Nahdatul Akma Ahmad
Universiti Teknologi MARA

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Usability measures used to enhance user experience in using digital health technology among elderly: a systematic review Azaliza Zainal; Nur Farhanum Abdul Aziz; Nahdatul Akma Ahmad; Fariza Hanis Abdul Razak; Fadia Razali; Noor Hidayah Azmi; Haily Liduin Koyou
Bulletin of Electrical Engineering and Informatics Vol 12, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i3.4773

Abstract

In 2030, it is expected that 15% of the country's population will be classified as elderly and there is driving up demand for elderly healthcare services. The evolution of digital health technology has emerged as a solution to this issue. However, there has been a recent decline in the elderly adoption of digital health technologies. This issue is worsened by the emergence of interfaces and interaction styles in newly developed technologies. A systematic review was conducted in this article to investigate the usability measures used to improve the user experience of digital health technology among the elderly. This study includes articles selected from the Web of Science and Scopus databases, both of which are well-established. Using thematic analysis, data from 29 articles were analyzed, yielding four main themes: i) effectiveness; i) efficiency; iii) satisfaction; and iv) learnability. The four main themes generated 12 sub-themes. The appearance, functionality, and structure of new digital health technology are the primary barriers to adoption. User interface (UI) design should take into account the limitations of elderly users. Additionally, elderly users require motivation, support, and training to utilize digital health technologies effectively. This study's findings make significant contributions to digital health and gerontechnology fields.
GoPrintBot: An Interactive E-Commerce for Online Printing Services Nur Izhatie Aisyah Ishak; Nahdatul Akma Ahmad
Journal of Information System and Informatics Vol 5 No 2 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i2.502

Abstract

GoPrintBot is an innovative endeavor focused on creating an interactive e-commerce chatbot tailored specifically for online printing services. The primary objective is to enhance the customer experience by offering a seamless and efficient ordering process, eliminating the need for customers to navigate complex websites or wait for customer service representatives. This study addresses common issues encountered in traditional e-commerce platforms, including unintuitive navigation, ineffective search and filter systems, and slow response times for customer inquiries. The proposed solution involves developing a chatbot system that will revolutionize the online printing industry, significantly improving the customer experience and operational efficiency. The methodology employed encompasses comprehensive requirements gathering, followed by the design and development of the chatbot system using established System Development Life Cycle (SDLC) methodologies. GoPrintBot serves as a prototype, showcasing the potential of chatbots to streamline the online printing process and provide personalized and efficient services. The findings of this study have significant implications for businesses that prioritize customer satisfaction and aim to optimize their online printing services.
From algorithms to classrooms: a decade of artificial intelligence in education research Lim Seong Pek; Nahdatul Akma Ahmad; Faiz Zulkifli; Rabindra Dev Prasad; Ari Muzakir; Jun S. Camara
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i1.34427

Abstract

The education industry has seen a substantial transformation thanks to artificial intelligence (AI), which has improved administrative effectiveness, accessibility, and individualized learning. However, issues like moral dilemmas, digital justice, and policy inconsistencies still exist. From 2015 to 2024, this bibliometric research explores how AI is revolutionizing education. Personalized learning, improved accessibility, and expedited administrative procedures have all been made possible by AI; yet, issues with cost, digital equity, and ethics still exist. We used the Web of Science (WoS) database to conduct a comprehensive bibliometric analysis of 291 peer-reviewed articles that were indexed in the Social Sciences Citation Index (SSCI). The PRISMA methodology was used in the study to find and filter pertinent material. Thematic trends, citation patterns, and co-authorship networks were examined using bibliometric tools like VOSviewer. The progress of generative AI tools like ChatGPT, the importance of AI in democratizing education, and the integration of AI into curriculum building are some of the key discoveries. The report identifies significant nations, organizations, and researchers in AI education and emphasizes global research relationships. Our research raises ethical governance issues while shedding light on AI’s potential to promote individualized learning and increase student engagement. These findings support sustainable development goal (SDG) 4 on quality education by highlighting the need for responsible AI use to address the digital divide. This paper offers useful suggestions for academics, educators, and legislators to maximize AI’s promise while tackling its drawbacks.
Artificial intelligence in education: a bibliometric analysis of emerging trends Lim Seong Pek; Nahdatul Akma Ahmad; Faiz Zulkifli; Fatin Syamilah Che Yob; Usman Ependi; Geoffrey Rhoel C. Cruz
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i1.34428

Abstract

This study investigates the transformative potential of artificial intelligence (AI) in education through a bibliometric analysis of 291 scholarly works retrieved from the Web of Science (WoS) database. Traditional methods of instruction are under threat from the growing demand for individualized and equitable education, particularly in underserved communities. This study looks at how AI innovations, like virtual assistants and adaptive learning platforms, can enhance learning outcomes and the efficacy of instruction in order to address these concerns. The methodology used co-occurrence and co-citation analyses to map research trends and find educational and AI thematic clusters. Pedagogical frameworks, medical education innovations, ethical governance, generative AI applications, and AI acceptance are the five main research areas highlighted in the findings. With 5,246 citations and an H-index of 42, the data show how widely used AI is in both academia and industry. Adaptive learning models, moral dilemmas, and AI literacy are emerging themes. According to this research, AI has the potential to improve accessibility, equity, and quality in education while tackling issues like algorithmic bias and digital divides. This is in line with sustainable development goal 4 (quality education). Teachers, legislators, and technologists can use this study’s thorough intellectual landscape to gain practical insights on how to responsibly incorporate AI into educational systems for more sustainable innovation.