Kendali Aliran dan Tekanan Adaptif dengan Metode Artificial Neural Network pada Alat Terapi Oksigen

ABYANUDDIN SALAM, NUR WISMA NUGRAHA, WILDAN ALFARIDHANI

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ABSTRAK

Penelitian ini bertujuan untuk merancang prototype pengendalian aliran dan tekanan adaptif pada alat terapi oksigen. Sensor yang digunakan yaitu sensor MAX30100 untuk membaca saturasi oksigen dan sensor MLX90614 sebagi sensor yang dapat menghitung Respiration Rate atau laju napas. Metode yang digunakan yaitu Artificial Neural Network yang diimplentasikan pada Raspberry Pi. Sistem akan bekerja dengan memprediksi nilai laju aliran dan tekanan oksigen yang diperlukan pasien berdasarkan nilai Respiration Rate (RR). Artificial Neural Network (ANN) dapat diimplmentasikan pada rancangan alat terapi oksigen, dengan persentase akurasi Output ANN terhadap perhitungan yaitu 99,39%, sedangkan persentase akurasi ANN terhadap pembacaan aliran oksigen yang terbaca pada sensor flow sebesar yaitu 94,73% dan persentase akurasi ANN terhadap pembacaan tekanan oksigen pada sensor pressure sebesar 89,03%.

Kata kunci: Terapi Oksigen, Respiration Rate, Artificial Neural Network

 

ABSTRACT

This research aims to design a prototype of flow and pressure control in an adaptive oxygen therapy device. The sensors used are MAX30100 sensors to read oxygen saturation and MLX90614 sensors as sensors that can calculate Respiration Rate or breath rate. The method used is Artificial Neural Network which is implemented on Raspberry Pi. The system will work by predicting the value of the flow rate and oxygen pressure required by the patient based on the Respiration Rate (RR) value. Artificial Neural Network (ANN) can be implemented in the design of oxygen therapy devices, with the percentage of ANN Output accuracy to the calculation of 99.39%, while the percentage of ANN accuracy on oxygen flow readings on the flow sensor is 94.73% and the percentage of ANN accuracy on oxygen pressure readings on the pressure sensor is 89.03%.

Keywords: Oxygen Therapy, Respiration Rate, Artificial Neural Network


Kata Kunci


Terapi Oksigen; Respiration Rate; Artificial Neural Network

Teks Lengkap:

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Referensi


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DOI: https://doi.org/10.26760/elkomika.v12i1.133

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