User Transaction Patterns in Smart Contracts Based on Call Frequency and Transfer Value

Main Article Content

👤 Hery Hery
🏢 Department of Information Systems, Pelita Harapan University, Jalan M.H. Thamrin Boulevard No.1100 Lippo Karawaci, Tangerang, 15811, Indonesia
👤 Calandra Haryani
🏢 Department of Information Systems, Pelita Harapan University, Jalan M.H. Thamrin Boulevard No.1100 Lippo Karawaci, Tangerang, 15811, Indonesia

Smart contracts are integral to blockchain technology, enabling decentralized and automated transactions. This study examines 1,000 smart contracts by analyzing metrics such as total transactions, unique users, total value transferred (ETH), gas consumption, and call frequency. Total transactions range from 1 to 18,902, with unique users spanning 1 to 14,839. The average total value transferred is 3,245.87 ETH, peaking at 7,850.16 ETH, while gas consumption averages 25,486,392 units with a maximum of 58,471,065 units. Strong correlations were identified between transaction volume (r = 0.78), user engagement, and gas consumption. Clustering analysis categorizes contracts into low, moderate, and high-activity groups, while anomaly detection highlights 32 contracts with unusual behaviors, indicating inefficiencies or vulnerabilities. These findings emphasize the importance of optimizing smart contract designs to improve efficiency, security, and scalability. The study provides actionable insights into operational patterns and proposes future research directions, including design optimization, real-time monitoring, cross-platform analysis, and machine learning applications for predictive modeling. By addressing these aspects, this research contributes to the ongoing development of robust and efficient decentralized systems.

[1]
H. Hery and C. Haryani, “User Transaction Patterns in Smart Contracts Based on Call Frequency and Transfer Value”, Int. J. Res. Metav., vol. 2, no. 3, pp. 236–247, Aug. 2025.

Article Details

Section
Articles

Similar Articles

1 2 3 > >> 

You may also start an advanced similarity search for this article.