Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Journal of Information Systems and Informatics
Rahman, Md. Mahfuzur
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
A novel approach to analyzing the impact of AI, ChatGPT, and chatbot on education using machine learning algorithms Hasan, Nahid; Polin, Johora Akter; Ahmmed, Md. Rayhan; Sakib, Md. Mamun; Jahin, Md. Farhan; Rahman, Md. Mahfuzur
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.7158

Abstract

Artificial intelligence (AI) is one of the most common and essential technologies in this modern era, especially in the education and research sectors. It mimics machine-processed human intellect. In modern times, ChatGPT is one of the most effective and beneficial tools developed by OpenAI. Provides prompt answers and feedback to help academics and researchers. Using ChatGPT has various advantages, including improving methods of instruction, preparing interactive lessons, assessment, and advanced problem-solving. Threats against ChatGPT, however, include diminishing creativity, and analytical thinking. Additionally, students would adopt unfair procedures when submitting any tests or assignments online, which would increase their dependency on AI systems rather than thinking analytically. In this study, we have demonstrated arguments on both sides of AI technology. We believe that our study would provide a depth of knowledge and more informed discussion. Data is collected via an offline platform and then machine learning algorithms such as K-nearest neighbour (K-NN), support vector machine (SVM), naive bayes (NB), decision tree (DT), and random forest (RF) are used to analyze the data which helps to improve teaching and learning techniques where SVM shows best performance. The results of the study would offer several significant learning and research directions as well as ensure safe and responsible adoption.
Emerging Trends in Digital Transformation and Information Systems by Bibliometric Analysis in the United States Islam, Mirazul; Islam, Md Ahadul; Saha, Raju; Hossain, Didar; Rahman, Md. Mahfuzur
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1340

Abstract

This bibliometric analysis examines the evolving trends of digital transformation (DT) and information systems (IS) in U.S. businesses. It explores how technology—focused on strategy, efficiency, innovation, and customer engagement—is reshaping organizations and workplaces. Using a PRISMA-based systematic review and data from Scopus (2016–2026), the study applies the Bibliometrix R package to assess publication patterns. Results show significant growth, with 2,692 documents reflecting a 43.58% annual increase and 18.39% involving international collaboration. Key themes include AI/ML integration in business processes, digital sustainability, and IS as a strategic driver for business model evolution. U.S. businesses are increasingly aligning digital transformation with sustainability goals. This study addresses a key research gap by offering detailed insights into DT and IS impacts on operations and sustainability practices. It underscores the need for integrated socio-technical strategies, responsible data governance, and global collaboration to foster innovation and bridge digital divides.
Co-Authors Ahmmed, Md. Rayhan Hasan, Nahid Hossain, Didar Islam, Md Ahadul Islam, Mirazul Jahin, Md. Farhan Polin, Johora Akter Saha, Raju Sakib, Md. Mamun