Judul: Analisis dinamika perubahan stok karbon di dalam Kawasan Taman Nasional Meru Betiri pada kondisi ada proyek CDM kehutanan
Abstrak: Perubahan iklim yang menjadi isu global dewasa ini merupakan akibat dari peningkatan emisi Gas Rumah Kaca (GRK) di atmosfer. Berdasarkan Protokol Kyoto, yang termasuk GRK adalah CO2 CH4, ,N2O, HFCs, dan SF6. Gas Rumah Kaca yang dianggap menjadi penyebab utama perubahan iklim adalah CO2, dan CH4, (Kementrian Lingkungan Hidup, 2001). Salah satu mekanisme yang ditawarkan Protokol Kyoto sebagai solusi penekanan emisi CO2 adalah Clean Development Mechanism (CDM).
Keyword: 

Judul: Pendugaan perubahan cadangan karbon di Taman Nasional Gunung Merapi
Abstrak: Climate change is a direct effect of global warming. Global warming means increasing temperature of the earth's which directly related to greenhouse gases (GHG) emissions from human activities. Solutions to accomplish climate change from effect of global warming are adaptation and mitigation. Increasing carbon stocks and reducing GHG emissions from human activities is an effective ways of mitigation climate change. Forest is an area that could absorb and save carbon stocks through photosynthesis. Gunung Merapi National Park (GMNP) is a region that has forests with several types of land use changed because of human activities or natural processes. This change will affect the amount of carbon stock at GMNP, whereas GMNP forest can used as be baseline of carbon sink area and carbon stock. The study aimed to assess carbon stocks changes within period of 1991−2001, 1991−2009, and 2001−2009. Carbon stocks measurement was conducted in 3 months from June to August 2010. Materials used in the research are Landsat 5 TM and Landsat 7 ETM (Path 120 Row 065), earth visual map, and boundaries region map. Carbon stocks above ground measured by using non-destructive methods for trees and destructive methods for ground cover, bushes, and grassland. Processing data of biomass assessment using allometry equation which will be converted to carbon values. Carbon measurement was conducted at 35 plots from various types of land used, namely secondary forest, mixed plantation forest, pine plantation forest, shrub, bamboo, bush, and grassland. The largest land used carbon stocks was secondary forest (172.08 Mg.ha-1) and the smallest carbon stocks were shrub and grassland (3.62 Mg.ha-1). Carbon stocks in period 1991−2001 was declined 157458.71 Mg and in period 1991-2009 was also reduced of about 145391.26 Mg, but period 2001−2009 was increased by 12067.45 Mg. There was trend of carbon stocks in GMNP declined in period of 1991 to 2001, conversely in 2009 tended to increase although the increasing was very small.
Keyword: 

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