KLASIFIKASI KUALITAS UDARA MENGGUNAKAN METODE NAIVE BAYES DAN FUZZY NAIVE BAYES DENGAN DATA HILANG DAN DATA IMPUTASI

PUTRA, GUSNADI JULIANSAH and Resti, Yulia and Zayanti, Des Alwine (2025) KLASIFIKASI KUALITAS UDARA MENGGUNAKAN METODE NAIVE BAYES DAN FUZZY NAIVE BAYES DENGAN DATA HILANG DAN DATA IMPUTASI. Undergraduate thesis, Sriwijaya University.

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Abstract

Healthy air plays a very important role in the survival of life, whereas polluted air will have a negative impact on living things. Therefore, it is necessary to classify air quality. The aim of this research is to carry out classification to determine good air quality using the Naive Bayes and Fuzzy Naive Bayes methods with missing data and imputed data. The research results show that using both the Naive Bayes and Fuzzy Naive Bayes methods by removing missing data obtains better results than imputing missing data. Classification of air quality data using the Naive Bayes method by removing missing data obtained an accuracy of 85.92%, precision of 8.21%, recall of 36.01% and Fscore of 31.45%. Meanwhile, classification of air quality data using the Naive Bayes method by imputing any missing data obtained an accuracy of 82.71%, precision of 23.78%, recall of 24.29% and Fscore of 20.72%. Classification of air quality data using the fuzzy Naive Bayes method by removing missing data obtained an accuracy of 85.6%, precision of 44.03%, recall of 46.04% and Fscore of 43.08%. Meanwhile, classification of air quality data using the fuzzy Naive Bayes method by imputing any missing data obtained an accuracy of 84.89%, precision of 27.2%, recall of 26.47% and Fscore of 24.97%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Air Quality, Fuzzy Sets, Naive Bayes, Fuzzy Naive Bayes
Subjects:	Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics > QA279.C663 Response surfaces (Statistics)
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Gusnadi Juliansah Putra
Date Deposited:	24 Mar 2025 02:47
Last Modified:	24 Mar 2025 02:47
URI:	http://repository.unsri.ac.id/id/eprint/169765

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