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Analisis Pola Konvergensi Transpor Kelembapan Udara di Indonesia Bagian Barat Menggunakan K-Means dengan Pembobotan Statistik dan Hierarchical Shape-Based Clustering

KUBIK: Jurnal Publikasi Ilmiah Matematika · Vol. 9 No. 2 (2024) · hlm. 208–220

DOI
10.15575/kubik.v9i2.39753
ISSN
2686-0341, 2338-0896
Terbit
2024-11-28
Penerbit
Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung
Bahasa
ind

Abstrak

This study analyzes the convergence patterns of Vertically Integrated Moisture Transport (VIMT) in the western region of Indonesia using the K-Means method with statistical weighting and Hierarchical Shape-Based Clustering based on Dynamic Time Warping (DTW). Daily data on specific humidity, zonal wind speed, and meridional wind speed from 2020–2023 were used to calculate VIMT. Clustering methods were utilized to identify grouping patterns in moisture transport data. The results showed that moisture convergence significantly increased during the rainy season (November–February). Using the K-Means method, five clusters with clearer separations were obtained compared to the four clusters produced by the Hierarchical Clustering method. Performance evaluation using Silhouette and Calinski-Harabasz scores indicated that the K-Means method was superior, with scores of 0.37 and 104.88 compared to 0.13 and 96.34 for the Hierarchical method. This provides an understanding of the moisture transport patterns, serving as a reference for predicting weather and climate patterns, thereby supporting efforts to mitigate the impacts of extreme weather in Western Indonesia.

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Hari WijayantoAfiliasi tidak diketahui2
Devi Permata SariAfiliasi tidak diketahui2
Tasya Anisah RizqiAfiliasi tidak diketahui2
Erfiani M.SAfiliasi tidak diketahui2
Nafisa Berliana Indah PratiwiAfiliasi tidak diketahui1
IndahwatiAfiliasi tidak diketahui1
Agus Mohamad SolehAfiliasi tidak diketahui1
Anisa NurizkiAfiliasi tidak diketahui1
Mohamad Solehudin ZaenalAfiliasi tidak diketahui1
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Dhita Elsha PangestikaAfiliasi tidak diketahui1
I Made SumertajayaAfiliasi tidak diketahui1
Erdanisa Aghnia IlmaniAfiliasi tidak diketahui1
Ahmad SyauqiAfiliasi tidak diketahui1
Munawar MunawarAfiliasi tidak diketahui1
Giarno GiarnoAfiliasi tidak diketahui1
Ervan FerdiansyahAfiliasi tidak diketahui1
Fendy ArifiantoAfiliasi tidak diketahui1
Silvia YuliantiAfiliasi tidak diketahui1
Yenni AngrainiIPB University1
Muhammad Rizky NurhambaliAfiliasi tidak diketahui1
Siau Man MahAfiliasi tidak diketahui1
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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.uinsgd.ac.id/index.php/kubik/oai, pertama di-harvest 7 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="id-ID">Analisis Pola Konvergensi Transpor Kelembapan Udara  di Indonesia Bagian Barat Menggunakan  K-Means dengan Pembobotan Statistik dan  Hierarchical Shape-Based Clustering</dc:title>
	<dc:creator>Pratiwi, Asri</dc:creator>
	<dc:creator>Azis, Tukhfatur Rizmah</dc:creator>
	<dc:creator>Fitrianto, Anwar</dc:creator>
	<dc:creator>Erfiani, Erfiani</dc:creator>
	<dc:creator>Jumansyah, L.M. Risman Dwi</dc:creator>
	<dc:subject xml:lang="id-ID">Convergence</dc:subject>
	<dc:subject xml:lang="id-ID">DTW</dc:subject>
	<dc:subject xml:lang="id-ID">hierarchical clustering</dc:subject>
	<dc:subject xml:lang="id-ID">k-means</dc:subject>
	<dc:subject xml:lang="id-ID">moisture</dc:subject>
	<dc:subject xml:lang="id-ID">VIMT</dc:subject>
	<dc:description xml:lang="id-ID">This study analyzes the convergence patterns of Vertically Integrated Moisture Transport (VIMT) in the western region of Indonesia using the K-Means method with statistical weighting and Hierarchical Shape-Based Clustering based on Dynamic Time Warping (DTW). Daily data on specific humidity, zonal wind speed, and meridional wind speed from 2020–2023 were used to calculate VIMT. Clustering methods were utilized to identify grouping patterns in moisture transport data. The results showed that moisture convergence significantly increased during the rainy season (November–February). Using the K-Means method, five clusters with clearer separations were obtained compared to the four clusters produced by the Hierarchical Clustering method. Performance evaluation using Silhouette and Calinski-Harabasz scores indicated that the K-Means method was superior, with scores of 0.37 and 104.88 compared to 0.13 and 96.34 for the Hierarchical method. This provides an understanding of the moisture transport patterns, serving as a reference for predicting weather and climate patterns, thereby supporting efforts to mitigate the impacts of extreme weather in Western Indonesia.</dc:description>
	<dc:publisher xml:lang="en-US">Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung</dc:publisher>
	<dc:date>2024-11-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.uinsgd.ac.id/index.php/kubik/article/view/39753</dc:identifier>
	<dc:identifier>10.15575/kubik.v9i2.39753</dc:identifier>
	<dc:source xml:lang="en-US">KUBIK: Jurnal Publikasi Ilmiah Matematika; Vol. 9 No. 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika; 208-220</dc:source>
	<dc:source xml:lang="id-ID">KUBIK; Vol 9 No 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika; 208-220</dc:source>
	<dc:source>2686-0341</dc:source>
	<dc:source>2338-0896</dc:source>
	<dc:source>10.15575/kubik.v9i2</dc:source>
	<dc:language>ind</dc:language>
	<dc:relation>https://journal.uinsgd.ac.id/index.php/kubik/article/view/39753/11918</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Asri Pratiwi</dc:rights>
</oai_dc:dc>