Article Per Year (5 Year)
p-Index From 2020 - 2025
1.288
P-Index
This Author published in this journals
All Journal Jurnal Penyuluhan Jurnal Manajemen dan Agribisnis Jurnal Agribisnis Indonesia (Journal of Indonesian Agribusiness) Jurnal Keteknikan Pertanian Tropis dan Biosistem Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Logic : Jurnal Rancang Bangun dan Teknologi J-Dinamika: Jurnal Pengabdian Kepada Masyarakat
Abdul Holik
Agribusiness Department, Politeknik Negeri Banyuwangi
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Mechanical Engineering

Published : 10 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Ilmiah Rekayasa Pertanian dan Biosistem

 1 
PREDIKSI HASIL PANEN PADI MENGGUNAKAN PESAWAT TANPA AWAK Abdul Holik; Riza Rahimi Bachtiar
Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Vol 7 No 2 (2019): Jurnal Ilmiah Rekayasa Pertanian dan Biosistem
Publisher : Fakultas Teknologi Pangan & Agroindustri (Fatepa) Universitas Mataram dan Perhimpunan Teknik Pertanian (PERTETA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (952.013 KB) | DOI: 10.29303/jrpb.v7i2.139

Abstract

Prediction of agricultural products is needed in terms of planning and decision making as well as in policy making for national food security. One strategic commodity that needs special attention is rice. This study aims to predict rice yields using unmanned aircraft. The results of image acquisition are processed by multi thresholding method to separate leaf objects, rice panicles, and background. Furthermore, the results of sorting objects are used as input in making predictions of rice crop models using artificial neural networks. To compare the results of predictions, we weighed the weight of rice harvest on each block. The results showed that between predictions and actual correlations were very strong with R2 = 0.88, MSE (Mean Square Error) = 0.169 and MAPE (Mean Absolute Percentage Error) values ​​were -0.006. These results indicate that the prediction model of rice yields can be used for estimation purposes.
Co-Authors abdul Ardito Atmaka Aji Danang Sudarso Widya Prakoso Joyo Widakdo Danang SWPJ Widakdo Halil H Halil Halil Herman Yuliandoko Lutfi Nur Iska Mohammad Aziz Yusuf Muhammad Habbib Khirzin Nurwahyuningsih Nurwahyuningsih Riyan Budiyanto Riza Rahimi Bachtiar Riza Rahimi Bachtiar Riza Rahimi Bachtiar Zulis Erwanto