Sains Malaysiana 43(11)(2014):
1791–1800
Pengelasan Kabur dalam Perantauan Kecenderungan Kemarau di
Semenanjung Malaysia
(Fuzzy Clustering for Regionalization of Drought Proneness in
Peninsular Malaysia)
WAHIDAH SANUSI1*, ABDUL AZIZ JEMAIN2 & WAN ZAWIAH WAN ZIN2
1Jurusan Matematika,
Fakultas Matematika dan, Ilmu Pengetahuan Alam
Universitas
Negeri Makassar, 90224, Parangtambung Makassar, Sulawesi Selatan
Indonesia
2Pusat Pengajian Sains
Matematik, Fakulti Sains dan Teknologi, Universiti Kebangsaan Malaysia
43600
Bangi, Selangor, Malaysia
Diserahkan:
22 Mei 2013/Diterima: 2 April 2014
ABSTRAK
Dalam kajian ini, pendekatan pengelasan kabur Gustafson-Kessel (GK)
telah digunakan untuk mengelaskan 35 stesen hujan di Semenanjung Malaysia ke
dalam rantau homogen. Pertama, algoritma pengkelasan kabur GK digunakan
untuk mengenal pasti rantau awal. Kemudian, diuji
keserasian dan kehomogenan rantau berkenaan. Akhir
sekali, penyesuaian rantau dilakukan untuk mendapatkan rantau homogen. Hasil kajian mendapati 35 stesen hujan kajian boleh dibahagikan
kepada enam rantau yang homogen. Rantau 1 meliputi bahagian barat laut
dan utara Semenanjung Malaysia, rantau 2, 3 dan 4 meliputi bahagian barat,
rantau 5 meliputi bahagian barat daya dan rantau 6 meliputi bahagian timur. Hasil kajian ini juga memperlihatkan bahawa berdasarkan nilai
purata Indeks Kerpasan Piawai (SPI) skala masa satu bulan, rantau 2 lebih
sering mengalami keadaan kemarau melampau. Walau bagaimanapun,
berdasarkan SPI skala masa satu bulan, peristiwa kemarau terjadi secara rawak
dalam semua rantau yang dianalisis, bahkan semua rantau tersebut pernah
mengalami kejadian kemarau ekstrim dalam tempoh masa setahun. Hasil kajian ini turut menunjukkan bahawa pendekatan pengelasan
kabur Gustafson-Kessel boleh digunakan untuk membina rantau homogen.
Kata kunci: Indeks Kerpasan Piawai (SPI); pengkelasan kabur
Gustafson-Kessel; perantauan; ujian kehomogenan; ujian keserasian
ABSTRACT
In this study, the Gustafson-Kessel (GK) fuzzy clustering
method is used to classify the 35 rainfall stations in Peninsular Malaysia into
homogeneous regions. First, the GK fuzzy clustering algorithm is applied to
identify the initial region. The next step is to test the discordancy and
homogeneity of corresponding region. Finally, adjustment of region is done to
obtain the homogeneous region. The results showed that, for thirty five
rainfall stations studied, these stations could be grouped into six homogeneous
regions. The first region covers the northwestern and northern of Peninsular
Malaysia, region 2, 3 and 4 cover the western, region 5 covers the southwestern
and region 6 covers the eastern. The study also indicates that, based on the
average Standardized Precipitation Index (SPI) value for one-month
time scale, region 2 experiences more frequent extreme drought condition.
However, based on the SPI, drought events randomly occurred in all
regions, moreover these regions experience drought events within a year. The
results also showed that GK fuzzy clustering method could be applied to
construct a homogeneous region
.
Keywords: Discordancy test; Gustafson-Kessel
fuzzy clustering; homogeneity test; regionalization; Standardized Precipitation
Index (SPI)
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*Pengarang
untuk surat-menyurat; email: w_sanusi@yahoo.com
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