Judul: Dampak Ekonomi Pencemaran Air Terhadap Perikanan Budidaya Sistem Keramba Jaring Apung (KJA) di Waduk Cirata, Kabupaten Bandung Barat
Abstrak: This research aims to analyze the economic impact of water pollution on aquaculture in Cirata Reservoir. Impact of water pollution in Cirata is declining fish productivity of floating cage aquaculture. Based on the data analysis there are 8 factors that could explain the presence of contamination in the last 5 years which has exceeded the threshold of category C (Pb, Zn, Cl2, H2S, DO, Cu, Cd, and Nitrite). Further multiple regression analysis of water quality impact on the productivity of floating cage. Showed that, only variable DO levels is statistically significant effect on productivity of floating cage. Value of economic loss is calculated based declining productivity amounting to Rp 985.485.382.718 in 2011. The results of the calculation of economic loss in the last 5 years amounting to Rp 4.219.702.954.280. There are five policys identified which were restrictions on the amount of floating cage with progressive taxation, tax collection at each floating cage aquaculture for environmental improvement costs (Rp 10/kg crops), installation of waste filter, biological cleaners, and withdrawals floating cage which are not enviromental friendly (floating made of styrofoam) and unused. AHP analysis results that the first policy priority is the installation of waste filter policy.
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Judul: Estimasi Nilai Kerugian Ekonomi akibat Pencemaran Air di Waduk Cirata, Wilayah Kabupaten Cianjur, Provinsi Jawa Barat
Abstrak: Cirata Reservoir is one of cascade reservoir which was built by dammed Citarum River’s flow for some purposes, such as hydropower plant, fisheries, and floating cage aquaculture. Cirata Its water quality is declining due to water pollution. This pollution causes economic losses for the users of Cirata Reservoir, those are: floating cage aquaculture farmers, fishermen, and PT. PJB UP Cirata as the management of Cirata hydropower plant. This research aims to identify the respondents’ perceptions about the water pollution use descriptive analysis and to estimate the economic losses which are caused by water pollution in Cirata Reservoir Cianjur Regency in 2013 use economic loss approach and benefit transfer method. Commonly, the respondents understand about the water pollution in reservoir and suffered by it. Based on data analysis obtained that economic loss estimation of floating cage aquaculture is IDR 427,581,110,250.00 (the biggest loss), economic loss estimation of fisheries is IDR 1,176,696,421.00, and economic loss estimation of hydropower plant is IDR 198,418,167,672.67. Therefore, total economic loss estimation due to water pollution in Cirata Reservoir Cianjur Regency in 2013 is IDR 628,175,974,343.67.
Keyword: water pollution., resource damage assessment, economic loss, Cirata Reservoir

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