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p-Index From 2021 - 2026
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This Author published in this journals
All Journal Blockchain Frontier Technology (BFRONT) International Journal of Education, Vocational and Social Science
Aswadi Jaya
Universitas PGRI Palembang, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Data Mining Techniques in Blockchain Using Machine Learning Algorithms Ankur Singh Bist; Aswadi Jaya; Agung Rizky; Maulana Arif Komara; Kgomotso Moyo
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1169

Abstract

The rapid advancement of blockchain technology has generated an enormous volume of complex transaction data, creating significant challenges in data analysis, particularly in terms of scalability, noise, and anonymity. This study aims to identify effective data mining techniques and implement machine learning algorithms to enhance the performance of blockchain data analysis. A quantitative approach was employed by utilizing data mining techniques and machine learning algorithms, including Random Forest, K-Means, and Neural Network. These methods were applied to blockchain datasets obtained from Ethereum, Bitcoin, and OpenSea through several stages, namely preprocessing, feature engineering, model training, and evaluation using accuracy, precision, recall, F1-score, and Root Mean Square Error metrics. The results indicate that Random Forest demonstrates stable performance with high classification accuracy, Neural Network excel at capturing complex patterns in non-linear data, while K-Means is effective in identifying patterns through clustering. These findings suggest that each algorithm offers distinct advantages depending on the characteristics of the data and the objectives of the analysis. This study concludes that the integration of data mining techniques and machine learning algorithms can significantly improve the effectiveness of blockchain data analysis compared to traditional methods. Furthermore, the proposed integrated framework can serve as a reference for the future development of blockchain-based data analytics systems. Rather than providing a quantitative benchmark against conventional analytical approaches, this study proposes a standardized methodological framework intended to support consistent implementation, evaluation, and future comparative validation across heterogeneous blockchain analytics applications.
Busuu Application On Students’ Reading Skills Development Darwawin Perdana Akbar; Aswadi Jaya; Hermansyah Hermansyah
International Journal of Education, Vocational and Social Science Vol. 5 No. 04 (2026): International Journal of Education, Vocational and Social Science( IJVESS)
Publisher : Cita konsultindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63922/ijevss.v5i04.4467

Abstract

This study aimed to describe how students used the Busuu application in their previous reading activities and how they perceived its use in an EFL classroom context. The study employed a descriptive qualitative method involving 35 students of Grade XI.3 and one English teacher at SMA PGRI 1 Palembang. Data were collected through classroom observation, questionnaire, student interviews, and teacher interview, with student interviews used as the main source of data and the other instruments used for supporting and triangulation purposes. The data were analyzed using data condensation, categorization, data display, and conclusion drawing based on Miles, Huberman, and Saldaña (2014). The results showed that students used Busuu mainly for reading short texts, following instructions, and doing reading tasks and also used some strategies such as rereading, guessing the meaning from context, and using digital features such as translation tools, audio, pictures, and videos to help them in understanding the meanings of vocabulary and sentences. The results also showed that these elements helped students to manage their reading while some students still had problems with unfamiliar vocabulary, sentence comprehension, and some idioms. As for student perceptions, most students perceived Busuu as a useful and practical application that facilitated their reading activities. Some students also reported their reliance on digital features and the importance of teacher guidance and independent reading practice in enhancing their understanding.
Co-Authors Agung Rizky Ankur Singh Bist Darwawin Perdana Akbar Hermansyah Hermansyah Kgomotso Moyo Maulana Arif Komara