Judul: Pengaruh fenomena iodm terhadap pola penyebaran klorofil di perairan barat sumatera
Abstrak: Fenomena Indian Ocean Dipole Mode (IODM) ditemukan pertama kali oleh para peneliti yang tergabung dalam Climate Variations Research Program (CVRP) dari Frontier Research Center for global Change (FRCGC). Fenomena IODM dapat diidentifikasikan dengan menggunakan Dipole Mode Index (DMI). Jika DMI bernilai positif, SPL di Samudera Hindia bagian timur menjadi rendah dan sebaliknya terjadi di Samudera Hindia bagian barat. Sedangkan, jika SPL di Samudera Hindia bagian timur menjadi tinggi dan sebaliknya terjadi Samudera Hindia bagian barat maka DMI akan bernilai negatif. Berdasarkan nilai DMI tersebut, IODM dibagi menjadi dua fase yakni IODM positif dan IODM negatif yang kemungkinan dapat menyebabkan terjadi upwelling di pantai barat Sumatera. Penelitian ini bertujuan untuk mengetahui pola sebaran klorofil-a secara spasial. Serta mengetahui seberapa jauh pengaruh IODM terhadap pola sebaran klorofil-a di perairan barat Sumatera.
Keyword: 

Judul: Kajian kesuburan perairan pada tiga kondisi moda dwikutub samudera hindia (indian ocean dipole mode) hubungannya dengan hasil tangkapan ikan pelagis di Perairan Barat Sumatera
Abstrak: The Indian Ocean Dipole Mode (IOD/IODM) is an oscillation of the interaction between atmosphere and ocean system. IODM comprises of bipolar structure that characterized by the difference of sea surface temperature to normal. This phenomenon provides important influence to the several parameters of oceanographyc. While the positive event of IODM, during southeast munsoon (June to October), southeasterly wind from Australia generates upwelling, bringing cooler waters and increased nutrients to the surface along the southern coast of Java and Sumatera and its condition has been increasing chlorophyll-a concentration. The objectives of this study is to know the variability of chlorophyll-a along the southern coast of Java and Sumatera on positive IODM event. The sea surface temperature (SST) images taken from thermal sensor of Advanced Very High Resolution Radiometer-National Oceanic and Atmospheric Administration (AVHRR-NOAA) has been used to detect the cooler water as upwelling indicator. We investigated the spasial and temporal variability of chlorophyll-a along the south coasts of West Java and Sumatera from September 1997 to December 2009, by using the data of the Sea-viewing Wide-field of view sensor (SeaWiFS) of Sea Star satellite. The results shown that formation phase of IODM in transitional season I (May), while the strengthening of the South Equatorial Current followed by early cooling of the SST. The maturation phase in the southeast monsoon (June to August) and decay phase in November was followed by warming of the SST. At the Southeast monsoon (June to August), there is a visible presence of upwelling in the south of Java and western coast of Sumatera. Upwelling with highly intensity was founded in the southern coast of Java and western part of Sumatera on strong positive IODM event assosiated with intermediate of El Niño event, 1994. Higer chlorophyll-a concentration corresponds very well with monsoon-generated upwelling during the Southeast monsoon cycle. During the peak of anomalous easterly winds on strong positive IODM event (1997 and 2006) were induced strong upwelling. This event produced higher chlorophyll-a concentration that extended further northwest-ward along the Sumatera coast. The impact of upwelling while the IODM positive event on pelagic fish catch, likely follow the temporal variability in chlorophyll.
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