identification system model for classifying superior variety of cassava

laksmana, Indra and Syelly, Rosda and Tazar, Nurzarrah (2017) identification system model for classifying superior variety of cassava. In: global innovation on sustainability and sustainable development. SAFE Network.

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Abstract

cassava is very potential for being processed as a vegetable,animalfeed,chips,or bioethanol through fermentation proces etc. the need for superior cassava varieties as raw materials is expected will produce a high quality product. this research designs an identification system for three varieties of cassava based on levels of cyanide acid by applying a heuristic search of alogrithm using genetic operations. the similarity of cassava varieties to each other very close. in order to identify them, this research proposes genetic programming that is structured and represented in tree form. the experiments in this study used binary code data resulting form the booleanizing processs of thress varieties of cassava. binary code data is divided into training identify. the obtained rule consists of 500.000 population parameters, 20-25 nodes consisting of function set AND,OR,NOR abd 52 terminal sets, crossover probability of 0.9 and 0.1 mutations of 3 generations. the resulting rule can be utilized by the community in identifiying cassava varieties

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