Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia

The air pollution index (API) has been recognized as one of the important air quality indicators used to record the correlation between air pollution and human health. The API information can help government agencies, policy makers and individuals to prepare precautionary measures in order to elimin...

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Main Authors:	Nur Haizum Abd Rahman, Muhammad Hisyam Lee, Suhartono, Mohd Talib Latif
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2016
Online Access:	http://journalarticle.ukm.my/10380/ http://journalarticle.ukm.my/10380/ http://journalarticle.ukm.my/10380/1/06%20Nur%20Haizum.pdf

id	ukm-10380
recordtype	eprints
spelling	ukm-103802017-05-22T00:03:52Z http://journalarticle.ukm.my/10380/ Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia Nur Haizum Abd Rahman, Muhammad Hisyam Lee, Suhartono, Mohd Talib Latif, The air pollution index (API) has been recognized as one of the important air quality indicators used to record the correlation between air pollution and human health. The API information can help government agencies, policy makers and individuals to prepare precautionary measures in order to eliminate the impact of air pollution episodes. This study aimed to verify the monthly API trends at three different stations in Malaysia; industrial, residential and sub-urban areas. The data collected between the year 2000 and 2009 was analyzed based on time series forecasting. Both classical and modern methods namely seasonal autoregressive integrated moving average (SARIMA) and fuzzy time series (FTS) were employed. The model developed was scrutinized by means of statistical performance of root mean square error (RMSE). The results showed a good performance of SARIMA in two urban stations with 16% and 19.6% which was more satisfactory compared to FTS; however, FTS performed better in suburban station with 25.9% which was more pleasing compared to SARIMA methods. This result proved that classical method is compatible with the advanced forecasting techniques in providing better forecasting accuracy. Both classical and modern methods have the ability to investigate and forecast the API trends in which can be considered as an effective decision-making process in air quality policy. Penerbit Universiti Kebangsaan Malaysia 2016-11 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/10380/1/06%20Nur%20Haizum.pdf Nur Haizum Abd Rahman, and Muhammad Hisyam Lee, and Suhartono, and Mohd Talib Latif, (2016) Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia. Sains Malaysiana, 45 (11). pp. 1625-1633. ISSN 0126-6039 http://www.ukm.my/jsm/malay_journals/jilid45bil11_2016/KandunganJilid45Bil11_2016.htm
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	The air pollution index (API) has been recognized as one of the important air quality indicators used to record the correlation between air pollution and human health. The API information can help government agencies, policy makers and individuals to prepare precautionary measures in order to eliminate the impact of air pollution episodes. This study aimed to verify the monthly API trends at three different stations in Malaysia; industrial, residential and sub-urban areas. The data collected between the year 2000 and 2009 was analyzed based on time series forecasting. Both classical and modern methods namely seasonal autoregressive integrated moving average (SARIMA) and fuzzy time series (FTS) were employed. The model developed was scrutinized by means of statistical performance of root mean square error (RMSE). The results showed a good performance of SARIMA in two urban stations with 16% and 19.6% which was more satisfactory compared to FTS; however, FTS performed better in suburban station with 25.9% which was more pleasing compared to SARIMA methods. This result proved that classical method is compatible with the advanced forecasting techniques in providing better forecasting accuracy. Both classical and modern methods have the ability to investigate and forecast the API trends in which can be considered as an effective decision-making process in air quality policy.
format	Article
author	Nur Haizum Abd Rahman, Muhammad Hisyam Lee, Suhartono, Mohd Talib Latif,
spellingShingle	Nur Haizum Abd Rahman, Muhammad Hisyam Lee, Suhartono, Mohd Talib Latif, Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia
author_facet	Nur Haizum Abd Rahman, Muhammad Hisyam Lee, Suhartono, Mohd Talib Latif,
author_sort	Nur Haizum Abd Rahman,
title	Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia
title_short	Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia
title_full	Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia
title_fullStr	Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia
title_full_unstemmed	Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia
title_sort	evaluation performance of time series approach for forecasting air pollution index in johor, malaysia
publisher	Penerbit Universiti Kebangsaan Malaysia
publishDate	2016
url	http://journalarticle.ukm.my/10380/ http://journalarticle.ukm.my/10380/ http://journalarticle.ukm.my/10380/1/06%20Nur%20Haizum.pdf
first_indexed	2023-09-18T19:57:16Z
last_indexed	2023-09-18T19:57:16Z
_version_	1777406612773797888

Evaluation performance of time series approach for forecasting air pollution index in Johor, Malaysia

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