Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Bulletin of Electrical Engineering and Informatics
Noorrezam Yusop
Universiti Teknikal Malaysia Melaka
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Al-Chemy: e-learning platform for foundation students Nur Ilyana Ismarau Tajuddin; Nurul Jannah Abd Rahman; Khairi Azhar Aziz; Noorrezam Yusop; Nor Aziyatul Izni
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4476

Abstract

The unexpected closure of educational institutions as a result of the emergence of COVID-19 prompted the authorities to suggest adopting alternatives to traditional learning methods. E-learning is an innovative approach for delivering electronically mediated, well-designed, learner-centred interactive learning environments by utilizing internet and digital technologies with respect to instructional design principles. This paper presents the implementation and prototyping of an innovative web-based e-learning platform for chemistry course known as Al-Chemy. Al-Chemy was developed for foundation students at Tahmidi Centre, Universiti Sains Islam Malaysia. The rapid application development (RAD) methods have been used in developing Al-Chemy through website wix.com. Al-Chemy was structured with interactive notes, animation, virtual experiment, quizzes, and games. The combination of these activities helps students in learning basic and advanced concepts of chemistry.
A recent hybrid of IoT with adaptive extended Kalman filter fuzzy logic for children’s health dietary Noorrezam Yusop; Massila Kamalrudin; Mohd Nazrien Zaraini; Siti Fairuz Nurr Sardikan
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i3.pp1217-1225

Abstract

The increasing prevalence of childhood obesity highlights the critical need for intelligent dietary monitoring systems that are tailored to individual nutritional requirements. This work describes the creation and testing of an internet of things (IoT) hybrid using an adaptive extended Kalman filter and fuzzy logic (AEKFFL-IoT) model aimed at providing personalised food calorie prediction for children. The system uses IoT devices to collect real-time sensor data, such as height, weight, and BMI, and then employs extended Kalman filter (EKF) algorithms to denoise signals and anticipate trends. Fuzzy logic inference is then utilised to adaptively calculate caloric requirements based on biometric data. Experimental results reveal that the proposed AEKFFL model has a training root mean square error (RMSE) of 21.43 kcal and a testing RMSE of 22.35 kcal, exceeding existing rule-based, wearable, and ANN-driven models in terms of accuracy and generalisation. Furthermore, the system achieves high classification accuracy (94.5%) for BMI categorisation and fuzzy rule application. Comparative examination confirms the model’s adaptability, real-time integration, and mobile deployment capability. This study presents a scalable and intelligent approach for child-centered dietary monitoring, paving the path for personalised digital health interventions.
Co-Authors Khairi Azhar Aziz Massila Kamalrudin Mohd Nazrien Zaraini Nor Aziyatul Izni Nur Ilyana Ismarau Tajuddin Nurul Jannah Abd Rahman Siti Fairuz Nurr Sardikan