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    Penilaian Prestasi Pendekatan Siri Masa untuk Peramalan Indeks Pencemaran Udara di Johor, Malaysia
    (Penerbit UKM, 2016) 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).