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ANALISA TRANSAKSI PADA BLOCKCHAIN DENGAN METODE MACHINE LEARNING

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Penilaian

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Blockchain offers high security; however, the performance of transactions on this network remains a subject that requires further analysis. Transaction success in blockchain is influenced by various factors.This study aims to analyze transaction performance on the blockchain using the K-Means Clustering method. The analysis focuses on the parameters of Gas Limit and Gas Consumed to understand the factors contributing to transaction success and failure. The methods used include data preprocessing, determining the number of clusters, implementing the K-Means algorithm, and evaluating performance using the Silhouette Score. Data visualization through scatter plots and boxplots helps identify patterns of imbalance in gas allocation. The results of the study show that the K-Means method successfully grouped transaction data into two clusters: the first cluster represents transactions with a low Gas Limit that have a higher potential for failure, while the second cluster consists of transactions with a higher Gas Limit and greater chances of success. The evaluation using the Silhouette Score yielded an average value of 0.98, indicating excellent clustering performance with optimal separation between clusters. This study provides a clear overview of blockchain transaction performance and identifies the causes of transaction failures as an initial step toward improving system efficiency.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507000974	T166055	T1660552024	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1660552024

Publisher

: Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xix, 108 hlm.: ilus., tab.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem komputer

Specific Detail Info

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Statement of Responsibility

EM

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