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p-Index From 2020 - 2025
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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
Farashazillah Yahya
Universiti Malaysia Sabah
Computer Science & IT Electrical & Electronics Engineering

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Mobile learning application: flipped classroom Aslina Baharum; Lim Yi Wan; Farashazillah Yahya; Nadia Hanin Nazlan; Nor Azida Mohamed Nor; Ismassabah Ismail; Noorsidi Aizuddin Mat Noor
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i2.pp1084-1090

Abstract

This study attempts to illustrate the phases of designing a flipped learning mobile application. It is worth noting that changes in students’ learning behavior should be met by changes in the classroom – particularly on the way a course should be delivered. Studies have shown that students who learn using the flipped learning method are less likely to fail as opposed to their counterparts in the traditional classroom setting. The rising importance and popularity of flipped learning necessitates the development of a mobile application that assists both students to learn and allow instructors to manage their course via their mobile devices, almost anywhere and anytime. The software development life cycle (SDLC) is divided into four distinct phases: 1) Preliminary study, 2) content design, 3) System design and development, and 4) System evaluation. The effectiveness of the application is tested using electroencephalography (EEG). The findings suggest effectiveness of the mobile application falls within the acceptable range. Improvements for the flipped learning mobile application is also presented.
A review of hyperspectral imaging-based plastic waste detection state-of-the-arts Owen Tamin; Ervin Gubin Moung; Jamal Ahmad Dargham; Farashazillah Yahya; Sigeru Omatu
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp3407-3419

Abstract

Plastic waste issues emerged from the build-up of plastics that negatively impacts the environment. As a result, plastic waste detection is proposed in many research studies to tackle the problems. Therefore, this paper aims to review hyperspectral imaging techniques and machine learning in plastic waste detection. Hyperspectral imaging techniques are found to be effective in detecting plastic waste and microplastics as they were able to capture plastic reflectance spectral by using the near-infrared sensor. However, the review also shows that hyperspectral imaging techniques were less efficient in capturing the electromagnetic spectrum of black plastics due to carbon-black absorption properties. Carbon-black strongly absorbs light in the ultraviolet and infrared spectral range of the electromagnetic spectrum, therefore not detected by the near-infrared sensor. This paper also reviews how machine learning can alternatively detect and sort all types of waste, including plastics. Multiple studies show that the machine learning model achieved good accuracy in detecting all types of plastics based on the waste dataset. Finally, it can be seen that the spectral information of plastic can be used as feature extraction for machine learning models for better plastic detection. It is hoped that this study will contribute to more systematic research on the same topic.
Effective dashboards for urban water security monitoring and evaluation Zada Qusyairin Mohd Zainuddin; Farashazillah Yahya; Ervin Gubin Moung; Bashirah Mohd Fazli; Mohammad Fikry Abdullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4291-4305

Abstract

This paper reviews the factors affecting effective dashboards for urban water security monitoring and evaluation. Urban water security is a constantly evolving field influenced by several factors, including changes in climate, ecosystems, socio-economic status, and human beings. Although urban water security has been discussed in some parts of the literature, there has been minimal literature review that focused on the factors of urban water security and the effective dashboards for monitoring and evaluation. Using systematic literature review (SLR) and preferred reporting items for systematic reviews and meta-analysis (PRISMA), this paper reviewed 143 articles. The result shows growth in the environmental informatics landscape since the last ten years when the first article on the urban water management dashboard was published. The visual design was the most frequently discussed factor for dashboards, followed by user customization. It also shows that this topic can go deeper to integrate both factors and design an effective environmental dashboard. The discussion identified three potential opportunities for future research in water security and informatics: i) exploring other dimensions of effective dashboards, ii) considering more research on the environmental dashboard, and iii) investigating the real-life application of dashboards in urban water security.
Co-Authors Aslina Baharum Bashirah Mohd Fazli Ervin Gubin Moung Ismassabah Ismail Jamal Ahmad Dargham Lim Yi Wan Mohammad Fikry Abdullah Nadia Hanin Nazlan Noorsidi Aizuddin Mat Noor Nor Azida Mohamed Nor Owen Tamin Sigeru Omatu Zada Qusyairin Mohd Zainuddin