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All Journal Bulletin of Electrical Engineering and Informatics
Zaaba, Zarul Fitri
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Electrical & Electronics Engineering

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Privacy during epidemic of COVID-19: a bibliometric analysis Ali, Auwal Shehu; Zaaba, Zarul Fitri; Singh, Manmeet Mahinderjit
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4460

Abstract

1,226 articles on privacy and COVID-19 were published by authors from 69 countries in this year's issue. COVID 19's privacy is now the focus of many researchers' attention. The present body of knowledge on privacy for COVID-19 digital technologies has been thoroughly analyzed, and a concise overview of research status and future developments can be gleaned. This paper conducted a bibliometric examination of privacy using the Scopus dataset. Utilizing VOSviewer software, the relevant literature papers published on this topic were examined to determine the field's development history, research hotspots, and future directions. Over time, there has been a rise in the number of studies published in privacy for COVID-19, particularly after 2020, and the growth rate has been steadily increasing. Regarding published research, the United States and China lead the pack. These articles appeared in primarily English-language journals and conference proceedings. Privacy and COVID-19 research was mostly computer science. The most used terms in privacy and COVID-19 were data privacy and humans. This paper examines the evolution of privacy and COVID-19 research and indicates current research priorities and future research goals. Furthermore, the privacy and COVID-19 study seem to be a promising sphere as this study identifies 26 domains.
MyPharmaceutical: an interactive proof of concept Jie, Khor Ying; Zaaba, Zarul Fitri; Omar, Mohd Adib
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.5896

Abstract

With the rise of health awareness, pharmaceutical and cosmetic products should be verified to protect ourselves from health risks. MyPharmaceutical is a proof-of-concept proposed to provide a mobile application for users to carry out product verification and reporting and a web application for administrative purposes. The data on the registered pharmaceutical and cosmetic products were extracted from national pharmaceutical regulatory agency (NPRA) website. MyPharmaceutical mobile application provides functionalities such as searching the registered product, bookmarking products, reporting products, and tracking report status. The mobile application also implemented a barcode scanner feature to provide ease of product verification. A named entity recognition algorithm is applied with the NLP.js library to provide an improved product search feature for the users, where products can be searched with multiple search criteria in a single input. The web application is proposed to support the mobile application, where the NPRA data admins and officers can manage reported products, publish announcements, verify product data, and utilize the analytic dashboard. The system proposed is expected to provide ease of product verification and reporting to assist the public in choosing safe registered products and a platform for NPRA to manage data and deliver information to the users.
Creating and analysing privacy policies of Malaysia e-commerce using personal data protection act Shehu Ali, Auwal; Zaaba, Zarul Fitri; Mahinderjit Singh, Manmeet; Anuar, Nor Badrul; M. Shariff, Mohd Ridzuan
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.8991

Abstract

Despite legally binding agreements between users and website owners, users often overlook website privacy policies due to their length and complexity. Transparency in these policies is crucial, particularly in Malaysia, where regulatory agencies face challenges ensuring compliance with the personal data protection act (PDPA) of 2010 due to intricate language and complex legal clauses. Machine learning has been used to analyse privacy policies under various legal frameworks, but no dataset currently exists for the Malaysian PDPA. Thus, to bridge this gap, we introduce a pilot corpus of 50 privacy policies specifically tailored to the Malaysian PDPA. This dataset is analysed and made available for academic research, offering insights into privacy regulations and identifying trends in privacy policy transparency. Our findings pave the way for the development of tools to enhance compliance with PDPA standards and improve policy readability for users. The corpus also serves as a foundation for further research in privacy and data protection, encouraging the exploration of automated approaches for policy analysis and regulatory oversight.
Co-Authors Ali, Auwal Shehu Anuar, Nor Badrul Jie, Khor Ying M. Shariff, Mohd Ridzuan Mahinderjit Singh, Manmeet Omar, Mohd Adib Shehu Ali, Auwal Singh, Manmeet Mahinderjit