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All Journal The Indonesian Journal of Computer Science
Daffa Syah Alam
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Penentuan Tingkat Stres berdasarkan Bio-Parameter Menggunakan Variasi Kernel Support Vector Machine Daffa Syah Alam; Rokhana, Rika; Arief, Zainal
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4495

Abstract

System for detecting a person's stress level based on bio-parameters is blood pressure, heart rate, and respiratory rate. Measurements of blood pressure, heart rate, and respiratory rate in order to detect the condition of a person's stress level are carried out non-invasively or don’t damage the nervous tissue in the body and routinely. Heart rate measurement using MAX30102 sensor on the finger. Measurement of blood pressure using the MPX2050GP pressure sensor by placing cuff on the person's arm. While measuring the breathing rate using the MAX9814 micondensor sensor. In determining or classifying stress level conditions from non-invasive measurement parameters of blood pressure, heart rate and respiratory rate using Support Vector Machine (SVM) method with specified kernel variations. The classification of stress level conditions consists of four classes including normal, mild stress, moderate stress and severe stress. So that a dataset of 71 data is obtained with the data augmentation process and the accuracy of each SVM kernel variation used is obtained.
Co-Authors Rokhana, Rika Zainal Arief