Abstract
Franchising is currently a promising business process where many types of franchises are currently mushrooming and growing rapidly. An algorithm is needed that can classify the type of franchise according to existing attributes. The K-Nearest Neighbor algorithm can produce robust or clean data and effects even for large data sets. The K-Nearest Neighbor algorithm is an algorithm that is able to classify franchise types with an accuracy value of 92.23%. With this high accuracy, it can be ensured that the classification can be clearly seen, where according to the research it was found that the very prospective and prospective classes are in Bakmi Gila and Alfamart. That way, you will get maximum profits by choosing the right franchise
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