Rudiyanto .
Fakultas Teknologi Pertanian, Institut Pertanian Bogor

Published : 6 Documents
Articles

Found 6 Documents
Search

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

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

ALGORITMA FILTER KALMAN UNTUK MENGHALUSKAN DATA PENGUKURAN

Jurnal Keteknikan Pertanian Vol 20, No 3 (2006): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

ABSTRACT The objective of this paper is to apply a simple algorithm of Kalman Filter, wich is know as noise data filtering. The computer program was written in Macro Visual Basic in MS Exel. Testings were carried out on available temperature, Water level and force data and then were comared with the mooving average method. The result shows that the algorithm performed better and lesser deviation than the mooving average. Keyword: Kalman Filter, mesurement data, computer program Diterima: 30 Oktober 2006; Disetujui: 14 Nopember 2006

ALGORITMA FILTER KALMAN UNTUK MENGHALUSKAN DATA PENGUKURAN

Jurnal Keteknikan Pertanian Vol 20, No 3 (2006): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

ABSTRACT The objective of this paper is to apply a simple algorithm of Kalman Filter, wich is know as noise data filtering. The computer program was written in Macro Visual Basic in MS Exel. Testings were carried out on available temperature, Water level and force data and then were comared with the mooving average method. The result shows that the algorithm performed better and lesser deviation than the mooving average. Keyword: Kalman Filter, mesurement data, computer program Diterima: 30 Oktober 2006; Disetujui: 14 Nopember 2006

PERBAlKAN METODE PENGHITUNGAN DEBIT SUNGAI MENGGUNAKAN CUBIC SPLINE NTERPOLATION

Jurnal Keteknikan Pertanian Vol 21, No 3 (2007): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Original Source | Check in Google Scholar

Abstract

ABSTRAKMakalah ini menyajikan perbaikan metode pengukuran debit sungai menggunakan fungsi cubic spline interpolation. Fungi ini digunakan untuk menggambarkan profil sungai secara kontinyu yang terbentuk atas hasil pengukuran jarak dan kedalaman sungai. Dengan metoda baru ini, luas dan perimeter sungai lebih mudah, cepat dan tepat dihitung. Demikian pula, fungsi kebalikannnya (inverse function) tersedia menggunakan metode. Newton-Raphson sehingga memudahkan dalam perhitungan luas dan perimeter bila tinggi air sungai diketahui. Metode baru ini dapat langsung menghitung debit sungaimenggunakan formula Manning, dan menghasilkan kurva debit (rating curve). Dalam makalah ini dikemukaan satu canton pengukuran debit sungai Rudeng Aceh. Sungai ini mempunyai lebar sekitar 120 m dan kedalaman 7 m, dan pada saat pengukuran mempunyai debit 41 .3 m3/s, serta kurva debitnya mengikuti formula: Q= 0.1649 x H 2.884 , dimana Q debit (m3/s) dan H tinggi air dari dasar sungai (m).Kata Kunci: Debit Sungai, Penarnpang dan Perimeter Basah Sungai, Cubic Spline Interpolation.Diterima: 8 Agustus 2007; Disetujui: 22 Agustus 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 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