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

Hirzan, Alauddin Maulana
Maulana, Charis
Handayani, Sri

JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer)
Vol. 7 No. 2 (2025): Desember 2025

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