Implementasi Fuzzy Inference System untuk Klasifikasi Gas Karbondioksida - Faricha, Anifatul; Arif, Rangga R.; Adiputra, Dimas; Dwi Putranto, Rifki (Jurnal Algoritma, 2025)
Good air quality is vital for human health, one important factor being the range of carbon dioxide levels that can be tolerated by the respiratory system. In this study, the type of gas sensor used was an electrochemical sensor, which has a higher level of selectivity than semiconductor sensors, resulting in more accurate carbon dioxide gas measurements and easier air quality classification. For carbon dioxide readings, this study used an MG-811 gas sensor. Carbon dioxide readings were also compared with a commercial gas measuring device, namely BOSEAN. In addition, the fuzzy inference system method was used to classify air quality into three levels of conditions, namely low, normal, and alert. Based on the data analysis results, the mean absolute percentage error (MAPE) value for the comparison of carbon dioxide gas readings between the MG-811 gas sensor and BOSEAN is 2.23%. Overall, the fuzzy inference system that has been developed works well and can be used to classify air quality automatically.