Sistem Monitoring dan Pendukung Keputusan Kondisi Kesehatan Pasien Menggunakan Integrasi Sensor Tanda Vital Berbasis IoT Dengan Metode C4.5

Abstract

The development of Internet of Things (IoT) technology has opened up great opportunities in the development of real-time patient health monitoring systems with the integration of vital sign sensors. This study aims to develop a patient health monitoring and decision support system that combines IoT-based vital sign sensors with the C4.5 method as a decision-making algorithm. This system is designed to collect vital data such as heart rate, blood pressure, and body temperature automatically through sensors connected to the ESP32 microcontroller. The data obtained is then processed using the C4.5 method to provide recommendations for patient health conditions accurately and quickly. The research methodology includes the stages of system design, hardware and software development, implementation, and testing in stages. Testing is carried out by running the program on the prepared hardware, interacting with users through input buttons, and displaying measurement results and analysis on the LCD screen. The test results show that the system is able to operate stably, provide real-time vital sign data, and produce decisions that are in accordance with the patient's health condition. This system also has an easy-to-use interface that makes it easy for users to monitor and make decisions. The system implementation uses hardware such as ESP32, MAX30102 sensor for heart rate and blood oxygen, MLX90614 sensor for body temperature, tensiometer for blood pressure, push button as user input, and LCD as display media. The software is developed using a programming environment that supports IoT integration and the C4.5 algorithm. Data communication between sensors and microcontrollers uses serial ports and I2C which are chosen because of their reliability in real-time data transfer. The conclusion of this study is that the IoT based monitoring and decision support system with the C4.5 method developed can provide an effective solution in monitoring patient health conditions accurately and xvi efficiently. This system is expected to be a reference for the development of IoT based health technology in the future and provide real benefits in the medical world, especially in remote patient monitoring and fast and precise clinical decision making.