Judul: Uji Pemberian Paraquat, Difenoconazole DanButylphenylmethyl Carbamate (BPMC) Terhadap Emisi CO2 dan CH4, serta Perubahan Konsentrasi Asam-Asam Fenolat Di Tanah Gambut
Abstrak: Pesticides are widely used in agriculture land, including agricultural land with peat soil. The Study concerning pesticide and CO2 emission has not been done in Indonesia. The objectives of this study were to analyze the effect of paraquat, difenoconazole, butylphenylmethyl carbamate (BPMC) on CO2 and CH4 emission and concentration of phenolic acids in peat soil. The study was conducted at the Laboratory of Soil Chemistry and Fertility, Department of Soil Science and Land Resource, IPB. Soil Sample was collected in District of Pulang Pisau, Central Kalimantan. Peat soil was treated with paraquat, difenoconazole dan butylphenylmethyl carbamate (BPMC) and incubated for 24, 48, 96, 120 and 168 hours. The results showed that the application of pesticides at the recommendation rates increased CO2 emission compared to that of control. Concentration of total phenolic acid of all treatments decreased sharply compared to that of initial data where the concentration of total phenolic acids of treated ones were lower than those of control except BPMC. The results suggested that CO2 emission were from Carbon of degraded phenolic acid and pesticides. The application of pesticides with recommendation rate decreased CH4 emission compared to that of control.
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Judul: Pengaruh Pemberian Paraquat, Difenoconazol, dan BPMC (Buthylphenylmethyl Carbamate) Terhadap CO2 yang Dilepaskan dari Bahan Gambut dengan Inkubasi Tertutup dan Terbuka
Abstrak: The use of pesticides in agriculture is considered practically to eradicate the pests and plant diseases. However there are woried about the impact of environmental pollution on soil and water. In addition, other important environmental issues from the peat soil is carbon emissions. Peat soils have high organic carbon, so that when the carbon is lost through oxidation process, it will be speed up the release of the carbon emitted into the atmosphere. However, the organic material from peat soil is able to absorb the active materials of pesticides. Therefore, the application of pesticides in peat soils can be expected reduce the carbon release. This study aimed to find out the effect of Paraquat, Difenoconazol, and BPMC (Buthylphenylmethyl Carbamate) on CO2 release from Peat in the form of concentrations and fluxes Materials with Opened and Closed Incubation. Incubation time consists of 1 day, 2 days, 4 days, 5 days, and 7 days. The time was selected according with the retention of pesticides is less than 2 weeks. CO2 concentration and flux measurements is used by IRGA (Infrared Gas Analysis) type LI-802. Gases from a closed chamber flowed into the IRGA by using a pump and CO2 concentration directly read by IRGA every second for approximately 2,5 minutes. The study consisted of closed and opened incubation. In a closed incubation measured of CO2 concentrations, while the open incubation measured of CO2 flux . The results showed in the first seven days of closed incubation, can be increased of the CO2 concentration. In a closed incubation treatment of paraquat, difenoconazol, and BPMC CO2 concentration measured at 6.282,98 ppm, ppm 5.043,72, and 5.112,69 ppm. While control of soil is equal to 4.716,70 ppm. In the opened incubation treatment of paraquat, difenoconazol, and BPMC CO2 flux measured is 0,009 mg/m2/sec, 0,005 mg/m2/sec, and 0,015 mg/m2/sec and control of soil has 0,001 mg/m2/sec. The low rate application of pesticide has not impacted significantly on reducing CO2 concentrations and the relatively short time of application.
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Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm