Stress is a condition caused by interactions between individuals and the environment, giving rise to the perception of demands that originate from situations in a person's biological, psychological and social systems. The field of object classification research has been carried out, making it possible to create technology in the field of object classification with high accuracy. There are many objects classification methods, in this study mainly discuss the K-NN (K-Nearest Neighbor) method. Research on each variable in the K-NN algorithm to determine the best variable in classification. This study will examine the patient who is experiencing stress can be helped to identify the level of stress themselves by answering a series of questionnaires about the symptoms experienced. The accuracy testing is performed using the K-NN algorithm, that k and training data that are different each other including k= 5,8,10,15 and training data of 8,18,38,50 respectively on a patient dataset with symptoms and its weight . This research resulted a patient diagnosis and K-NN maximum accuracy of 82%
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