This research compares the accuracy of the C4.5 algorithm and Classification and Regression Tree (CART) for prospective employees selection in companies. This research using dataset with criteria like age, working experience, recent education, marital status, number of abilities possessed, and the result of admission selection test. Testing uses 200 prospective employee selection data manually from a company. Algorithm testing using K-Fold Cross Validation and the accuracy calculation of the algorithm using Confusion Matrix. C4.5 algorithm has a level of accuracy, the success rate of the system, and the level of accuracy of the decision results of 52,83%, 41,48% and 43,98%, and CART algorithm is 53,33%, 44,06%, and 42,81%.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.