Hermantoro .
Fakultas Teknologi Pertanian, Institut Pertanian Stiper

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Teknik Rekayasa Pemadatan Kayu II : Sifat Fisik dan Mekanik Kayu Agatis (Agathis lorantifolia Salisb.) Terpadatkan dalam Konstruksi Bangunan Kayu

Jurnal Keteknikan Pertanian Vol 17, No 1 (2003): Buletin Keteknikan Pertanian
Publisher : PERTETA

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Abstract

The successful application of pitcher irrigation system has motivated to investigate the pitcher as a fetigation system. The experiment was conducted at Leuwikopo Experiment Station, Agricultural Engineering Departemen, Bogor Agricultural University. The main objective of this study is to study the effectiveness of pitcher fertigation system on bushes pepper crops. The result shows that the pitcher wall is capable to release NPK solution. Diffusion rate of fertilizer solution was measured as affected by the concentration inside and outside of the pitcher. The soil moisture distribution in the soil is sufficient to transfor the solution available for crops development. Concentration of Phosphate (P) and Potassium (K) decrease laterally and the Nitrogen (N) tends to accumulate homogeneously in moist part around the pitcher.

Determination of Hydrodynamic Dispersion Coefficient of Solute Transfort in Soil Using Inverse Problem Method

Jurnal Keteknikan Pertanian Vol 16, No 1 (2002): Buletin Keteknikan Pertanian
Publisher : PERTETA

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Abstract

Solute transport in porous medium is affected by two parameters i.e : 1) average velocity of solute particle, and 2) solute dispersion. Theoretically, the solute transport can be describes by Convective Dispersion Equation, when the methods to determine D in this paper we present a modified method of inverse problem to calculate D. The results indicated that the inverse problem much or less matched with the analytical solution.

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 Pengolahan Citra Digital dan Jaringan Syaraf Tiruan Untuk Memprediksi Kadar Bahan Organik dalam Tanah

Jurnal Keteknikan Pertanian Vol 25, No 1 (2011): Jurnal Keteknikan Pertanian
Publisher : PERTETA

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Abstract

Abstract The objective of this research is to determine organic matter content in soil using image processing and artificial neural network. The images of soil were captured using digital camera and processed using image process algorithm. The images parameter data i.e. red, green, blue, hue, saturation, intensity, mean, entropy, energy, contrast, and homogeneity were extracted from sixty soil sample with different organic matter content. Parameter images data were used as the inputs data for ANN analysis. Output layer of ANN is organic matter content in soil. Based on experiment found that application of image processing and ANN for predicting organic matter content in soil have the high accuracy with coefficient determination of  90.75 % and mean square error (MSE) of 0.002762. Keywords : soil organic matter, images process, artificial neural network Abastrak Tujuan penelitian adalah menentukan kadar bahan organik dalam tanah menggunakan pengolahan citra digital dan jaringan syaraf tiruan. Citra tanah diambil menggunakan sebuah camera digital dan diolah menggunakan algoritma pengolahan citra. Parameter citra yang digunakan adalah : red, green, blue, saturasi, intensitas, rerata, entropi, energi, kontras, dan homogenitas diambil dari 60 contoh tanah dengan kadar bahan organik yang berbeda. Parameter citra tersebut digunakan sebagai data masukan dalam analisis ANN., sebagai lapisan keluaran dari ANN adalah kadar bahan organik dalam tanah. Berdasarkan hasil penelitian dan analisis pengolahan citra dan ANN dapat digunakan untuk emprediksi kadar bahan organik dalam tanah dengan akurasi tinggi dengan kooefisien determinasi 90,75% dan MSE 0,002761. Kata kunsi : bahan orgaik tanah, pengolahan citra, jaringan syaraf tiruan.Diterima: 12 Agustus 2010; Disetujui: 03 Januari 2011 

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 Pengolahan Citra Digital dan Jaringan Syaraf Tiruan Untuk Memprediksi Kadar Bahan Organik dalam Tanah

Jurnal Keteknikan Pertanian Vol 25, No 1 (2011): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

Abstract The objective of this research is to determine organic matter content in soil using image processing and artificial neural network. The images of soil were captured using digital camera and processed using image process algorithm. The images parameter data i.e. red, green, blue, hue, saturation, intensity, mean, entropy, energy, contrast, and homogeneity were extracted from sixty soil sample with different organic matter content. Parameter images data were used as the inputs data for ANN analysis. Output layer of ANN is organic matter content in soil. Based on experiment found that application of image processing and ANN for predicting organic matter content in soil have the high accuracy with coefficient determination of  90.75 % and mean square error (MSE) of 0.002762. Keywords : soil organic matter, images process, artificial neural network Abastrak Tujuan penelitian adalah menentukan kadar bahan organik dalam tanah menggunakan pengolahan citra digital dan jaringan syaraf tiruan. Citra tanah diambil menggunakan sebuah camera digital dan diolah menggunakan algoritma pengolahan citra. Parameter citra yang digunakan adalah : red, green, blue, saturasi, intensitas, rerata, entropi, energi, kontras, dan homogenitas diambil dari 60 contoh tanah dengan kadar bahan organik yang berbeda. Parameter citra tersebut digunakan sebagai data masukan dalam analisis ANN., sebagai lapisan keluaran dari ANN adalah kadar bahan organik dalam tanah. Berdasarkan hasil penelitian dan analisis pengolahan citra dan ANN dapat digunakan untuk emprediksi kadar bahan organik dalam tanah dengan akurasi tinggi dengan kooefisien determinasi 90,75% dan MSE 0,002761. Kata kunsi : bahan orgaik tanah, pengolahan citra, jaringan syaraf tiruan.Diterima: 12 Agustus 2010; Disetujui: 03 Januari 2011 

Determination of Hydrodynamic Dispersion Coefficient of Solute Transfort in Soil Using Inverse Problem Method

Jurnal Keteknikan Pertanian Vol 16, No 1 (2002): Buletin Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

Solute transport in porous medium is affected by two parameters i.e : 1) average velocity of solute particle, and 2) solute dispersion. Theoretically, the solute transport can be describes by Convective Dispersion Equation, when the methods to determine D in this paper we present a modified method of inverse problem to calculate D. The results indicated that the inverse problem much or less matched with the analytical solution.

Teknik Rekayasa Pemadatan Kayu II : Sifat Fisik dan Mekanik Kayu Agatis (Agathis lorantifolia Salisb.) Terpadatkan dalam Konstruksi Bangunan Kayu

Jurnal Keteknikan Pertanian Vol 17, No 1 (2003): Buletin Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

The successful application of pitcher irrigation system has motivated to investigate the pitcher as a fetigation system. The experiment was conducted at Leuwikopo Experiment Station, Agricultural Engineering Departemen, Bogor Agricultural University. The main objective of this study is to study the effectiveness of pitcher fertigation system on bushes pepper crops. The result shows that the pitcher wall is capable to release NPK solution. Diffusion rate of fertilizer solution was measured as affected by the concentration inside and outside of the pitcher. The soil moisture distribution in the soil is sufficient to transfor the solution available for crops development. Concentration of Phosphate (P) and Potassium (K) decrease laterally and the Nitrogen (N) tends to accumulate homogeneously in moist part around the pitcher.

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