Abstract
Each customer has different coffee tastes and of course in each coffee shop has a different blend of coffee, so it takes a Knowledge Management in choosing a coffee drink that suits the taste of the customer. This thesis discusses how expert systems solve these problems by using the Case Based Reasoning method and PHP-based Nearest Neighbor Algorithm to calculate the amount of similarity between the previous case and the new case. The results of the analysis of contingency factors from Knowledge Management using the framework of Becerra-Fernandez shows that Exchange and Internalization rank 1 and 2, with these results, Exchange and Internalization become the priority of the development of knowledge management process and can find coffee that suits customers' tastes.
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