Ahmad Pudoli
Program Studi Teknik Informatika, Universitas Budi Luhur

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Penggunaan Algoritma Naive Bayes dalam klasifikasi Pengaruh Pencemaran Udara Dewi Kusumaningsih; Amri Wicahyo; Ahmad Pudoli; Noripansyah .
Jurnal ICT: Information Communication & Technology Vol. 21 No. 1 (2021): JICT-IKMI, Juli 2021
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

one of the factors used to identify environmental problems and living things is information on the effect of air pollution. In overcoming this problem, there are 20 types of classification of the effect of air pollutants on the decision of the Environmental Impact Management Agency (BAPEDAL) for the third attachment regarding the Effect of the Air Pollutant Standard Index for Each Pollutant Parameter. Referring to the problem, this study uses the DKI Jakarta dataset source which collects data from the Air Quality Monitoring Station (SPKU) and uses the Air Pollution Effect Classification application which aims to obtain information on the effect of air pollution by conducting a classification process based on past data from the dataset in 2018 to 2020. The application can run the Knowledge Discovery in Database (KDD) process including data mining or data mining using the classification method with the Naive Bayes algorithm. In this application there is a dataset processing feature into a training data to make the dataset accurate as a determining variable in the Naive Bayes classification process. So, the result of this application is that it can give the results of the classification of the effect of air pollution according to past data. For the testing process, 129 lines of testing data against 4061 lines of training data resulted in an accuracy of 96% of the classification of the effects of air pollution. Thus the conclusion of this study, can provide information on the effect of air pollution that is useful for living things and the environment with a fairly high accuracy of past data..