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All Journal Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain
Emary, Ibrahiem M. M. El
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Examining User Satisfaction and Continuous Usage Intention of Digital Financial Advisory Platforms in Indonesia: An Integrated Model Approach Emary, Ibrahiem M. M. El; Sanyour, Rawan; Abdullah, Manal
Journal of Digital Market and Digital Currency Vol. 2 No. 2 (2025): Regular Issue June 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jdmdc.v2i2.30

Abstract

This study evaluates user satisfaction (US) and continuous intention (CI) to use digital financial advisory platforms in Indonesia. Utilizing structural equation modeling (SEM) with SmartPLS, we examined the relationships between perceived ease of use (PEU), perceived enjoyment (PE), service quality (SQ), US, and CI. Data were collected from 413 respondents via an online survey conducted between February and March 2024. The descriptive statistics for the main variables indicated that the mean scores ranged from 5.3 to 5.9 on a 7-point Likert scale, with standard deviations between 1.1 and 1.3. Our results show that PEU significantly influences PE (β = 0.923, t-value = 88.677, p < 0.001) and CI (β = 0.471, t-value = 13.950, p < 0.001). PE positively affects the US (β = 0.211, t-value = 7.248, p < 0.001), while SQ is a strong predictor of the US (β = 0.773, t-value = 29.423, p < 0.001). Furthermore, the US significantly impacts CI (β = 0.518, t-value = 15.117, p < 0.001). The R-squared values for the key constructs were 0.851 for PE, 0.876 for US, and 0.878 for CI, indicating substantial explanatory power. These findings underscore the importance of usability, enjoyment, and SQ in enhancing US and retention. The study contributes to the literature by providing an integrated model that combines these key variables, offering a comprehensive framework for understanding user behavior in digital financial advisory platforms. Theoretical contributions include extending the Technology Acceptance Model (TAM) by incorporating enjoyment and SQ. Practical implications suggest that platform providers prioritize user-friendly design, engaging features, and high service standards to improve the US and foster long-term engagement. Future research should explore additional factors, such as perceived security and trust, to further enrich the understanding of user behavior in digital financial services.
Classification of Bitcoin Ransomware Transactions Using Random Forest: A Data Mining Approach for Blockchain Security Emary, Ibrahiem M. M. El; Brzozowska, Anna; Popławski, Łukasz; Dziekański, Paweł; Glova, Jozef
Journal of Current Research in Blockchain Vol. 2 No. 2 (2025): Regular Issue June 2025
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v2i2.33

Abstract

The rapid evolution of ransomware attacks necessitates robust and scalable detection mechanisms to safeguard digital assets. This study leverages the Bitcoin Ransomware Dataset, comprising 2,916,697 transactions, to evaluate the effectiveness of the Random Forest algorithm in classifying ransomware-related activities. Through comprehensive preprocessing, including feature encoding and standardization, and exploratory data analysis (EDA), the dataset is prepared for modeling. The Random Forest model achieves an overall accuracy of 99%, demonstrating exceptional performance in identifying the majority class. However, challenges persist in classifying minority classes, highlighting the impact of class imbalance. Feature importance analysis reveals that attributes such as income, weight, and length play pivotal roles in the classification process. The study underscores the potential of Random Forest for ransomware detection while emphasizing the need for advanced techniques to address class imbalance and improve minority class performance.
Co-Authors Abdullah, Manal Brzozowska, Anna Dziekański, Paweł Glova, Jozef Popławski, Łukasz Sanyour, Rawan