Identifikasi Kunyit Dan Temulawak Berbasis Citra Digital Menggunakan Metode Naive Bayes Classifier

Airlangga, Raga Satya (2021) Identifikasi Kunyit Dan Temulawak Berbasis Citra Digital Menggunakan Metode Naive Bayes Classifier. Diploma thesis, Politeknik Negeri Jember.

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Abstract

Turmeric and Curcuma even though they are both included in herbal plants, turmeric and Curcuma are not the same. A person will easily identify the difference between turmeric and Curcuma by smelling it. However, this is not the case for a computer that is not equipped with an intelligent system. So with the similarities and differences between turmeric and Curcuma, it can be developed into a digital image-based research. This study aims to make it easier to identify between turmeric and Curcuma Therefore, the researchers made a classification system on turmeric and Curcuma. In this study, the input parameters used include: 8 GLCM features, namely G0 contrast, G0 entropy, G45 contrast, G45 entropy, G90 contrast, G90 entropy, G135 contrast, G135 entropy and 1 color feature, namely Green. The results of the classification system for identification of differences in turmeric and Curcuma using Naïve Bayes obtained the highest accuracy of 91,66% Key words: Turmeric, Curcuma, GLCM, Naïve Bayes, Color Feature

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