CREDIT CARD INTERNAL FRAUD DETECTION ON ONLINE TRANSACTION DATA USING HIDDEN MARKOV MODEL

The rapid progress in the technology of electronic commerce has led to increased use of credit cards. This happens because credit cards are an easy payment method for online shopping transactions. With the increase in the use of credit cards, cases of credit card fraud have also increased. If in...

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Bibliographic Details
Main Author: CHRISTINA, DINA
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/36178
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:The rapid progress in the technology of electronic commerce has led to increased use of credit cards. This happens because credit cards are an easy payment method for online shopping transactions. With the increase in the use of credit cards, cases of credit card fraud have also increased. If information about credit card transactions is an observed process and the factors that cause the magnitude of credit card transactions are not directly observed (hidden) and assumed to form a Markov chain, then credit card transactions can be modeled by the Hidden Markov Models (HMM). In this study, will be discussed the process of traning a model that records the normal behavior of a credit card holder until the process of detecting new transactions on a credit card. After detecting new cret card transactions, an optimal threshold value will be determined for a new transaction to be categorized as fraud transaction. Several experiments with different amounts of hidden state will be presented to show the effectiveness of model in detecting fraud transaction and the effectiveness of model against the level of accuracy.