KLASIFIKASI DATA MINING UNTUK MENENTUKAN KUALITAS UDARA DI PROVINSI DKI JAKARTA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (K-NN)

Abstract

Air plays an important role in maintaining the life of living things on earth. Metabolic processes that occur in the bodies of living things cannot take place without oxygen from the air. The air pollution problem in DKI Jakarta is very serious and can cause health problems such as irritation of the respiratory tract, respiratory diseases, and long-term health problems such as cardiovascular disease and lung cancer. Air pollution can also affect environmental quality, reduce visibility, and damage ecosystems. The purpose of this study is to determine the accuracy of classifying air quality in DKI Jakarta province. The data mining method that the author uses is the K-Nearest Neighbors (K-NN) algorithm. From the results of the evaluation process of the K-Nearest Neighbors (K-NN) algorithm using the K-5 fold that has been carried out using the RapidMiner tool, the results of K-2 fold accuracy of 73.97%, K-3 fold accuracy of 72.60%, K-4 fold accuracy of 72.60%, and K-5 fold accuracy of 75.35%.