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Exploring the elderly user experience in using digital health interventions: a case study of the MySejahtera application Ahmad, Nahdatul Akma; Rosdi, Rosidah; Alias, Nursyahidah; Zainal, Azaliza; Abdul Aziz, Nur Farhanum
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.v13i4.7203

Abstract

In recent years, there has been increased interest in using digital health tools to improve healthcare outcomes and encourage healthy lifestyles. However, older adults, who often face challenges with technology, may encounter difficulties when using these tools. This study focused on understanding how elderly individuals experience the MySejahtera app, a digital health tool designed to help manage health during a pandemic. The research involved 30 elderly users through focus groups, interviews, and user experience evaluations. The study identified key themes in the elderly user experience, such as the need for simplicity, efficiency in the app's interface, ease of learning, concerns about security, and emotional reactions. Recommendations were made to enhance the engagement of elderly users with digital health apps. While the MySejahtera app shows promise for older adults, the study highlights the importance of addressing specific design considerations and providing support to improve user satisfaction. Overall, the research offers valuable insights and recommendations for designing and implementing digital health applications that better meet the needs and preferences of elderly users.
Bridging generations: a scoping review of teaching technology to the elderly using intergenerational strategies Ahmad, Nahdatul Akma; Tengku Shahdan, Tengku Shahrom; Yahya, Norziana
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i2.pp529-539

Abstract

The proportion of the global population aged 60 and above is projected to nearly double by 2050, emphasizing the urgent need for societies to adapt to the challenges posed by an aging population. As the elderly increasingly face difficulties in navigating digital technologies, which are essential for daily tasks and accessing services, the digital divide often leads to digital exclusion. This scoping review investigates intergenerational strategies used to teach technology to older adults. Seventeen studies from 11 countries were analyzed, highlighting six key intergenerational learning strategies: reverse mentoring, virtual learning, collaborative learning, family intergenerational activities, game play learning, and storytelling. These strategies offer diverse methods for enhancing digital literacy and social engagement, with reverse mentoring showing promise in fostering digital competence, and virtual learning promoting inclusivity across generations. However, barriers such as technological access, ongoing support, and cultural differences complicate implementation. This review underscores the importance of adapting instructional approaches to the needs of the elderly while leveraging intergenerational interactions to bridge the digital literacy gap. It calls for sustained efforts to address user needs, provide technical support, and ensure inclusivity, especially for isolated individuals, to maximize the effectiveness and sustainability of these strategies.
Recent issues of elderly intergenerational instructional strategies: a scoping review Ali, Muhammad Asri Mohd; Ahmad, Nahdatul Akma; Ariff, Mohamed Imran Mohamed; Alias, Nursyahidah; Baharum, Zirawani; Shahdan, Tengku Shahrom Tengku
Journal of Education and Learning (EduLearn) Vol 18, No 3: August 2024
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v18i3.21730

Abstract

This scoping review investigates instructional strategies implemented in recent studies to enhance the digital application usage experience for the elderly, addressing emerging issues in the context of a rapidly aging global population. With the World Health Organization predicting a significant increase in the proportion of individuals aged 60 years and above by 2030, the imperative for digital literacy among the elderly becomes crucial. The review, drawing from 14 eligible articles sourced from Web of Science and Scopus, categorizes findings into two main themes: i) intergenerational strategies of instruction and ii) contemporary issues associated with intergenerational approaches. By exploring these dimensions, the paper provides valuable insights for researchers seeking to understand and tackle current challenges in instructing the elderly on digital applications, contributing to the ongoing discourse on improving the quality of life for the aging population through digital technology.
A Novel Hybrid Classification on Urban Opinion Using ROS-RF: A Machine Learning Approach Ependi, Usman; Ahmad, Nahdatul Akma
Jurnal Penelitian Pendidikan IPA Vol 10 No 8 (2024): August
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i8.8042

Abstract

Urban opinion from crowdsourced data often leads to imbalanced datasets due to the diversity of issues related to urban social, economic, and environmental topics. This study presents a novel hybrid approach that combines Random Over-Sampling and Random Forest (ROS-RF) to effectively classify such imbalanced data. Using crowdsourced urban opinion data from Jakarta, experimental results show that the ROS-RF method outperforms other approaches. The ROS-RF classifier achieved an impressive F1-score, recall, precision, and accuracy of 98%. These findings highlight the superior effectiveness of the ROS-RF method in classifying urban opinions, especially those related to social, economic, and environmental issues in urban settings. This hybrid approach provides a robust solution for managing imbalanced datasets, ensuring more accurate and reliable classification outcomes. The study underscores the potential of ROS-RF in enhancing urban data analysis and decision-making processes