Estimasi Ketinggian,Debit dan Kecepatan Aliran Sungai pada Model Shallow Water dengan Menggunakan Extended Kalman Filter

Palupi, Retno Dewi (2017) Estimasi Ketinggian,Debit dan Kecepatan Aliran Sungai pada Model Shallow Water dengan Menggunakan Extended Kalman Filter. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Indonesia merupakan negara maritim yang luas wilayahnya sebagian besar adalah perairan dimana meliputi laut, danau, sungai. Sungai merupakan salah satu sumber air yang menampung dan mengalirkan aliran air. Salah satu sungai di pulau Jawa yaitu sungai Brantas. Sungai Brantas sangat berpotensi banjir. Banjir didefinisikan sebagai debit ekstrim sungai yang terjadi akibat peningkatan volume air. Sehingga untuk memperkirakan ketinggian dan debit aliran sungai, dilakukan estimasi ketinggian dan debit aliran air. Estimasi ketinggian dan debit aliran sungai dilakukan dengan menggunakan persamaan Saint Venant didimensi 1 dengan menggunakan Extended Kalman Filter. Hasil menunjukkan bahwa estimasi dengan menggunakan metode Extended Kalman Filter pada aliran sungai normal, aliran sungai berpotensi meluap, aliran sungai dangkal pada 3 titik daerah yaitu daerah Ploso, Lengkong Baru dan Porong memiliki nilai RMSE kurang dari 1. Sedangkan estimasi dengan memasukkan data didapatkan nilai persentase error yaitu sebesar 0,02129% hingga 5%. ==================================================================
Indonesia is a maritime country whose territory is largely waters such as sea, lake, river. River is one of water sources that holds and drain the flow of water. One of the rivers in Java is Brantas river. The Brantas river is potentially flooded. Floods are defined as extreme river discharges that occur due to an increase in water volume. To anticipate the coming of flood, the height and discharge of water flow are estimated in this final project . Estimation of altitude and discharge of river flow is done using the Saint Venant equation in dimension 1 using Extended Kalman Filter. The results show that the estimation using Extended Kalman Filter method has a good result. By entering the normal stream flow conditions, river flow is potentially overflow, river flow is low at 3 point area that are area of Ploso, Lengkong Baru and Porong have small RMSE values where RMSE is less than 1. While the estimation by inputing the measurement data obtained RMSE value is still quite large. While the estimation by inputing the measurement data obtained presentage error were 0,02129% hingga 5%.

Item Type: Thesis (Undergraduate)
Additional Information: RSMa 519.2 Pal a
Uncontrolled Keywords: Shallow Water, Kalman Filter, Extended Kalman Filter, Beda hingga, Finite Different
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA911 Fluid dynamics. Hydrodynamics
Divisions: Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User: Retno Dewi Palupi
Date Deposited: 09 Oct 2017 02:24
Last Modified: 08 Mar 2019 03:01
URI: http://repository.its.ac.id/id/eprint/46406

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