Blood Pressure and Heart Rate Measurement for Hypertension Classification Using the K-Nearest Neighbors Method Based on IoT - Siti Salwa Nurhadiva; Aryanti Aryanti; Sarjana Sarjana (PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic, 2024)
This research aims to develop a hypertension classification system based on measuring blood pressure and heart rate using the K-Nearest Neighbor (KNN) method and storing data on the Thingspeak cloud server. Hypertension is a major health problem that requires regular monitoring for effective prevention and management. This research created a tool that can measure blood pressure and heart rate using the KNN method as a classification. The data was collected using a sensor device integrated with Thingspeak for real-time data storage and analysis. The KNN method is used to classify measurement data into optimal, normal, prehypertension, grade 1 hypertension, and grade 2 hypertension categories. The implementation of data storage on the Thingspeak cloud server allows easy data access and efficient analysis, and supports continuous health monitoring. In conclusion, the system developed can be an effective tool in monitoring and classifying hypertension, and has the potential to be applied on a wider scale for public health management.