search and recommendation engines, speech understanding, and so on.
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