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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Lizawati Salahuddin
Universiti Teknikal Malaysia Melaka
Computer Science & IT Electrical & Electronics Engineering

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A conceptual integrated health information systems framework in postnatal care for modern and traditional malay medicine Raja Rina Raja Ikram; Lizawati Salahuddin; Mohd Hariz Mohd Naim; Ariff Idris; Nor Afirdaus Zainal Abidin; Nadiah Ishak; Noor Raihan Ab Hamid
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 3: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i3.pp1531-1539

Abstract

This paper proposes an integrated health information systems framework for Traditional Malay Medicine (TMM) and modern medicine in the field of postnatal care. A qualitative study was conducted via healthcare experts in the field of modern medicine and Traditional Malay Medicine to assess the current situation and identify the research gap and point of isolation between both traditional and modern medicine field. A total of 26 healthcare practitioners whom represented five different set of healthcare organisations participated in this study. The healthcare practitioners consist of modern and traditional Malay medicine background with and without proper training. Results show that there is a gap in the current people, process and technology areas of the current framework. A novel conceptual framework, MyPostnatal, proposes the existence of a sufficiently generic, extensible in-formation model where new data sources can be integrated without major changes to the data scheme. Human and organization factors are also highlighted to stimulate the adoption towards electronic health records.
A review of the automated timber defect identification approach Teo Hong Chun; Ummi Raba’ah Hashim; Sabrina Ahmad; Lizawati Salahuddin; Ngo Hea Choon; Kasturi Kanchymalay
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2156-2166

Abstract

Timber quality control is undoubtedly a very laborious process in the secondary wood industry. Manual inspections by operators are prone to human error, thereby resulting in poor timber quality inspections and low production volumes. The automation of this process using an automated vision inspection (AVI) system integrated with artificial intelligence appears to be the most plausible approach due to its ease of use and minimal operating costs. This paper provides an overview of previous works on the automated inspection of timber surface defects as well as various machine learning and deep learning approaches that have been implemented for the identification of timber defects. Contemporary algorithms and techniques used in both machine learning and deep learning are discussed and outlined in this review paper. Furthermore, the paper also highlighted the possible limitation of employing both approaches in the identification of the timber defect along with several future directions that may be further explored.
Co-Authors Ariff Idris Kasturi Kanchymalay Mohd Hariz Mohd Naim Nadiah Ishak Ngo Hea Choon Noor Raihan Ab Hamid Nor Afirdaus Zainal Abidin Raja Rina Raja Ikram Sabrina Ahmad Teo Hong Chun Ummi Raba’ah Hashim