DETEKSI ANOMALI TRANSAKSI BITCOIN MENGGUNAKAN METODE KMEANS DAN KMEDOIDS

JUNIANSYAH, RAHMAT and Stiawan, Deris and Afifah, Nurul (2024) DETEKSI ANOMALI TRANSAKSI BITCOIN MENGGUNAKAN METODE KMEANS DAN KMEDOIDS. Undergraduate thesis, Sriwijaya University.

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Abstract

Bitcoin is one of the most popular digital currencies widely used in online transactions. However, Bitcoin transactions are prone to anomalies, which may indicate suspicious activities such as fraud or other illegal actions. Detecting these anomalies is essential to enhance the security and reliability of the Bitcoin network. This study aims to identify anomalies in Bitcoin transactions using the KMeans and KMedoids clustering methods. The dataset consists of daily Bitcoin transactions from 2009 to 2024, sourced from BigQuery. The data preprocessing includes normalization using the Standard Scaler before applying the clustering algorithms. The resultsshow that the KMeans method achieved a silhouette score of 0.96, while the KMedoids method scored 0.98. Further analysis revealed that KMedoids is more reliable in handling data with outliers compared to KMeans, despite requiring longer computation times. Keywords: KMeans, KMedoids, Bitcoin, Anomaly, Clustering

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	KMeans, KMedoids, Bitcoin, Anomali, Clustering
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Rahmat Juniansyah
Date Deposited:	20 Jan 2025 04:47
Last Modified:	20 Jan 2025 04:47
URI:	http://repository.unsri.ac.id/id/eprint/165835

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