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<title><![CDATA[KAJIAN WILAYAH RAWAN LONGSOR DENGAN MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE PADA PLATFORM GOOGLE EARTH ENGINE (STUDI KASUS :]]></title>
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<note>Identifikasi wilayah longsor merupakan langkah penting dalam upaya mitigasi bencana, khususnya di Kabupaten Subang yang memiliki potensi tinggi terhadap bencana longsor. Penelitian ini bertujuan mengidentifikasi wilayah berpotensi longsor dengan menggunakan algoritma Support Vector Machine (SVM) pada platform Google Earth Engine (GEE). Data yang digunakan meliputi curah hujan, jenis batuan, kemiringan lereng, dan riwayat longsor tahun 2022. Proses validasi dilakukan menggunakan 95 titik longsor tervalidasi dan 143 titik non-longsor, dengan akurasi model mencapai 89.8%. Evaluasi model menunjukkan precision sebesar 86.96%, recall 83.33%, F1-score 85.11%, dan Kappa Statistic 77.7%, mengindikasikan kinerja model yang baik sesuai standar acuan. Hasil analisis mengidentifikasi bahwa wilayah dengan curah hujan tinggi, lereng curam, dan jenis batuan yang mudah lapuk memiliki potensi longsor yang signifikan. Visualisasi hasil penelitian dilakukan menggunakan QGIS Desktop versi 3.24.3, menghasilkan peta identifikasi longsor yang dapat mendukung perencanaan mitigasi bencana. Penelitian ini diharapkan dapat menjadi acuan dalam pengembangan analisis bencana berbasis teknologi GIS dan sistem peringatan dini longsor di masa depan.</note>
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