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Title: Intelligent Odor-Profile classification of Kelulut honey using Case-Based Reasoning technique (CBR)
Authors: Muhammad Sharfi Najib, Shahrul Hisyam Azih, Nurdiyana Zahed, Muhammad Faruqi Zahari, Wan Muhamad Azmi Mamat, Hadi Manap
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2016
Volume: 11
Issue: 10
Language: English
Nowadays, Kelulut is one of a bee species, yet different in size, it produces a honey that is clearer in colour as compared to natural honey bee. However, study on Kelulut honey grade is not yet extensively explored. Hence, this research aim is to classify Kelulut honey based on smell pattern recognition. In order to sense the smell of Kelulut honey, an E-nose that is comprises of sensor array has been used to measure 2000 samples of dataset from two different types of Kelulut honey. The measured data have been normalized and analysed using statistical method. Then, it has been classified using CBR as an intelligent classifier. It is shown that 100% classification rate of accuracy has been achieved for 2 types of Kelulut honey. The performance measures of CBR in terms of accuracy, specificity, sensitivity have been successfully achieved with 100% performance.
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