Judul: Studi Iklim Mikro Taman Kota (Taman Ade Irma suryani) di Komadya Bandung
Abstrak: Pembangunan banyak mengalih fungsikan ruang terbuka hijau menjadi pertokoan, tempat rekreasi, dan pemukiman. Meningkatnya jumlah penduduk yang disertai dengan tingginya tingkat aktivitas manusia khususnya di Kotamadya Baandung meyebabkan kualitas lingkungan mennjadi menurun. Menurut Dahlan (1992) hijaunya kota tidak hanya menjadikan kota tersebut indah dan sejuk namun mencakup pula aspek kelestarian, keserasian, keselarasan dan keseimbangan sumber daya alam yang pada gilirannya akan memberikan manfaat berupa kenyamanan, kesegaran, terbebasnya kota dari polusi, kebisingan serta sehatnya warga kota. Penelitian tentang pengaruh hutan kota terhadap iklim mikro lingkungan sekitar belum banyak dilakukan, sehingga penelitian tentang ini sangat diperlukan untuk dapat mernberikan gambaran sejauh mana efektivitas hutan kota memberikan pengaruh terhadap lingkungan sekitarnya.
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Judul: Studi Iklim Mikro di hutan kota manggala wanabakti jakarta
Abstrak: Dengan semakin meningkatnya pembangunan di perkotaan menyebabkan semakin berkurangnya Ruang Terbuka Hijau (RTH), sebagian besar lahan kota menjadi tertutup oleh beton/tembok serta aspal yang sudah barang tentu menimbulkan perubahan sifat thermal dan keadaan neraca energi lahan kota. Hal ini ditandai dengan meningkatnya suhu udara dan sebaliknya kelembaban nisbinya semakin menurun. Tujuan penelitian ini adalah untuk mengetahui fluktuasi iklim mikro (suhu udara dan kelembaban nisbi udara) yang terjadi pada ke empat lokasi yang berbeda tipe penutupan lahannya, serta membandingkan perubahan iklim mikro yang terjadi pada lokasi hijau (bervegetasi) dengan lokasi terbuka (tanpa vegetasi). Penelitian ini dilaksanakan di Manggala Wanabakti Jakarta dimana pengambilan data di lapangan dilakukan pada Taman Hutan Persahabatan, Taman Parkir, Taman Rumput dan Lapangan Upacara. Adapun parameter yang diukur adalah suhu udara, kelembaban nisbi udara, kecepatan angin pada ketinggian 1,5 m di atas ..dst
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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