KLASIFIKASI KUALITAS UDARA DKI JAKARTA BERDASARKAN INDEKS STANDAR PENCEMAR UDARA MENGGUNAKAN METODE REGRESI LOGISTIK MULTINOMIAL DAN K-NEAREST NEIGHBOR

FUTRI, RISKI WULANDARI and Resti, Yulia and Zayanti, Des Alwine (2024) KLASIFIKASI KUALITAS UDARA DKI JAKARTA BERDASARKAN INDEKS STANDAR PENCEMAR UDARA MENGGUNAKAN METODE REGRESI LOGISTIK MULTINOMIAL DAN K-NEAREST NEIGHBOR. Undergraduate thesis, Sriwijaya University.

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Abstract

DKI Jakarta's air quality has changed as a result of increased physical development of the city and industrial centers. Currently the air is drier and dirtier than before, if this is allowed to continue it will have a negative impact on living things. Therefore, research is needed on the classification of DKI Jakarta's air quality which is expected to help the DKI Jakarta Environment Agency to provide information to the public, so that people can prevent the adverse effects of air pollution when outdoors. Classification is a process to determine the level of air quality, classification testing in this study uses two different methods, namely Multinomial Logistic Regression and K-Nearest Neighbor. Researchers compared the two methods based on the level of classification accuracy, namely the accuracy, precision, recall, and f1-score values. The level of classification accuracy produced by the Multinomial Logistic Regression method is 82.45%, 60.56%, 60.47%, and 60.51%, respectively. The level of classification accuracy produced by the K-Nearest Neighbor method is 93.87%, 92.33%, 92.94%, and 92.63%, respectively. The results of this study indicate that the K-Nearest Neighbor method has better classification accuracy results compared to the Multinomial Logistic Regression method. Keywords: Air Quality, Multinomial Logistic Regression, K-Nearest Neighbor

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Air Quality, Multinomial Logistic Regression, K-Nearest Neighbor
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.B45 Big data. Machine learning. Quantitative research. Metaheuristics.
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Riski Wulandari Futri
Date Deposited:	03 Jun 2024 04:05
Last Modified:	03 Jun 2024 04:05
URI:	http://repository.unsri.ac.id/id/eprint/146149

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