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Image of DETEKSI TRANSAKSI ANOMALI PADA BLOKCHAIN DENGAN MENGGUNAKAN METODE GATED RECURRENT UNIT (GRU)

Skripsi

DETEKSI TRANSAKSI ANOMALI PADA BLOKCHAIN DENGAN MENGGUNAKAN METODE GATED RECURRENT UNIT (GRU)

Muhammad, Faisal Soultan - Personal Name;

Penilaian

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Penilaian anda saat ini :  

Illegal activities such as money laundering using cryptocurrencies represented by Bitcoin have emerged. In this study, a Gated Recurrent Unit (GRU) neural network is used to identify anomalous transaction patterns in the dataset. The dataset is created by taking raw data based on yearly parameters to extract a subset of data. This subset represents data from the years 2011 to 2013 and is extracted by writing a Python code snippet. Due to the imbalance of the data, the dataset's classes are balanced using oversampling and undersampling techniques. The best model achieved an accuracy of 90.31%. Then, through k-fold validation, the model showed good consistency, with an average accuracy of 86.29%. These results indicate that the model has reliable performance in the detection task.


Availability
Inventory Code Barcode Call Number Location Status
2407003712T146293T1462932024Central Library (REFERENCES)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1462932024
Publisher
Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer., 2024
Collation
xiii, 62 hlm.; ilus.; tab.; 29 cm.
Language
Indonesia
ISBN/ISSN
-
Classification
005.207
Content Type
Text
Media Type
unmediated
Carrier Type
unspecified
Edition
-
Subject(s)
Prodi Sistem Komputer
deteksi anomali
Specific Detail Info
-
Statement of Responsibility
UIN Farrah
Other version/related

No other version available

File Attachment
  • DETEKSI TRANSAKSI ANOMALI PADA BLOKCHAIN DENGAN MENGGUNAKAN METODE GATED RECURRENT UNIT (GRU)
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