Evaluasi Akurasi Geomorphic Flood Index (GFI) Untuk Penyesuaian Kelas Bahaya Menggunakan Data Penurunan Muka Tanah Berbasis PS-InSAR (Studi Kasus: Kota Jakarta Utara)

Malin, Ramadhan Aulia (2026) Evaluasi Akurasi Geomorphic Flood Index (GFI) Untuk Penyesuaian Kelas Bahaya Menggunakan Data Penurunan Muka Tanah Berbasis PS-InSAR (Studi Kasus: Kota Jakarta Utara). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Jakarta Utara merupakan wilayah pesisir yang menghadapi ancaman banjir yang terus diperparah oleh fenomena penurunan muka tanah. Pemetaan bahaya banjir umumnya menggunakan model Geomorphic Flood Index (GFI) dengan data elevasi statis seperti FABDEM, yang memiliki kelemahan karena mengabaikan dinamika topografi akibat subsiden. Penelitian ini bertujuan mengevaluasi akurasi GFI standar dan mengembangkan model penyesuaian kelas bahaya dengan mengintegrasikan data laju penurunan muka tanah dari pengolahan Persistent Scatterer Interferometry Synthetic Aperture Radar (PS-InSAR). Analisis PS-InSAR menggunakan 117 citra Sentinel-1A (2018–2021) yang tervalidasi oleh stasiun CORS menunjukkan laju subsiden tertinggi berada di Muara Baru, Kecamatan Penjaringan sebesar -25,8 mm/tahun. Laju deformasi vertikal ini dikonversi menjadi deformasi kumulatif untuk memodifikasi FABDEM guna menyimulasikan kondisi topografi proyeksi tahun 2024. Hasil perhitungan ulang indeks GFI menunjukkan peningkatan total area bahaya banjir sebesar 12,72% (penambahan seluas 5,69 km²) dibandingkan model standar (2011). Validasi model menggunakan data historis genangan BPBD DKI Jakarta dengan metode out-of-time validation menunjukkan bahwa penyesuaian subsiden pada model GFI 2024 berhasil meningkatkan akurasi total sebesar 2,62% dan sensitivitas sebesar 8,50%, yang mana berhasil mendeteksi 21 titik kejadian banjir tambahan yang sebelumnya tidak terdeteksi oleh model standar. Meskipun analisis Receiver Operating Characteristics (ROC) dan Area Under Curve (AUC) menunjukkan diskriminasi model berada pada kategori lemah (~0,61–0,62) akibat sifat GFI yang hanya mempertimbangkan faktor topografi, penelitian ini menegaskan bahwa integrasi data penurunan muka tanah sangat krusial dalam menghindari peremehan estimasi bahaya banjir di kawasan pesisir dengan geodinamika yang aktif.
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North Jakarta is a coastal region facing flood threats exacerbated by rapid land subsidence phenomenon. Flood hazard mapping often utilizes the Geomorphic Flood Index (GFI) model with static elevation data such as FABDEM, which has limitations as it ignores topographic dynamics caused by subsidence. This study aims to evaluate the accuracy of the standard GFI model and develop a hazard class adjustment model by integrating land subsidence rate data from Persistent Scatterer Interferometry Synthetic Aperture Radar (PS-InSAR) processing. PS-InSAR analysis using 117 Sentinel-1A images (2018–2021), validated against a CORS station, showed the highest subsidence rate in Muara Baru, Penjaringan at -25.8 mm/year. This vertical deformation rate was converted into cumulative deformation to modify the FABDEM to simulate the projected 2024 topographic conditions. Recalculation of the GFI index revealed a 12.72% increase in the total flood hazard area (an addition of 5.69 km²) compared to the standard model (2011). Model validation using historical BPBD DKI Jakarta flood data via out-of-time validation showed that the subsidence adjustment in the GFI 2024 model successfully increased overall accuracy by 2.62% and sensitivity significantly by 8.50%, successfully detecting 21 additional flood events previously undetected by the standard model. Although the Receiver Operating Characteristics (ROC) and Area Under Curve (AUC) analyses placed the model's discrimination in the poor category (~0.61–0.62) due to GFI's inherent reliance solely on topography, this research confirms that integrating land subsidence data is crucial to prevent the underestimation of flood hazard assessments in geodynamically active coastal regions.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Banjir, Geomorphic Flood Index, GFI, Deformasi, PS-InSAR, Jakarta Utara, Evaluasi Akurasi, Penurunan Muka Tanah, Flood, Geomorphic Flood Index, GFI, Deformation, PS-InSAR, North Jakarta, Accuracy Assessment, Land Subsidence
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Ramadhan Aulia Malin
Date Deposited:	22 Jul 2026 00:36
Last Modified:	22 Jul 2026 00:36
URI:	http://repository.its.ac.id/id/eprint/134968

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