Suharyatun, Siti and Rahmawati, Winda and Sugianti, Cicih (2019) Jaringan Syaraf Tiruan untuk Pendugaan Porositas Tanah. In: Seminar Nasional Sub Lahan Optimal 2019, 4-5 September 2019, Palembang.
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Abstract
Texture is one of the physical properties of soil that is permanent and related to the other physical properties of soil. Its properties is included the ability to absorb the water which expressed by porosity. This study aims to develop an artificial neural network (ANN) model to estimate soil porosity based on soil texture. The research was conducted in several stages, namely: (1) measuring the physical properties of soil consisting of texture, moisture content, volume density, and particle density (2) calculating soil porosity, (3) Developing ANN models are correlated on textures and soil porosity. ANN models are made using 3 input layer neurons, 5 hidden layer 1 neurons, 5 hidden layer 2 neurons and 1 input layer neurom. The ANN model uses the logig-tansig-purelin activation function with a RMSE (Root Mean Square Error) value of 2.0242. Determination of the training model (R2) was 0.957. The results of testing the validity of the models produce the same determination value R2 = 0.957.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | S Agriculture > S Agriculture (General) |
| Divisions: | Fakultas Pertanian (FP) > Prodi Teknik Pertanian |
| Depositing User: | SITI SUHAR |
| Date Deposited: | 18 May 2020 02:27 |
| Last Modified: | 18 May 2020 02:27 |
| URI: | http://repository.lppm.unila.ac.id/id/eprint/16671 |
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