Comparison of prediction methods for air pollution data in Malaysia and Singapore

The process for analyzing and extracting useful information from a large database that employs one or more machine learning techniques is Data Mining. There are many data mining methods that can be used in a variety of data patterns. One of them is prediction modeling. This study compares several da...

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Main Authors: Sulaiman, Sarina, Shamsuddin, Siti Mariyam, Wibowo, Merlinda
Format: Article
Published: International Journal of Innovative Computing 2018
Online Access:http://eprints.utm.my/id/eprint/82143/
http://ijic.utm.my/
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spelling my.utm.821432019-11-05T06:53:25Z http://eprints.utm.my/id/eprint/82143/ Comparison of prediction methods for air pollution data in Malaysia and Singapore Sulaiman, Sarina Shamsuddin, Siti Mariyam Wibowo, Merlinda The process for analyzing and extracting useful information from a large database that employs one or more machine learning techniques is Data Mining. There are many data mining methods that can be used in a variety of data patterns. One of them is prediction modeling. This study compares several data mining performance methods for prediction such as Naïve Bayes, Random Tree, J48, and Rough Set to get the most powerful classifier to extract the knowledge of air pollution data. The parameters being used for observation in the performance of the prediction methods are correctly and incorrectly classified instances, the time taken, and kappa statistic. The experimental result reveals that Rough Set is extremely good for classifying the Air Pollutant Index (API) data from Malaysia and Singapore. Rough Set has the lowest error and the highest performance compared to other methods with the accuracy more than 97%. International Journal of Innovative Computing 2018 Article PeerReviewed Sulaiman, Sarina and Shamsuddin, Siti Mariyam and Wibowo, Merlinda (2018) Comparison of prediction methods for air pollution data in Malaysia and Singapore. International Journal of Innovative Computing, 8 (3). pp. 65-71. ISSN 2180-4370 http://ijic.utm.my/
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
description The process for analyzing and extracting useful information from a large database that employs one or more machine learning techniques is Data Mining. There are many data mining methods that can be used in a variety of data patterns. One of them is prediction modeling. This study compares several data mining performance methods for prediction such as Naïve Bayes, Random Tree, J48, and Rough Set to get the most powerful classifier to extract the knowledge of air pollution data. The parameters being used for observation in the performance of the prediction methods are correctly and incorrectly classified instances, the time taken, and kappa statistic. The experimental result reveals that Rough Set is extremely good for classifying the Air Pollutant Index (API) data from Malaysia and Singapore. Rough Set has the lowest error and the highest performance compared to other methods with the accuracy more than 97%.
format Article
author Sulaiman, Sarina
Shamsuddin, Siti Mariyam
Wibowo, Merlinda
spellingShingle Sulaiman, Sarina
Shamsuddin, Siti Mariyam
Wibowo, Merlinda
Comparison of prediction methods for air pollution data in Malaysia and Singapore
author_facet Sulaiman, Sarina
Shamsuddin, Siti Mariyam
Wibowo, Merlinda
author_sort Sulaiman, Sarina
title Comparison of prediction methods for air pollution data in Malaysia and Singapore
title_short Comparison of prediction methods for air pollution data in Malaysia and Singapore
title_full Comparison of prediction methods for air pollution data in Malaysia and Singapore
title_fullStr Comparison of prediction methods for air pollution data in Malaysia and Singapore
title_full_unstemmed Comparison of prediction methods for air pollution data in Malaysia and Singapore
title_sort comparison of prediction methods for air pollution data in malaysia and singapore
publisher International Journal of Innovative Computing
publishDate 2018
url http://eprints.utm.my/id/eprint/82143/
http://ijic.utm.my/
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score 13.209306