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ITS » Master Theses » Manajemen & Rekayasa Sumber Air S2
Posted by dee@its.ac.id at 22/11/2011 10:58:05  •  1776 Views


MODEL PREDIKSI OPERASIONAL PINTU AIR LENGKONG MENGGUNAKAN ARTIFICIAL NEURAL NETWORK

OPERATIONAL PREDICTION MODELS FOR LENGKONG WATER CONTROL GATE USING ARTIFICIAL NEURAL NETWORK

Author :
SAVITRI, YANG RATRI  ( 3107205703 )




ABSTRAK

Sungai Brantas sangat berpotensi banjir dan sering menimbulkan kerugian akibat curah hujan yang tinggi. Hal ini disebabkan karena sepanjang sungai ini sudah banyak sekali dimanfaatkan sebagai pemukiman yang padat. Pengoperasian pintu yang baik mampu mengurangi dampak kerusakan bencana banjir besar. Dalam thesis ini ANN artificial neural network digunakan untuk meramalkan bukaan pintu air Lengkong dengan memanfaatkan data di daerah hulu. Model prediksi untuk operasional pintu dilakukan dengan mengumpulkan data sekunder yang dibutuhkan yaitu data debit pada stasiun Ploso data elevasi muka air Mlirip data debit pada saluran irigasi delta Brantas serta laporan operasional pintu air Lengkong. Data tersebut digunakan sebagai data input untuk model. Selanjutnya dibuat dua model untuk kemudian dibandingkan. Model yang pertama memiliki output berupa debit outflow dan jumlah pintu air yang dioperasikan model yang kedua memiliki output berupa tinggi bukaan pintu air. Model tersebut dibangun dengan menggunakan arsitektur jaringan multilayer perceptron dengan menerapkan fungsi aktivasi sigmoid pada lapisan tersembunyi dan lapisan output. Proses running pembelajaran training validasi maupun verifikasi diselesaikan dengan menggunakan program neural machine. Dari dua model di atas model yang memberikan hasil terbaik adalah model peramalan outflow dan jumlah pintu dengan 25 unit node pada hidden layer.


ABSTRACT

Brantas River had a potential flooding and often cause a losses due to high rainfall. This because along the river sides is used as a settlement of a dense population. A good operation of the gate are able to reduce the impact of a huge flood damage. In this study ANN artificial neural network is used to predict the opening of sluice gates Lengkong by utilizing the data from the upstream. Model predictions for operational sluice gate used by collecting needed secondary information such as discharge data from ploso station Mlirip water surface elevation data discharge data in the Brantas delta irrigation channel and sluice gates Lengkong operational reports. The data are used as input data for models. Furthermore created two models and then will be comparated. The first model has an output of the total outflow discharge and numbered of operated sluice gate the second model has the output of a high aperture sluice gate level. The model is built using a multilayer perceptron network architecture by applying the sigmoid activation function in hidden layer and output layer. Running process of learning training validation and verification program is solved using neural machine. From the two models above the model gives the best results are forecasting model outflow and the number of doors with 25 units in the hidden layer nodes.



KeywordsPintu air Lengkong; Dam Lengkong; Artificial Neural network; ANN
 
Subject:  Jaringan komputer
Contributor
  1. Ir. Bambang Sarwono, M.Sc
  2. Dr.techn.Pujo Aji, ST.MT
Date Create: 04/02/2011
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Master-3100011043660
Collection ID: 3100011043660
Call Number: RTS 006.3 Sav m


Source
Master Thesis of Civil Engineering, RTS 006.3 Sav m, 2011

Coverage
ITS Community

Rights
Copyright @2011 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




[ Download - Open Access ]

  1.  ITS-Master-16185-3107205703-Abstract_id.pdf - 221 KB
  2.  ITS-Master-16185-3107205703-Abstract_en.pdf - 220 KB
  3.  ITS-Master-16185-3107205703-Conclusion.pdf - 166 KB




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