Abstract
Weather information has an important role in human life in various fields, such as agriculture, marine, and aviation. The accurate weather forecasts are needed in order to improve the performance of various fields. In this study, use artificial neural network method with backpropagation learning algorithm to create a model of weather forecasting in the area of ??South Bali. The aim of this study is to determine the effect of the number of neurons in the hidden layer and to determine the level of accuracy of the method of artificial neural network with backpropagation learning algorithm in weather forecast models. Weather forecast models in this study use input of the factors that influence the weather, namely air temperature, dew point, wind speed, visibility, and barometric pressure.The results of testing the network with a different number of neurons in the hidden layer of artificial neural network method with backpropagation learning algorithms show that the increase in the number of neurons in the hidden layer is not directly proportional to the value of the accuracy of the weather forecasts, the increase in the number of neurons in the hidden layer does not necessarily increase or decrease value accuracy of weather forecasts we obtain the best accuracy rate of 51.6129% on a network model with three neurons in the hidden layer.
Highlights
Weather information has an important role in human life in various fields
The accurate weather forecasts are needed in order to improve the performance of various fields
use artificial neural network method with backpropagation learning algorithm to create a model of weather forecasting in the area
Summary
Cuaca mempunyai peranan penting bagi kehidupan manusia dalam menjalani aktivitas terutama aktivitas di tempat terbuka. Jaringan syaraf tiruan merupakan salah satu bagian dari metode kecerdasan buatan, dimana metode ini merepresentasikan cara kerja otak manusia untuk menyelesaikan suatu masalah klasifikasi (Hermawan, 2006). Salah satu algoritma dari jaringan syaraf tiruan yang dapat digunakan dalam menyelesaikan masalah klasifikasi adalah algoritma back-propagation. Pada penelitian ini digunakan metode jaringan syaraf tiruan dengan algoritma pembelajaran backpropagation untuk memprakirakan cuaca di daerah Bali Selatan dengan output 15 kejadian cuaca yaitu cerah, cerah berawan, cerah berawan dengan awan cumulonimbus (CB), berawan, berawan dengan awan cumulonimbus (CB), badai guntur, hujan ringan, hujan ringan dengan awan cumulonimbus (CB), hujan sedang, hujan sedang dengan awan cumulonimbus (CB), hujan lebat, hujan lebat dengan awan cumulonimbus (CB), hujan ringan dengan badai guntur, hujan sedang dengan badai guntur dan hujan lebat dengan badai guntur. Ini sangat berbahaya dalam suatu penerbangan, mengingat banyak kecelakaan pesawat yang diakibatkan oleh awan cumulonimbus (CB)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have