Judul: Estimation of Nitrogen Requirements for Inpari 32 Rice Plants Using Plant Simulation Models
Abstrak: Padi merupakan komoditas pertanian sumber pangan yang dibutuhkan dalam skala besar di Indonesia. Nitrogen adalah satu dari 4 unsur hara makro (N, P, K, Mg) yang mutlak diperlukan dalam pertumbuhan dan perkembangan tanaman di mana tingkat pemenuhan kebutuhan nitrogen dapat mempengaruhi produksi atau hasil panen. Hal ini mendasari urgensi penentuan serapan nitrogen pada fase pertumbuhan dan perkembangan padi melalui pendekatan pemodelan dinamika sistem untuk mengestimasi kebutuhan N tanaman. Model simulasi yang dikembangkan terdiri dari: (1) sub model perkembangan tanaman; (2) sub model pertumbuhan tanaman; (3) sub model neraca air; dan (4) sub model neraca nitrogen. Produktivitas hasil dari model simulasi dengan perlakuan F1, F2 dan F3 berturut-turut yaitu 5487, 5854 dan 5064 kg/ha. Perbandingan hasil keluaran produktivitas model dengan hasil produktivitas observasi menunjukkan nilai RMSE sebesar 28,90 dan MAPE 0,50 dengan akurasi 99,5 %. Hasil uji-t berpasangan pada kandungan N organ hasil uji Laboratorium Tanah IPB dengan keluaran model secara keseluruhan menunjukkan hasil model tidak berbeda nyata. Berdasarkan pendekatan model, jumlah kebutuhan nitrogen tanaman padi keluaran model yaitu 132 – 144 N kg/ha., Rice is an agricultural commodity which is a source of food needed on a large scale in Indonesia. Nitrogen is one of the 4 macro nutrients (N, P, K, Mg) which are absolutely necessary for plant growth and development where the level of fulfillment of nitrogen needs can affect crop production or yield. This underlies the urgency of determining nitrogen uptake in the growth and development phases of rice through a system dynamics modeling approach to estimate plant N requirements. The simulation model developed consists of: (1) plant development sub model; (2) plant growth sub model; (3) water balance sub model; and (4) nitrogen balance sub model. The productivity results from the simulation model with F1, F2 and F3 treatments were 5487, 5854 and 5064 kg/ha respectively. Comparison of the model productivity output with the observed productivity results shows an RMSE value of 28.90 and MAPE 0.50 with an accuracy of 99.5%. The results of the paired t-test on organ N content from the IPB Soil Laboratory test results with the overall model output showed that the model results were not significantly different. Based on the model approach, the amount of nitrogen requirements for rice plants output from the model is 132 – 144 N kg/ha.
Keyword: simulation model, plant nitrogen, lowland rice, rice productivity

Judul: Development of Empirical Model for Estimation of Rice Nitrogen Accumulation Based on Sentinel 2 Satellite Imagery
Abstrak: Plant Nitrogen Accumulation (PNA) merupakan jumlah total (akumulasi) N dalam tajuk tanaman per satuan luas tanah. PNA adalah sebuah indikator yang menunjukkan status N pada tanaman. Penelitian ini mengusulkan sebuah model empiris untuk menghitung PNA pada lahan sawah yang luas, dengan cepat dan dekat waktu nyata berdasarkan data Sentinel 2. Hasil analisis terhadap hubungan indeks vegetasi dengan data PNA sampel tanaman padi yang diambil dari plot-plot percobaan menunjukkan bahwa status N tanaman padi dapat dideteksi secara dekat waktu nyata menggunakan data Sentinel 2. Analisis statistik juga menunjukkan bahwa variasi temporal dan spasial indeks PNA tanaman padi pada perlakuan teknik tanam dan varietas yang berbeda dapat diestimasi berdasarkan indeks vegetasi dari Sentinel 2. Analisis hubungan data pengukuran PNA tanaman padi dengan delapan metode indeks vegetasi, membuktikan bahwa perhitungan PNA berbasis NDRE merupakan model optimum yang ditunjukkan oleh nilai R2 = 75.17%, RMSE = 22.5 kg/ha, dan akurasi = 80.80% terhadap data training. Validasi model perhitungan PNA berbasis NDRE memiliki performa yang baik dengan 65.08%, RMSE = 45.2 kg/ha, dan akurasi = 74.22%. Model PNA ini telah digunakan untuk memetakan distribusi spasial status N tanaman padi yang berbeda waktu tanaman pada lahan baku sawah Kecamatan Rawamerta, Kabupaten Karawang. Hasil penelitian telah berkontribusi terhadap penerapan prinsip-prinsip pertanian presisi, dengan memberikan landasan penting bagi pengembangan sistem rekomendasi pemupukan berbasis teknologi penginderaan jauh., Plant Nitrogen Accumulation (PNA) is the total amount (accumulation) of N in the plant canopy per unit area of land. PNA is an indicator that shows the N status in plants. This study proposes a method for computing PNA over large areas of rice field, faster and in near real-time based on Sentinel 2 data. The research was proven that the N status of rice plants can be detected in real time using Sentinel 2 data, through empirical analysis of the relationship between the Sentinel 2-based vegetation indices and PNA of rice taken from the experimental plots. Statistical analysis was shown that the temporal and spatial variations of the PNA of rice on different planting techniques and varieties can be determined based on the vegetation indices. Empirical analysis of the PNA based on eight vegetation indices methods were proven that the NDRE-based PNA model was an optimum model, indicated by the value of R2 = 75.17%, RMSE = 22.5 kg/ha, and accuracy = 80.80% to the training data. The performance indicators of the PNA model were calculated with the results of R2 = 65.08%, RMSE = 45.2 kg/ha, and accuracy = 74.22%. The PNA model has been used to map the spatial distribution of the N status of rice plants at different planting stages over rice field area in Rawamerta District, Karawang Regency. The research results have contributed to the application of the principles of precision agriculture, through providing an important basis for the development of a fertilization recommendation system based on remote sensing technology.
Keyword: near real-time measurement, plant nitrogen accumulation, planting technique, rice varieties, vegetation indices

Judul: Pelabelan Super Vertex Magic
Abstrak: Super vertex magic labeling is labeling on graph with is a set of edges mapped into and is a set of vertices mapped into . It has a vertex magic labeling in which and represents the size and order of the graph respectively. This manuscript proves that paths, cyclics, and disjoint union of cyclics have a super vertex magic labeling. There are four theorems to be discussed. The first theorem proves that path is super vertex magic if and only if is odd and . The second theorem proves that cyclic is super vertex magic if and only if is odd. The third theorem proves that bijection function from an edge set onto of graph can be extended to a super vertex magic labeling if and only if the set amount of edge label that incidents with a vertex in the graph, consists of sequential integers as many as vertices in the graph. The fourth theorem proves that disjoint union of the cyclics consists of cyclics with each cyclic has vertices is super vertex magic if and only if and are odd.
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