Judul: Perencanaan Media Interpretasi di Kawasan Hutan dengan Tujuan Khusus (KHDTK) Cikampek, Kabupaten Karawang, Provinsi Jawa Barat
Abstrak: Kawasan Hutan dengan Tujuan Khusus (KHDTK) Cikampek merupakan kawasan hutan tertentu yang ditetapkan oleh pemerintah dengan tujuan penelitian dan non penelitian. Salah satu kegiatan non penelitian yang telah dilakukan adalah kegiatan wisata. Beberapa kegiatan wisata tersebut mengakibatkan sampah yang berserakan sehingga menganggu kenyamanan, mengurangi nilai edukasi dan estetika kawasan. Untuk mengatasi masalah tersebut, diperlukan upaya dalam menyadarkan dan meningkatkan pemahaman pengunjung terhadap lingkungan melalui media interpretasi. Fungsi lain dari media interpretasi adalah melindungi sumberdaya kawasan serta mengenalkan pengelolaan KHDTK Cikampek. Penelitian dilaksanakan di KHDTK Cikampek pada bulan Februari, Mei-Juni 2012. Teknik pengumpulan data dilakukan dengan metode observasi lapang, wawancara, dan studi literatur.
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Judul: Perencanaan Intepretasi di Kawasan Hutan dengan Tujuan Khusus (KHDTK) Cikampek, Kecamatan Cikampek, Kabupaten Karawang, Provinsi Jawa Barat
Abstrak: Forest Area with Special Purpose is an area which is established by the government for the purpose of research and non-research activity. Nowadays, Cikampek Forest Area with Special Purpose has been visited by many visitors. It became one of the driving factors of the community to the procurement of tourism activities. Yet, there are problems arising from the activities, such as waste problem and irregularity of visitors causes the irregularity of spatial in Cikampek Forest Area with Special Purpose. One solution to solve these problems is to increase visitors and public knowledge to the area through interpretation activity. The general purpose of this research is to make an interpretation planning of Forest Area with Special Purpose in Cikampek. This research specifically aims to identify the object of interpretation, interpretation paths, visitor characteristics, management and community conditions.
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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