Air Quality Prediction Using the Support Vector Machine Algorithm

  • Liza Widyarini Universitas Kristen Satya Wacana, Indonesia
  • Hindriyanto Dwi Purnomo Universitas Kristen Satya Wacana, Indonesia
DOI: 10.51519/journalisi.v6i2.705
Keywords: Air Quality, Prediction, SVM Algorithm, Air Pollution, Support Vector Machine.

Abstract

Air quality is an important factor in maintaining the health and well-being of humans and the environment. To anticipate and manage air pollution, air quality prediction has become an important research topic. In this research, researchers propose using the Support Vector Machine (SVM) algorithm to predict air quality. SVM has proven to be an effective method in classification and regression, especially in the context of complex and non-linear data such as air quality data. Researchers utilized historical air quality datasets that include various parameters such as particulates, ozone, nitrogen dioxide and carbon monoxide. Experiments were conducted to compare the performance of SVM with other prediction methods, and the results show that SVM provides accurate and reliable predictions in modeling air quality.

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Published
2024-06-13
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How to Cite
Widyarini, L., & Purnomo, H. (2024). Air Quality Prediction Using the Support Vector Machine Algorithm. Journal of Information Systems and Informatics, 6(2), 652-661. https://doi.org/10.51519/journalisi.v6i2.705
Issue
Vol 6 No 2 (2024): Journal of Information Systems and Informatics
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Articles

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