Saputra, Adi and Sulistiyanti, Sri Ratna and Marjunus, Roniyus and yulianti, yanti and Junaidi, Junaidi and Surtono, Arif (2022) Penerapan Jaringan Saraf Tiruan / JST (Backpropagation) untuk Prakiraan Cuaca di Bandar Udara Radin Inten II Lampung. Jurnal Teori dan Aplikasi Fisika. ISSN 2303-016X
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Abstract
Weather predictions are needed in everyday life planning, one of which is to make decisions. Artificial Neural Network (ANN) is an algorithm that is generally very good at pattern recognition problems. The maximum parameters in the development of weather forecasting information design based on Artificial Neural Networks / ANN (Backpropagation) by adding input data are rainfall, temperature, humidity, solar radiation, air pressure, wind direction and wind speed. This research was conducted in the area of Lampung's Radin Inten II Airport. The data used in this study is in the form of daily data on meteorological conditions in the Radin Inten II Lampung Airport area from the Radin Inten II Meteorological Station for the last 3 years, from 2017 to 2019. This data is needed as input data for the algorithm to be used in study. Based on the results of the study, the best training accuracy was 100% in the neural network architecture with the levenbergmarquardt (trainlm) and scaled conjugate gradient (trainscg) training function parameters, binary sigmoid and bipolar sigmoid activation functions, and the number of neurons 20, 40, 60, 80, and 100. While the best test accuracy is 74,359% on neural network architecture with training function parameters gradient descent wit momentum and adaptive learning rate (traingdx) and binary sigmoid activation function (logsig) and the number of neurons 20 and 80. Keywords: Application of Artificial Neural Networks, Weather Forecast, Radin Inten II Airport Lampung
Item Type: | Article |
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Subjects: | Q Science > Q Science (General) |
Divisions: | Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Fisika |
Depositing User: | Dr. Sri Ratna Sulistiyanti |
Date Deposited: | 12 Jul 2023 05:11 |
Last Modified: | 12 Jul 2023 05:11 |
URI: | http://repository.lppm.unila.ac.id/id/eprint/52237 |
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