Judul: Pendugaan Potensi Simpanan Biomasa dan Karbon dari Tegakan Jati (Tectona grandis) Tidak Terbakar dan Pasca Kebakaran Permukaan di KPH Indramayu
Abstrak: Global warming is the one of forest fires impact in environments. Global warming have impact to make climate changed because the concentration of carbon have increased in the air. The measurement of carbon storage in the forest is the one of important aspect to know the total of carbon. This research aims to estimate and compare carbon storage in the standing teak that unburned and post fire surface. The measurement of standing biomass used the approach volume method while undergrowth and litter used destructive method. The result show that the biomass potency in surface fires area is 46.34 tons/ha is bigger than unburned area is 41.39 tons/ha. Estimation of potency of carbon storage is proportional to the biomass potency. Carbon storage in surface fires area is 23.17 tonsC/ha and in unburned area is 20.69 tonsC/ha.
Keyword: Bogor Agricultural University (IPB), standing teak, forest fires, carbon storage, biomass

Judul: Pendugaan simpanan karbon yang terikat di areal hutan bekas kebakaran PT. Ratah Timber, Kalimantan Timur
Abstrak: Forest is one of natural resources that can be renewable and essential for human life. Forest fire is one of the disorders that occur in the forest. Forest fires cause reduced carbon stored in forests. This study aims to estimate the carbon bound stored in forestland after forest fires in PT. Ratah Timber, East Kalimantan. In this research, carbon bound storage prediction using destructive methods. Data were collected with a plot size 20 m x 50 m in the area of former forest fire as many as 30 pieces. Data was collected base on type of tree, diameter at breast height (dbh), tree height and wet weight. The samples taken are examples of trees with a diameter of 5-9 cm by 30 samples. Dry weight samples were obtained from measurements in the laboratory. Biomass estimators model used is the model by using variable diameter and total height that is B = 0,113501 D1, 22 T1,12. Carbon storage is obtained from half the value of biomass. The results showed that the bound total carbon stored in forestland after forest fires in PT. Ratah Timber, East Kalimantan used for 19,629 tons/ha and a whole area of 168,817 x 103 ton. Trees can provide carbon savings of 34,20 % of total carbon stored while the poles could contribute carbon savings of 33,66% of total carbon savings. Sapling also contribute enough carbon savings that is equal to 18,10% of the total carbon savings. Litters and under plants are also able to absorb carbon in forests. Litters is able to provide carbon deposits 13,05% of total carbon stored while under plant carbon deposits contribute 0,99% of total carbon savings. Saplings and poles contribute significant of saving carbon on the forest.
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