
Wheat Bread producers are required to produce quality products and are liked by consumers. Increasing the quality of bread will certainly have an impact on sales to be generated. One of the efforts in improving the quality is by doing Hedonic test and Hedonic Quality test. This study aims to develop a system capable of providing an assessment of new products to be released on the market. Hedonic quality is used as a variable for assessing bread products with 4 variables, which include flavor, taste, appearance, and texture. While the hedonic test using six classes is very very like, very like, like, rather like, and do not like, then this result will be used as a class of Knowledge Based (KB). This research uses Radial Basis Function Network (RBFN) algorithm, yielding 98,8% accuracy with 10 fold testing technique. The final goal of the development of this system will create a system capable of providing an assessment of a wheat bread product.
organoleptic test, machine learning, wheat bread, radial basis function network, T58.6-58.62, Management information systems
organoleptic test, machine learning, wheat bread, radial basis function network, T58.6-58.62, Management information systems
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