Judul: Penghilangan Gas H2S dan NH3 dengan Teknik Biofilter pada Ruang Produksi Pabrik Karet PTPN VIII Cikumpay, Purwakarta
Abstrak: Karet alam (natural rubber) yang diperoleh dari tanaman Hevea Braziliensis merupakan salah satu komoditas ekspor unggulan Indonesia yang jumlahnya cukup besar. Perkembangan industri karet menyebabkan timbulnya emisi berupa amoniak (NH3) dan hidrogen sulfida (H2S) yang mengganggu kesehatan pekerja pabrik karet. Biofilter adalah teknologi pengendalian pencemaran udara dengan cara menumbuhkan mikroorganisme pada bahan pengisi sehingga terbentuk biofilm atau biolayer yang dapat mengurai bahan-bahan pencemar udara.
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Judul: Penerapan biofilter untuk penghilangan NH3 dan H2S dengan menggunakan bakteri Nitrosomonas sp dan Thiobacillus sp di pabrik latek pekat
Abstrak: Karet merupakan salah satu komoditi hasil pertanian yang sangat besar. Jumlah produksi karet Indonesia pada tahun 2004 mencapai 1.851 juta ton yang terdiri dari perkebunan rakyat dan perkebunan besar. Karena jumlah produksi karet yang sangat besar, maka industri karet di Indonesia mengalami perkembangan seperti industri RSS (Ribbed smoked sheet), karet remah dan lateks pekat. Berkembangnya industri ini menghasilkan masalah baru yaitu pencemaran lingkungan. Salah satunya adalah pencemaran udara yang dihasilkan dari parik lateks pekat dimana lateks pekat ini membutuhkan amoniak yang cukup banyak dalam proses produksinya dan menghasilkan gas H2S dari limbah cair dan lump. Tujuan utama penelitian ini adalah untuk mengetahui kemampuan teknik biofilter dalam mengatasi permasalahan emisi gas yang dikeluarkan dari pabrik lateks pekat. Tujuan khususnya adalah menentukan kapasitas penyerapan emisi gas pada masing-masing biofilter dan menentukan campuran bahan pengisi tambahan terhadap kinerja biofilter berdasarkan kemampuan menghilangkan emisi gas amoniak dan hidrogen sulfida.
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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