Slamet Suprayogi
Fakultas Geografi Universitas Gadjah Mada

Published : 29 Documents
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Journal : Jurnal Keteknikan Pertanian

Applicatin of Some Evapotranspiration Models at Tropical Region

Jurnal Keteknikan Pertanian Vol 17, No 2 (2003): Buletin Keteknikan Pertanian
Publisher : PERTETA

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Abstract

Potential evaporation (ETp) can be calculated by ETp models climatological parametrs. Among them, the Penman model is most frequently used for ETp estimation. The penman model requires five climatic parameters : temperature, relative humidity, wind, saturation vapor pressure, and net radiation. It also uses complicated unit conversions and lengthy calculation. There are a simple models such as : Jensen - Haise models, Hargreaves, Radiation, Turcs, and Makkinks model. These models that requires only two climatic parameters, temperature and incident radiation.

Aplikasi Model Artificial Neural Network Terintegrasi dengan Geographycal Information System untuk Evaluasi Kesesuaian Lahan Perkebunan Kakao

Jurnal Keteknikan Pertanian Vol 22, No 1 (2008): Jurnal Keteknikan Pertanian
Publisher : PERTETA

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Abstract

Land evaluation for specific purpose in plantation sector become very important due to increasing the competition in land use and the development of plantation sector. Land evaluation produces information of land economic values for specific land use. The objective of the research is to develop land evaluation method for cocoa estate using integrated model Artificial Neural Network (ANN) and Geographical Information System (GIS). Back propagation ANN model were used to predict cocoa yield base on land qualities parameter. The result shows that the best of ANN model to predict cocoa yield have 15 input layer, 15 hidden layer, and 1 output layer. with the determination coefficient (r2) of 0.99 and Root Mean Square Error (RMSE) of 93.83 in the training process, otherwise in the testing found the r2 of O. 76 and RMSE of 113.83. In verification stage the integrated model ofANN and GIS was used to evaluate land suitability of Wijayaarga Cocoa Plantation is seem accurate in predicting cocoa yield and easers to mapping the land suitability unit.  Keyword: ANN, GIS, Land Evaluation, Cocoa Diterima: 04 Juni 2007; Disetujui: 18 September 2007

Aplikasi Model Artificial Neural Network Terintegrasi dengan Geographycal Information System untuk Evaluasi Kesesuaian Lahan Perkebunan Kakao

Jurnal Keteknikan Pertanian Vol 22, No 1 (2008): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

Land evaluation for specific purpose in plantation sector become very important due to increasing the competition in land use and the development of plantation sector. Land evaluation produces information of land economic values for specific land use. The objective of the research is to develop land evaluation method for cocoa estate using integrated model Artificial Neural Network (ANN) and Geographical Information System (GIS). Back propagation ANN model were used to predict cocoa yield base on land qualities parameter. The result shows that the best of ANN model to predict cocoa yield have 15 input layer, 15 hidden layer, and 1 output layer. with the determination coefficient (r2) of 0.99 and Root Mean Square Error (RMSE) of 93.83 in the training process, otherwise in the testing found the r2 of O. 76 and RMSE of 113.83. In verification stage the integrated model ofANN and GIS was used to evaluate land suitability of Wijayaarga Cocoa Plantation is seem accurate in predicting cocoa yield and easers to mapping the land suitability unit.  Keyword: ANN, GIS, Land Evaluation, Cocoa Diterima: 04 Juni 2007; Disetujui: 18 September 2007

Applicatin of Some Evapotranspiration Models at Tropical Region

Jurnal Keteknikan Pertanian Vol 17, No 2 (2003): Buletin Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

Potential evaporation (ETp) can be calculated by ETp models climatological parametrs. Among them, the Penman model is most frequently used for ETp estimation. The penman model requires five climatic parameters : temperature, relative humidity, wind, saturation vapor pressure, and net radiation. It also uses complicated unit conversions and lengthy calculation. There are a simple models such as : Jensen - Haise models, Hargreaves, Radiation, Turcs, and Makkinks model. These models that requires only two climatic parameters, temperature and incident radiation.

Aplikasi Model Artificial Neural Network Terintegrasi dengan Geographycal Information System untuk Evaluasi Kesesuaian Lahan Perkebunan Kakao

Jurnal Keteknikan Pertanian Vol 22, No 1 (2008): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

Land evaluation for specific purpose in plantation sector become very important due to increasing the competition in land use and the development of plantation sector. Land evaluation produces information of land economic values for specific land use. The objective of the research is to develop land evaluation method for cocoa estate using integrated model Artificial Neural Network (ANN) and Geographical Information System (GIS). Back propagation ANN model were used to predict cocoa yield base on land qualities parameter. The result shows that the best of ANN model to predict cocoa yield have 15 input layer, 15 hidden layer, and 1 output layer. with the determination coefficient (r2) of 0.99 and Root Mean Square Error (RMSE) of 93.83 in the training process, otherwise in the testing found the r2of O. 76 and RMSE of 113.83. In verification stage the integrated model ofANN and GIS was used to evaluate land suitability of Wijayaarga Cocoa Plantation is seem accurate in predicting cocoa yield and easers to mapping the land suitability unit. Keyword: ANN, GIS, Land Evaluation, Cocoa Diterima: 04 Juni 2007; Disetujui: 18 September 2007