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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics

Ahmad Firdaus Zainal Abidin

Universiti Malaysia Pahang

Author-ID : 2388495

Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 8 Documents Claim Missing Document

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Augmented reality: effect on conceptual change of scientific Danakorn Nincarean Eh Phon; Ahmad Firdaus Zainal Abidin; Mohd Faizal Ab Razak; Shahreen Kasim; Ahmad Hoirul Basori; Tole Sutikno
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

In recent years, Augmented Reality (AR) has received increasing emphasis and researchers gradually promote it Over the worlds. With the unique abilities to generate virtual objects over the real-world environment, it can enhance user perception. Although AR recognised for their enormous positive impacts, there are still a ton of matters waiting to be discovered. Research studies on AR toward conceptual change, specifically in scientific concept, are particularly limited. Therefore, this research aims to investigate the effect of integrating AR on conceptual change in scientific concepts. Thirty-four primary school students participated in the study. A pre-test and post-test were used to assess participants’ understanding of the scientific concepts before and after learning through AR. The findings demonstrated that 82% among them had misconceptions about the scientific concepts before learning through AR. However, most of them (around 88%) able to correct their misconceptions and shifted to have a scientific conceptual understanding after learning through AR. These findings indicate that AR was effective to be integrated into education to facilitate conceptual change.

Adaboost-multilayer perceptron to predict the student’s performance in software engineering Ahmad Firdaus Zainal Abidin; Mohd Faaizie Darmawan; Mohd Zamri Osman; Shahid Anwar; Shahreen Kasim; Arda Yunianta; Tole Sutikno
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Software Engineering (SE) course is one of the backbones of today's computer technology sophistication. Effective theoretical and practical learning of this course is essential to computer students. However, there are many students fail in this course. There are many aspects that influence a student's performance. Currently, student performance analysis methods just focus on historical achievement and assessment methods given in the class. Need more research to predict student's performance to overcome the problem of student failing. The objective of this research is to perform a prediction for student's performance in the SE using enhanced Multilayer Perceptron (MLP) machine learning classification with Adaboost. This research also investigates the requirements of each student before registering in this course. This research achieved 87.76 percent accuracy in classifying the performance of SE students.

Co-Authors Ahmad Hoirul Basori Arda Yunianta Danakorn Nincarean a/l Eh Phon Danakorn Nincarean Eh Phon Gertrude David Mohd Faaizie Darmawan Mohd Faizal Ab Razak Mohd Tajuddin Abdullah Mohd Zamri Osman Salwana Mohamad Asmara Shahid Anwar Shahreen Kasim Tole Sutikno Wan Isni Sofiah Wan Din Yundari, Yundari

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Journal : Bulletin of Electrical Engineering and Informatics