Klasifikasi Pencemaran Udara Di DKI Jakarta Menggunakan Metode Naïve Bayes

Abstract

Air quality index in Indonesia shows Jakarta in 5^th position with the highest air pollution. Naïve Bayes is one of the data mining methods that has excellent accuracy with simple calculations in the field of classification learning. In this study, Naïve Bayes is used to classify air quality based on air pollution standard index data in the Special Capital Region of Jakarta within 12 (twelve) months. The processed variables include PM10, PM25, SO2, CO, O3, and NO2. By using accuracy value evaluation data, the results show that Naïve Bayes is effectively used for air pollution classification with an accuracy rate of 91,96%.