期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2011
卷号：9
期号：3
页码：547-554
DOI：10.12928/telkomnika.v9i3.747
语种：English
出版社：Universitas Ahmad Dahlan
摘要：Quality standard for coffee as an agriculture commodity in Indonesia uses defect system which is regulated in Standar Nasional Indonesia (SNI) for coffee bean, No: 01-2907-1999. In the Defect System standard, coffee bean is classified into six grades, from grade I to grade VI depending on the number of defect found in the coffee bean. Accuracy of this method heavily depends on the experience and the expertise of the human operators. The objective of the research is to develop a system to determine the coffee bean grading based on SNI No: 01-2907-1999. A visual sensor, a webcam connected to a computer, was used for image acquisition of coffee bean image samples, which were placed under uniform illumination of 414.5 + 2.9 lux. The computer performs feature extraction from parameters of coffee bean image samples in the term of texture (energy, entropy, contrast, homogeneity) and color (R mean, G mean, and B mean) and determines the grade of coffee bean based on the image parameters by implementing neural network algorithm. The accuracy of system testing for the coffee beans of grade I, II, III, IVA, IVB, V, and VI have the value of 100, 80, 60, 40, 100, 40, and 100%, respectively.
