IMPLEMENTASI ALGORITMA BAYESIAN NETWORK DALAM MEMPREDIKSI INDEKS KUALITAS UDARA

MUAFFAN, ADITIYA and Firsandaya Malik, Reza (2020) IMPLEMENTASI ALGORITMA BAYESIAN NETWORK DALAM MEMPREDIKSI INDEKS KUALITAS UDARA. Undergraduate thesis, Sriwijaya University.

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Abstract

This research was conducted to be able to predict the level of air pollution by using parameters of air pollution carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), particulate matter (PM2.5) by implementing the Bayesian Network algorithm as algorithm in classifying the independent of each air pollution variable. In addition, this study also calculates the level of accuracy of the prediction results by comparing actual data with testing data. The data used in this study is data downloaded from the United States Environmental Protection Agency (EPA) website, with 365 records of data in the form of an index of the value of air pollution quality in the city of California in January-December 2019 which is used for the training process and testing process in the research. this. The distribution for testing data is 304 data records and training data is 61 data records. Tests were carried out using Jupyter Notebook software and WEKA software ver.3.8.4. The results of prediction testing with the Bayesian Network algorithm obtained in the Jupyter Notebook software are 90.14 and the results on WEKA software ver.3.8.4 are 98.63%, 99.08%, 98.63, and 100%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Wireless Sensor Network, Bayesian Network, Prediction, Air Pollution, Air Pollution Standard Index, Accuracy
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 10164 not found.
Date Deposited:	22 Jan 2021 04:14
Last Modified:	22 Jan 2021 04:14
URI:	http://repository.unsri.ac.id/id/eprint/40797

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