Skripsi

DETEKSI TRANSAKSI ANOMALI PADA BLOCKCHAIN DENGAN MENGGUNAKAN METODE DEEP BELIEF NETWORK (DBN). 

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Penilaian

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In recent years, blockchain technology has found widespread applications across various domains, including cryptocurrency, financial services, and risk management. Cryptocurrency, in particular, has garnered significant attention from investors, regulators, and the media ever since Bitcoin was first proposed by Nakamoto. This research utilizes a Deep Belief Network (DBN) to detect patterns of abnormal transactions (anomaly) in a dataset. The dataset was generated by extracting data spanning from 2011 to 2013 and balanced using oversampling and undersampling techniques. The best-performing model achieved an accuracy of 83.05%. Through k-fold validation, the model exhibited good consistency, with an average accuracy of 82.88%. These results indicate that the model maintains consistency and can be relied upon for the given detection task.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307006743	T130853	T1308532023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T1308532023

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xiii, 61 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.707

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Sistem Komputer
Data dalam sistem-sistem komputer

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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