The quality of coffee bean classification system based on color by using k-nearest neighbor method
Nelly Oktavia Adiwijaya, Hammam Iqomatuddin Romadhon, Januar Adi Putra, Dewangga Putra Kuswanto
Abstract
Abstract Sorting coffee bean nowadays is still done manually, although there is already a support machine for separation through size, but to determine the quality of the seeds remain manual using human power. This coffee bean sorting is in the spotlight to research whether it can be more effective if there is a tool that can directly find out the quality of coffee. This system will make it easier for workers in the field. In addition to saving time, costs will decrease and also the work of workers will be reduced. This paper present the implementation of machine learning method to classify the coffee bean quality. The dataset use 90 coffee bean for three classes and 30 for each class. From the experimental result, the highest accuracy obtain 83%.