<![CDATA[Artificial Neural Network (ANN) is a branch of Artificial Intelligence which possesses great potential. However, ANN has a huge drawback: the need for complex parameters to train a developed ANN in order to provide the right solution to the proposed problem. One way to overcome this weakness is the use of Genetic Algorithm as the best parameter selection method for a ANN. In this study, said concept was applied in an application that aims to help solve one of the aspects of design that has a high significance, namely color selection, by implementing both technologies simultaneously into a predictive system. To predict colors based on given parameters, the algorithm is formed to distinguish how colors are used so that they are able to group colors into specific color categories to then be combined to form a palette, which can be the basis of a color scheme for various design purposes. Based on the results of this study, researchers hope to provide additional insights into various fields that can synergize with Artificial Intelligence and its derivative disciplines to improve efficiency in various occupations, of which design is one of them.]]>
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