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Nurul Aswa Omar
Universiti Tun Hussein Onn Malaysia

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Fasting Ontology in Pillars of Islam Sara Afiqah Mohd Zailani; Nurul Aswa Omar; Aida Mustapha; Mohd Hisyam Abdul Rahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp562-569

Abstract

The development of Fasting Ontology in the Pillars of Islam is presented in this paper and has been built based on reliable sources of Islamic Knowledge. The METHONTOLOGY methodology is used for the ontology development, which include identifying motivation scenarios, creating the competency questions, implementation and evaluation. From the beginning of the development of life cycle, the ontology was appraised from the competency questions and the outcome were clear. Therefore, this ontology can link each concept specifically to the individual verse together with the Tafsir that is related to the topics. The ontology proposed will be part of a larger ontology on Five Pillars of Islam. This development of the ontology is intended to refer to the field of learning for other purpose. For instance, search engine, chatbot, expert system or knowledge-based system.
Data Mining Approach to Herbs Classification Adillah Dayana Ahmad Dali; Nurul Aswa Omar; Aida Mustapha
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp570-576

Abstract

Herbs are one of the high-value products in Malaysia. The term ‘herbs’ has more than one definition. It is also demanding by multiple manifolds. Herbs are used in many sectors nowadays. The ability to identify variety herbs in the market is quite hard without the intervention of human experts. Unfortunately, human experts are prone to error. Herbs classification is able to assist human experts and at the same time minimizing the intervention. This research performs identification and classification of herbs based on image capture ad variety of classification algorithms such as an Artificial Neural Network (ANN), K-Nearest Neighbors (IBK), Decision Table (DT) and M5P Tree algorithms. The selected algorithms are implemented and evaluated to their relative performance and IBK is found to produce the highest quality outputs.
Co-Authors Adillah Dayana Ahmad Dali Aida Mustapha Mohd Hisyam Abdul Rahim Sara Afiqah Mohd Zailani