Implementasi Jaringan Syaraf Tiruan Untuk Memprediksi Curah Hujan Dengan Backpropagation (Studi Kasus : Stasiun Klimatologi Banten)

Rizki Maulana, . (2024) Implementasi Jaringan Syaraf Tiruan Untuk Memprediksi Curah Hujan Dengan Backpropagation (Studi Kasus : Stasiun Klimatologi Banten). Other thesis, Universitas Pamulang.

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Abstract

Rainfall is an important factor in human life and ecosystems, because rainfall that is too high or too low can occur cause natural disasters and affect agricultural output and life humans in general. Rainfall estimates are still difficult due to the existing weather system complex and depends on many interacting factors. Factors that influence rainfall are air temperature, air humidity and wind velocity. In this research the author uses Artificial Neural Networks (ANN) Backpropagation to predict rainfall, This research uses 11 architectural models, namely 12-10-1, 12-11-1, 12-12-1, 12-13-1, 12-14-1, 12-15-1, 12-50-1, 12 -100-1, 12-150-1, 12-200-1, and 12-220-1. Of the eleven architectural models used, one best architectural model was obtained, namely 12-220-1 with an accuracy level of 66% epoch 228 iterations, training MSE of 0.000098442 and testing MSE of 0.13068..

Item Type: Thesis (Other)
Uncontrolled Keywords: Artificial Neural Networks, Backpropagation, Prediction, Rainfall
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Sri Lestari
Date Deposited: 06 Jun 2024 04:43
Last Modified: 06 Jun 2024 04:43
URI: http://repository.unpam.ac.id/id/eprint/12841

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