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Mohamad Firdaus Che Abdul Rani
Asia Pacific University of Technology and Innovation

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Gamification concept for encouraging lecture attendance Vinothini Kasinathan; Aida Mustapha; Chan Kok Fu; Mohamad Firdaus Che Abdul Rani; Sadesh Manikam
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp482-490

Abstract

New generation of students has high dependence on technology and embrace social learning environments that have low barrier to access. This means in-class lectures are not popular anymore, and in fact has become a burden for them to cope. To resolve the issue of low student attendance, this paper proposes a character growth game with the concept of gamification in education that is able to track and reward student attendance called PetAttendToClass. PetAttendToClass is a client-based system developed using C# and unity3D game engine. Although finding from the UAT session revealed that some users believed that attendance is the responsibility of the student, gamification is meant to turn this mundane responsibility into something motivative, interactive and interesting. It is hoped that by gamifying the class attendance, student will be motivated to attend their daily classes.
Heartbeats: music recommendation system with fuzzy inference engine Vinothini Kasinathan; Aida Mustapha; Tan Sau Tong; Mohamad Firdaus Che Abdul Rani; Nor Azlina Abd Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp275-282

Abstract

In developing a music recommendation system, there are several factors that can contribute to the inefficiency in music selection. One of the problems persists during the music listening is that common music playing application lacks the ability to acquire context of the user. Another problem that common music recommendation system fails to address the is emotional impact of the recommended song. To address this gap, this paper presents a music recommendation system based on fuzzy inference engine that considers user activities and emotion as part of the recommendation parameters. The system includes building a smart music recommendation system that has user profiling capabilities to recommend correct songs based on the user’s preferences, mood and time. Findings of the this paper have shown that Heartbeats’s fuzzy inference engine has successfully achieved its aim, which is to improve users’ music listening experience by giving suitable song recommendation based on user context situation.
Co-Authors Aida Mustapha Chan Kok Fu Nor Azlina Abd Rahman Sadesh Manikam Tan Sau Tong Vinothini Kasinathan