PREDIKSI KUALITAS UDARA MENGGUNAKAN METODE ENSEMBLE PADA MODEL DECISION TREE lD.3, RANDOM FOREST DAN REGRESI LOGISTIK MULTINOMIAL

RAHMAYANI, MAU'IZATIL and Resti, Yulia and Eliyati, Ning (2018) PREDIKSI KUALITAS UDARA MENGGUNAKAN METODE ENSEMBLE PADA MODEL DECISION TREE lD.3, RANDOM FOREST DAN REGRESI LOGISTIK MULTINOMIAL. Undergraduate thesis, Sriwijaya Unoversity.

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Abstract

Air quality is one of the important components for living things on the earth's surface, especially for humans. Air quality must be maintained and maintained so as not to experience a decrease in quality caused by weather factors. Air quality is one of the causes of human health problems. Therefore, the purpose of this study is to predict air quality using the Ensemble method using three classification models. The use of the ensemble method aims to minimize errors in classification and get a better level of accuracy. The data used in this study has 21 variables with a total of 2502 data. The classification uses the Ensemble Majority vote method based on three algorithm models Decision Tree, Random For est and Multinomial Logistics Regression. The results of this study indicate that the level of accuracy of air quality prediction using the Ensemble Majority Vote method obtained an accuracy value of 99.31%, macro precision of 78.45%, and macro recall of 78.63%, macro fscore of 78.54%, for precision, recall and micro fscore have the same value, namely 98.28%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	kualitas udara, Ensemble Majority Vote, Decision Tree, Random Forest Regresi Logistik Multinomial
Subjects:	Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Mau’izatil Rahmayani
Date Deposited:	10 Aug 2022 03:41
Last Modified:	10 Aug 2022 03:41
URI:	http://repository.unsri.ac.id/id/eprint/76549

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