Skripsi

IMPLEMENTASI METODE ENSEMBLE UNTUK MENGKLASIFIKASI KUALITAS UDARA PADA MODEL NEURAL NETWORK, K-NEAREST NEIGHBOR DAN FUZZY DECISION TREE DENGAN ALGORITMA ID3

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Penilaian

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Air quality is a form of suitability or level of good or bad levels or certain levels based on the quality in the air itself whose use is done wisely for the sake of future life. Efforts to maintain and improve air quality include pollution control, the use of cleaner and environmentally friendly energy, and the reduction of greenhouse gas emissions. Therefore this study is predicting air quality using the Ensemble method with three classification models. The use of the Ensemble method aims to increase the level of accuracy of better classification. This classification uses the Ensemble Majority Vote method with three algorithm models, namely Neural Network, K-Nearest Neighbor and Fuzzy Decision Tree. The results of this study showed that the level of accuracy using the ensemble method with Majority Vote obtained an accuracy value of 97.46%, precision of 75.85%, recall of 73.18% and f1-score of 74.49%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307004875	T125446	T1254462023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T1254462023

Publisher

Indralaya : Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Sriwijaya., 2023

Collation

xvi, 75 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

519.507

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Matematika
Matematika Statistikal

Specific Detail Info

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Statement of Responsibility

PITRIA

Other version/related

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