The desire to end someone's life commonly triggered by depression or mental health. One way to detect whether someone is depressed is by checking whether the person is constantly stressed for a long time. Electroencephalograph (EEG) is one of physiological signal that can be used for monitoring someone's mental condition, such as stress. The proposed and developed Stress Detection and Meditation Application is an application that can be used for meditating and reducing stress level by using EEG to get brainwave signals. In this developed system, Fast Fourier Transform (FFT) was used as the feature extraction and k-Nearest Neighbor (k-NN) was used to classify the features and detect whether the person is stressed or not. The Delta, theta, alpha, and beta waves as the features were the most suitable feature type for the stress detection and meditation application, while the value of k = 3 in k-NN classification provides the best k value with 80% accuracy.