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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Rosmawati Nordin
Universiti Teknologi MARA
Computer Science & IT Electrical & Electronics Engineering Engineering

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A mapping study on blood glucose recommender system for patients with gestational diabetes mellitus Shuhada Mohd Rosli; Marshima Mohd Rosli; Rosmawati Nordin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.176 KB) | DOI: 10.11591/eei.v8i4.1633

Abstract

Blood glucose (BG) prediction system can help gestational diabetes mellitus (GDM) patient to improve the BG control with managing their dietary intake based on healthy food. Many techniques have been developed to deal with blood glucose prediction, especially those for recommender system. In this study, we conduct a systematic mapping study to investigate recent research about BG prediction in recommender systems. This study describes an overview of research (2014-2018) about BG prediction techniques that has been used for BG recommender system. As results, 25 studies concerning BG prediction in recommender system were selected. We observed that although there is numerous studies published, only a few studies took serious discussion about techniques used to incorporate the BG algorithms. Our result highlighted that only one study discusses hybrid filtering technique in BG recommender system for GDM even though it has an ability to learn from experience and to improve prediction performance. We hope that this study will encourage researchers to consider not only machine learning and artificial intelligent techniques but also hybrid filtering technique for BG recommender system in the future research.
A mapping study on blood glucose recommender system for patients with gestational diabetes mellitus Shuhada Mohd Rosli; Marshima Mohd Rosli; Rosmawati Nordin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.176 KB) | DOI: 10.11591/eei.v8i4.1633

Abstract

Blood glucose (BG) prediction system can help gestational diabetes mellitus (GDM) patient to improve the BG control with managing their dietary intake based on healthy food. Many techniques have been developed to deal with blood glucose prediction, especially those for recommender system. In this study, we conduct a systematic mapping study to investigate recent research about BG prediction in recommender systems. This study describes an overview of research (2014-2018) about BG prediction techniques that has been used for BG recommender system. As results, 25 studies concerning BG prediction in recommender system were selected. We observed that although there is numerous studies published, only a few studies took serious discussion about techniques used to incorporate the BG algorithms. Our result highlighted that only one study discusses hybrid filtering technique in BG recommender system for GDM even though it has an ability to learn from experience and to improve prediction performance. We hope that this study will encourage researchers to consider not only machine learning and artificial intelligent techniques but also hybrid filtering technique for BG recommender system in the future research.
A mapping study on blood glucose recommender system for patients with gestational diabetes mellitus Shuhada Mohd Rosli; Marshima Mohd Rosli; Rosmawati Nordin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.176 KB) | DOI: 10.11591/eei.v8i4.1633

Abstract

Blood glucose (BG) prediction system can help gestational diabetes mellitus (GDM) patient to improve the BG control with managing their dietary intake based on healthy food. Many techniques have been developed to deal with blood glucose prediction, especially those for recommender system. In this study, we conduct a systematic mapping study to investigate recent research about BG prediction in recommender systems. This study describes an overview of research (2014-2018) about BG prediction techniques that has been used for BG recommender system. As results, 25 studies concerning BG prediction in recommender system were selected. We observed that although there is numerous studies published, only a few studies took serious discussion about techniques used to incorporate the BG algorithms. Our result highlighted that only one study discusses hybrid filtering technique in BG recommender system for GDM even though it has an ability to learn from experience and to improve prediction performance. We hope that this study will encourage researchers to consider not only machine learning and artificial intelligent techniques but also hybrid filtering technique for BG recommender system in the future research.
Review of traffic control techniques for emergency vehicles Wan Mohd Hafiz bin Wan Hussin; Marshima Mohd Rosli; Rosmawati Nordin
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp1243-1251

Abstract

Traffic control system play an important role to manage traffic congestion on the road especially during peak hours and peak seasons. One of the main challenges is to control the traffic when there are emergency cases at traffic light intersection especially peak hours. This could affect the route for emergency vehicles such as ambulance, fire brigade and police car to reach their destination. Due to the increase of traffic congestion during peak hours and peak seasons in Malaysia, there is a need for further evaluation of traffic control techniques. This paper reviewed and consolidated information on the different types of the existing traffic control system for road traffic management such as Radio Frequency Identification (RFID), wireless sensor network and image processing. This paper analysed and compared on the design, benefits and limitations of each technique. Through the reviews, this paper recommends the best traffic control technique for emergency vehicle that offers low price, low maintenance and can be used in various areas of applications.
Co-Authors Marshima Mohd Rosli Shuhada Mohd Rosli Wan Mohd Hafiz bin Wan Hussin