Prediksi Gas Karbon Monoksida dengan Jaringan Syaraf Tiruan berbasis Internet of Things

Alauddin Maulana Hirzan; Charis Maulana; Sri Handayani

doi:10.26905/jasiek.v7i2.14356

Authors

Alauddin Maulana Hirzan Universitas Semarang https://orcid.org/0000-0002-2486-6787
Charis Maulana Universitas Semarang
Sri Handayani Universitas Semarang

DOI:

https://doi.org/10.26905/jasiek.v7i2.14356

Keywords:

Artificial Neural Network, Carbon Monoxide, Internet of Things, Linear Regression, Prediction

Abstract

Carbon monoxide is a dangerous gas that can cause fatal effects in humans if inhaled in large quantities. To detect it, a model has been developed. This study proposes a prediction model using an Artificial Neural Network (ANN) algorithm to predict carbon monoxide. Of the four ANN models evaluated, the ANN-5K model showed the best performance with an accuracy of 80.18%, followed by ANN-6K with an accuracy of 77.13%, ANN-4K with 66.44%, and ANN-3K with 53.14%. When compared to linear regression, which only had an accuracy of 57.50%, the ANN-5K model was still superior. Thus, the proposed ANN-5K model proved to be more accurate and had a lower error rate compared to other models. The main contribution of this research is a prototype equipped with an ANN model to predict carbon monoxide gas

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