Implementasi Metode Decision Tree untuk Sistem Pendeteksi Stres berdasarkan Detak Jantung dan Kelenjar Keringat - Rejeki Puspa Dinasty; Edita Rosana Widasari; Hurriyatul Fitriyah (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2023)
Emotions greatly affect individual behavior and stress refer to physiological responses that occur when individuals fail to respond appropriately to emotional or physical threats. For this reason, it is important to know a person's mental stress, so that further action can be taken, so as not to have a serious impact on physical and mental health. Using the decision tree method with HR and GSR features to detect stres is useful because this method is able to handle data that is not well structured and provides an easily understood visual representation of the decision making process. In addition, HR and GSR features can provide useful information about a person's physical state that can be used to identify stress levels. From the results of system testing with MAX30102 and GSR sensors The accuracy of reading MAX30102 and GSR sensors is seen from the accuracy of the level stress results displayed and the value of the respondent questionnaire results. Stres detection systems through the heart rate and sweat glands have an accuracy of 98.5% while for the average system computing time needed to detect stress of 36802.83 ms or 36.80 seconds. The accuracy results were obtained by testing 24 respondents.