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: Agrometeorological Analysis of Inpari 32 Rice Productivity with Variations in Plant Spacing
Abstrak: Padi varietas Inpari 32 yang ditanam dengan 3 (tiga) variasi sistem tanam menunjukkan respon agrometeorologis yang berbeda. Hal ini dibuktikan melalui percobaan lapang pada Juli 2020 – Oktober 2020 di area persawahan irigasi di Desa Pasir Kaliki, Kabupaten Karawang, Jawa Barat. Padi varietas Inpari 32 ditanam menggunakan 3 (tiga) sistem tanam yaitu sistem tanam Jajar Tegel (P1), Jajar Legowo (P2), dan Jejer Manten (P3). Populasi dari masing-masing sistem tanam yaitu 16 tanaman/m2 untuk P1, 21 tanaman/m2 untuk P2, dan 19 tanaman/m2 untuk P3. Kajian agrometeorologi berbasis pemodelan simulasi tanaman padi digunakan untuk menganalisis respon tanaman padi pada 3 (tiga) sistem tanam tersebut. Model yang telah dikembangkan ini terdiri atas sub model pertumbuhan, sub model perkembangan, dan sub model neraca air. Model memerlukan input karakteristik fenologi padi, sifat fisik tanah, dan data cuaca harian. Proses kalibrasi dan validasi menunjukkan bahwa luaran model dipengaruhi oleh Specific leaf area (SLA) dan Radiation use efficiency (RUE) yang nilainya bervariasi selama masa tanam. Variasi SLA dan RUE Inpari 32 yang ditanam pada 3 (tiga) sistem tanam berkorelasi dengan produktivitasnya. Pendekatan mekanistik dan empiris yang digunakan dalam pengembangan model berhasil menjelaskan pengaruh variasi sistem tanam terhadap produktivitas padi. Hal ini ditunjukkan dengan nilai produktivitas padi dari model yang mendekati produktivitas padi pada plot percobaan. Output model pada perlakuan P1, P2, dan P3 berturut-turut adalah 5496 kg/ha, 5196 kg/ha dan 5372 kg/ha. Produktivitas aktual Inpari 32 dari petak percobaan dengan perlakuan P1, P2, dan P3 berturut-turut adalah 5475 kg/ha, 5050 kg/ha, dan 5350 kg/ha. Nilai akurasi model dalam menentukan produktivitas Inpari 32 pada 3 (tiga) sistem tanam berbeda adalah 98,8% dengan error 1,2%., The Inpari 32 rice variety planted in three different planting systems showed different agrometeorological responses. This was proven through field experiments in July 2020 – October 2020 in the irrigated rice fields located in Pasir Kaliki Village, Karawang Regency, West Java. The Inpari 32 was planted using 3 (three) planting systems, namely “Jajar Tegel” (P1), “Jajar Legowo” (P2), and “Jejer Manten” (P3). The population of each planting system was 16 plants/m2 for P1, 21 plants/m2 for P2, and 19 plants/m2 for P3. An agrometeorological study based on rice crop modeling was used to analyze the response of rice in the 3 (three) planting systems. This model is consisted of growth and development, and water balance sub-models, which required input rice phenological characteristics, soil physical properties, and daily weather data. The calibration and validation process shown that the model output was influenced by Specific leaf area (SLA) and Radiation use efficiency (RUE), whose values varied during the planting period. Variations in SLA and RUE of Inpari 32 planted in 3 (three) planting systems were correlated with its productivities. The mechanistic and empirical approaches used in model development succeeded in explaining the influence of variations in planting systems on rice productivity. This was indicated by the rice productivity value from the model which was closed to the productivity of experimental plots. The model output with P1, P2 and P3 treatments were 5496 kg/ha, 5196 kg/ha and 5372 kg/ha, respectively. The actual productivity of Inpari 32 from experimental plots
Keyword: planting system, rice crop model, rice productivity, RUE, SLA

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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