PREDIKSI CURAH HUJAN MENGGUNAKAN JARINGAN SARAF TIRUAN BACKPROPAGATION
| Main Author: | Muttaqin, Mishbahul |
|---|---|
| Format: | Thesis NonPeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
http://eprints.umm.ac.id/39602/1/PENDAHULUAN.pdf http://eprints.umm.ac.id/39602/2/BAB%20I.pdf http://eprints.umm.ac.id/39602/3/BAB%20II.pdf http://eprints.umm.ac.id/39602/4/BAB%20III.pdf http://eprints.umm.ac.id/39602/5/BAB%20IV.pdf http://eprints.umm.ac.id/39602/6/BAB%20V.pdf http://eprints.umm.ac.id/39602/ |
Daftar Isi:
- Rainfall has immense impacts in many aspects of life, for examples in agricultural, health, and transportation. By using rainfall forecasting we can anticipate many unwanted things to happen because of rainfall especially rainfall at extreme rate. The existence of the artificial neural network could really help us in creating rainfall forecasting program, primarily using backpropagation algorithm which will give us more precise results. And with the existence of Matlab programming, which provides us more features and is easier to use. The data which used in this research was taken from BMKG (Badan Meteorologi Klimatologi dan Geofisika) Station Karangploso, Malang. The variables are average temperature, average relative humidity, average wind speed, and average rainfall. The result from the tests are with more neurons in hidden layer the better/smaller MSE will be. While in some learning rate tests, we get 0,1 learning rate as the smallest MSE.