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All Journal ILMU KELAUTAN: Indonesian Journal of Marine Sciences Geo-Image Journal
Diza, Novia Fara
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Earth & Planetary Sciences

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Pemetaan dan Analisis Kerugian Daerah Terdampak Banjir Rob di Kecamatan Kraksaan, Probolinggo Semedi, Bambang; Rachmansyah, Arief; Marjono, Marjono; Yanuwiadi, Bagyo; Afandhi, Aminudin; Bayuaji, Gerardus David Ady Purnama; Syam's, Nova Dewi Safitri; Diza, Novia Fara; Safitri, Ni Luh Eka; Hikmawati, Viona Faiqoh
Geo-Image Journal Vol 12 No 2 (2023): Vol 12 No 2 (2023): Geo-Image : Spatial - Ecological - Regional
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/geoimage.v12i2.66807

Abstract

Pemukiman di wilayah pesisir Kecamatan Kraksaan, Probolinggo berbatasan langsung dengan Selat Madura dan berpotensi tinggi terdampak banjir rob karena pasang tinggi tertinggi menyebabkan sungai meluap. Penelitian ini bertujuan untuk: (1) mengetahui ketinggian genangan banjir rob dan luas area tergenang banjir rob, (2) mengetahui dampak genangan banjir rob terhadap keruskanan bangunan, (3) mengetahui estimasi kerugian bangunan akibat banjir rob. Pemetaan genangan banjir rob menggunakan metode Hloss memanfaatkan data DEM, data citra Sentinel-2A, dan data pasang surut. Perhitungan estimasi kerugian bangunan menggunakan metode Damage and Loss Assessment (DaLA). Hasil penelitian menunjukan bahwa tinggi genangan banjir rob tahun 2021 adalah 2.33 meter dengan kategori bahaya rendah seluas 17.55 ha, kategori bahaya sedang seluas 15,33 ha, kategori bahaya tinggi seluas 12.49 ha. Bangunan terdampak genangan banjir rob pada tahun 2021 kategori bahaya rendah sebanyak 794 unit, kategori bahaya sedang sebanyak 400 unit, kategori bahaya tinggi sebanyak 538 unit, dan total 1732 unit yang mengalami rusak ringan. Kerugian bangunan rumah permanen adalah Rp9,886,758,206, kerugian bangunan perdagangan dan jasa adalah Rp9,688,495,305, kerugian bangunan industri dan gudang Rp16,866,202,723, kerugian bangunan tempat ibadah adalah Rp121,355,451, dan kerugian bangunan kantor pemerintah adalah Rp227,541,470. Total kerugian bangunan terdampak genangan banjir rob di Kecamatan Kraksaan pada tahun 2021 adalah Rp36,790,353,155.
Habitat Suitability Modeling Based on Oceanographic Factors for Yellowfin Tuna (Thunnus albacares) Fishing Grounds in the Southern Waters of Java Semedi, Bambang; Diza, Novia Fara; Sari, Syarifah Hikmah Julinda; Wiadnya, Dewa Gede Raka; Lelono, Tri Djoko; Setyohadi, Daduk; Harlyan, Ledhyane Ika; Rahman, Muhammad Arif; Lee, Ming-An
ILMU KELAUTAN: Indonesian Journal of Marine Sciences Vol 30, No 2 (2025): Ilmu Kelautan
Publisher : Marine Science Department Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ik.ijms.30.2.163-173

Abstract

The southern waters of Java are suitable to be the largest supplier of Yellowfin tuna exports in Indonesia, but have not efficiently produced the expected yield. This research minimizes these constraints by modeling the yellowfin tuna fishing grounds in the southern waters of Java based on oceanographic factors such as Sea Surface Temperature (SST), chlorophyll-a (CHL_A), Sea Surface Salinity (SSS), Sea Surface Height (SSH) using an integration between remote sensing, Geographic Information Systems (GIS), and the Generalized Additive Model (GAM) statistical method. This study used oceanographic factor data from Aqua MODIS Level-3 and Copernicus, while yellowfin tuna fishery production was obtained from Palabuhanratu Nusantara Fishing Port (NFP), Cilacap Ocean Fishing Port (OFP), and Pondokdadap Coastal Fishing Port (CFP). The modeling process used 80% of the data, while the remaining 20% was used to validate the model results. The order of influence of oceanographic parameters from largest to smallest is SST > SSS > SSH > CHL-A. The best model from the GAM analysis showed that the combination of four oceanographic parameters had the greatest influence on yellowfin tuna CPUE. The catch per unit effort (CPUE) of yellowfin tuna was predicted to be high in May-October and low in November-April. The prediction model had high accuracy because most of the fishing activity was in the HSI 0.4-0.5 range and the RMSEP value was 0.63. Yellowfin tuna were suitable in habitats distributed from inshore to offshore in June and July, but less suitable in December.  
Co-Authors Aminudin Afandhi Arief Rachmansyah Bagyo Yanuwiadi Bambang Semedi Bayuaji, Gerardus David Ady Purnama Daduk Setyohadi Dewa Gede Raka Wiadnya Hikmawati, Viona Faiqoh Ledhyane Ika Harlyan Lee, Ming-An Marjono Marjono Rahman, Muhammad Arif Safitri, Ni Luh Eka Syam's, Nova Dewi Safitri Syarifah Hikmah Julinda Sari Tri Djoko Lelono