Komparasi Algoritma Support Vector Machine Dan CART Untuk Klasifikasi Kualitas Udara Dki Jakarta

Abstract

Air quality or air quality is a measure of air condition at a certain time and place that is measured and/or tested based on certain parameters. Exposure to high levels of air pollution can cause various harms to health, which can increase the risk of respiratory infections, heart disease and lung cancer. Jakarta is ranked 12th as a regional capital for 2021 with an annual average concentration of PM2.5 – the highest on average. As for the Southeast Asia region, Jakarta is ranked 6th as the most populous regional polluted city. Uniform and precise air quality classification can be an important role for planning and introduction of relevant policies and regulations for air pollution management by decision makers, in carrying out the classification can use technical data mining. The Support Vector Machine (SVM) and Classification and Regression Tree (CART) algorithms are part of the classification method. In this study, an analysis and comparison was carried out to determine the performance of the two methods in classifying air quality in Jakarta in 2021. And the resulting SVM classification has an accuracy value of 95.05% and an error classification value of 4.95%, and the results of the CART classification are with an accuracy value of 99.67% and a misclassification value of 0.33%. It can be interpreted that the CART algorithm is better than SVM in classification classification to determine air quality in DKI Jakarta.