Penggunaan Smartphone Android sebagai Alat Analisis Kebutuhan Kandungan Nitrogen pada Tanaman Padi
Abstract
Nitrogen (N) is one of the most important nutrients for the growth of rice crops. Unbalanced and excessive use of N-fertilizers causes environmental pollution, reduces quality of the crop, and increases pest pressure, in addition to the increasingcost to farmers from excessively applied fertilizers and pesticides. The goal of this paper is to build mobile applications which can analyze and recommend nitrogen elemental requirements in rice plants based on the color of rice leaves. This application has embedded a set of stages of the process for image processing and classification which is used to analyze the color of rice leaves captured through a smartphone camera. Image processing in this application is a feature extraction of red, green, and blue (RGB) values to obtain a characteristic on the leaf color image. Then the result of feature extraction is used to classify the color level of rice leaf by using a K-Nearest Neighbor method. The results of accuracy test show that accuracy of the application in analyzing and recommending nitrogen fertilizer needed by rice crops, on average, is 66.67%.
References
A. Siregar dan I. Marzuki, “Efisiensi Pemupukan Urea Terhadap Serapan N dan Peningkatan Produksi Padi Sawah (Oryza sativa. L.),” Jurnal Budidaya Pertanian, Vol. 7, No. 2, hal. 107-112, 2011.
P. S. Patti, E. Kaya, dan Ch. Silahooy, “Analisis Status Nitrogen Tanah dalam Kaitannya dengan Serapan N oleh Tanaman Padi Sawah di Desa Waimital, Kecamatan Kairatu, Kabupaten Seram Bagian Barat,” Agrologia, Vol. 2, No. 1, hal. 51-58, 2013.
Erythrina, “Bagan Warna Daun: Alat untuk Meningkatkan Efisiensi Pemupukan Nitrogen pada Tanaman Padi,” Jurnal Litbang Pertanian, Vol. 35, No. 1, hal. 1-10, 2016.
I. Nariratih, M. Damanik, dan G. Sitanggang, “Ketersediaan Nitrogen pada Tiga Jenis Tanah Akibat Pemberian Tiga Bahan Organik dan Serapannya pada Tanaman Jagung,” Jurnal Online Agroekoteknologi, Vol. 1, No. 3, hal. 479-488, 2013.
S. E. F. Yanti, E. Masrul dan H. Hannum, “Pengaruh Berbagai Dosis dan Cara Aplikasi Pupuk Urea Terhadap Produksi Tanaman Sawi (Brassica Juncea L.) pada Tanah Inceptisol Marelan,” Jurnal Online Agroekoteknologi, Vol. 2, No. 2, hal. 770-780, 2014.
A. S. Wahid, “Peningkatan Efisiensi Pupuk Nitrogen pada Padi Sawah dengan Metode Bagan Warna Daun,” Jurnal Litbang Pertanian, Vol. 22, No. 4, hal. 156-161, 2003.
Z. Islam, B. Bagchi dan M. Hossain, “Adoption of Leaf Color Chart for Nitrogen Use Efficiency in Rice: Impact Assessment of a Farmer-Participatory Experiment in West Bengal, India,” Field Crops Research, Vol. 103, No. 1, hal. 70-75, Juli 2007.
S. Sarun dan A. Somboonkaew, “Low-Cost Cell-Phone-Based Digital Lux Meter,” Proc. SPIE, Vol. 7853, No. 78530L, 2010.
S. Sumriddetchkajorn, A. Somboonkaew, dan S. Chanhorm, “Mobile Device-Based Digital Microscopy for Education, Healthcare, and Agriculture,” International Conference on ECTI, 2012, hal. 1-4.
I. H. Robbani, E. Trisnawati, R. Noviyanti, A. Rivaldi, F. P. Cahyani, dan F. Utaminingrum, “Aplikasi Mobile Scotect: Aplikasi Deteksi Warna Tanah dengan Teknologi Citra Digital pada Android,” Jurnal Teknologi Informasi dan Ilmu Komputer, Vol. 3, No. 1, hal. 19-26, April 2016.
J. Utama, “Akuisisi Citra Digital Menggunakan Pemrograman MATLAB,” Majalah Ilmiah Unikom, Vol. 9, No. 1, hal. 71-80, 2011.
J. Han dan M. Kamber, Data Mining Concepts and Techniques, San Francisco: Morgan Kaufmann, 2006.
H. Leidiyana, “Penerapan Algoritma K-Nearest Neighbor untuk Penentuan Resiko Kredit Kepemilikan Kendaraan Bermotor,” Jurnal Penelitian Ilmu Komputer, System Embedded & Logic, Vol. I, No. 1, hal. 65-76, 2013.
A. C. Rencher, Methods of Multivariate Analysis, Canada: Wiley Interscience, 2002.
M. Bramer, Principles of Data Mining, London: Springer, 2007.
F. Liantoni, “Klasifikasi Daun dengan Perbaikan Fitur Citra Menggunakan Metode K-Nearest Neighbor”, Jurnal Ultimatics, Vol. VII, No.2, hal.98-104, 2015.
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