Sobarman, Fahmi Adnizar (2022) Analisis Prakiraan Wilayah Rawan Banjir Menggunakan Sistem Impact Based Forecast (Ibf) Dan Metode Composite Mapping Analysis (CMA) Dengan Memanfaatkan Pemodelan Data Weather Research And Forecasting (WRF) Di Provinsi Jawa Timur. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Banjir sudah menjadi bencana yang sering dijumpai di Indonesia. Sepanjang tahun 2021, Provinsi Jawa Timur mengalami 105 kasus bencana banjir atau 15% dari kejadian nasional. Sebanyak 36 Kota/Kabupaten yang berada di Jawa Timur mendapatkan kelas risiko tinggi bahkan 18 diantaranya memperoleh skor 36,00 atau tertinggi se-Indonesia. Untuk mengurangi dampak dari bencana banjir adalah dengan menganalisis prakiraan wilayah rawan banjir berbasis dampak. Pada penelitian ini digunakan metode pembobotan Composite Mapping Analysis pada setiap parameter penyebab banjir yaitu curah hujan harian, tutupan lahan, kemiringan lereng, elevasi, kerapatan aliran, dan jenis tanah. Kemudian parameter sistem Impact Based Forecast berupa rawan banjir metode CMA, prakiraan cuaca harian, dan curah hujan model WRF. Didapatkan nilai bobot parameter yaitu: curah hujan harian 17,982, jenis tanah 17,633, tutupan lahan 16,278, elevasi 16,159, kemiringan lereng sebesar 15,990, dan kerapatan aliran 15,958. Selain itu diperoleh bobot prakiraan cuaca harian 33,891, peta rawan banjir 33,310, serta curah hujan model WRF 32,800. Penelitian ini juga didapatkan bahwa Provinsi Jawa Timur memiliki kelas prakiraan wilayah rawan banjir dengan sistem IBF cenderung memiliki matriks urgensi risiko aman dengan luas 3387131,237 Ha (70,6%), disusul dengan risiko waspada dengan luas 1408079,800 Ha (29,4%), dan risiko siaga dengan luas 520,948 Ha (0,0%), sedangkan matriks urgensi risiko awas merah tidak memiliki luasan atau bernilai 0 Ha.
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Floods have become a frequent disaster in Indonesia. Throughout 2021, East Java Province experienced 105 cases of flood disasters or 15% of national events. Thirty-six cities/regencies in East Java received a high-risk class. Even 18 of them scored 36.00, or the highest in Indonesia. One way to reduce the impact of flood disasters is to analyze impact-based forecasts of flood-prone areas. This study used the Composite Mapping Analysis weighting method for each parameter causing daily flooding, land cover, slope, elevation, river flow density, and soil type. Then the parameters of the Impact-Based Forecasting system are flood hazards using the CMA method, daily weather forecasts, and WRF rainfall models. The weight parameter values obtained are: daily rainfall 17,982, soil type 17,633, land cover 16,278, elevation 16,159, slope 15,990, and river flow density 15,958. In addition, the daily weather forecast weights are 33,891, flood-prone maps are 33,310, and the WRF rainfall model is 32,800. This study also found that East Java Province has a flood-prone area forecast class with the IBF system tends to have a safe risk urgency matrix with an area of 3387131,237 Ha (70,6%), discussion with alert risk with an area of 1408079,800 Ha (29,4%), and alert risk with an area of 520.948 Ha (0,0%), while the risk urgency matrix for caution does not have an area or value of 0 Ha.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSG 526.028 5 Sob a-1 2022 |
| Uncontrolled Keywords: | Banjir, Composite Mapping Analysis, Impact Based Forecast, Weather Research and Forecasting. Flood, Composite Mapping Analysis, Impact Based Forecast, Weather Research and Forecasting. |
| Divisions: | Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Marsudiyana - |
| Date Deposited: | 20 May 2026 07:50 |
| Last Modified: | 20 May 2026 07:50 |
| URI: | http://repository.its.ac.id/id/eprint/133285 |
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