Judul: Tipologi Mangrove dan Keterkaitannya dengan Kondisi Lingkungan di Desa Karangsong Indramayu
Abstrak: Mangrove is defined one of the vegetation types in tidal areas. This research was conducted to find out the typology of mangrove and the relationship with environmental condition in Karangsong village. The observations result showed that mangrove vegetation in Karangsong consisted of Api Api (A. marina) and Bakau (R. marina). Density of mangrove consist of tree stage (35.67-0.5 ind/100m2), sapling stage (0-34.67 ind/100m2) and seed stage (0-31 ind/m2) for each species. A. marina is more adaptive due to a high value of mangrove density and INP. Environment condition of Karangsong still in growth optimal range of mangrove. Based on the fact, it is recommendated to plant dan do rehabilitation.
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Judul: Estimation of Carbon Content in Mangrove Stands in the Karangsong Mangrove Ecotourism Area, Indramayu Regency
Abstrak: Hutan mangrove mempunyai potensi mitigasi perubahan iklim karena kemampuannya dalam menyerap dan menyimpan karbon dalam waktu lama dan dalam jumlah besar. Adanya alih fungsi lahan dapat merubah komposisi vegetasi hutan mangrove dan mengurangi simpanan karbon. Penelitian ini bertujuan untuk mengetahui komposisi vegetasi pada kawasan ekowisata mangrove Karangsong dan mengetahui kemampuan mangrove dalam menyerap serta menyimpan karbon. Metode dalam penelitian ini yaitu jalur garis berpetak pada 10 titik stasiun pengamatan yang dianggap mewakili keseluruhan karakteristik vegetasi dengan total intensitas sampling sebesar 5%. Analisis kandungan karbon dilakukan menggunakan persamaan alometrik. Dari hasil analisis vegetasi terdapat 4 jenis mangrove, yiatu Avicennia marina, Avicennia alba, Rhizophora stylosa, Rhizophora mucronata. Total biomassa, kandungan karbon dan simpanan karbon dioksida seluruh kawasan seluas 20 ha yaitu beturut-turut sebesar 99,14 ton/ha; 46,6 tonC/ha; 171 tonCO2 /ha. Besarnya kandungan karbon yang tersimpan di kawasan ekowisata Mangrove Karangsong dipengaruhi oleh faktor lingkungan yang terbentuk pada tegakan mangrove., Mangrove forests have the potential to mitigate climate change because of their ability to absorb and store carbon for a long time and in large quantities. The existence of land use change can change the composition of mangrove forest vegetation and reduce carbon sequestration. This study aims to determine the composition of vegetation in the Karangsong mangrove ecotourism area and to determine the ability of mangroves to absorb and store carbon. The method in this study was a line transect plot at 10 points of observation stations which are considered to represent the overall characteristics of the vegetation, the total sampling intensity is 5%. Carbon content analysis was carried out using allometric equations. From the results of the vegetation analysis, there were 4 types of mangroves, namely Avicennia marina, Avicennia alba, Rhizophora stylosa, and Rhizophora mucronata. The total biomass, carbon content, and carbon dioxide uptake in the entire area of 20 ha are 99.14 tons/ha; 46.6 tonsC/ha; and 171 tonsCO2/ha, respectively. The amount of carbon stored in the Karangsong Mangrove ecotourism area was influenced by environmental factors formed in the mangrove stands.
Keyword: biomassa, karbon, mangrove, vegetasi

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