Judul: Mutu Air di Kampus IPB Darmaga
Abstrak: Tujuan penelitian ini meliputi inventarisasi karakteristik suplai air di kampus IPB Darmaga, agar dapatdiketahui apakah karakteristiknya memenuhi persyaratan mutu yang telah ditetapkan atau tidah sehingga bisa diadakan perbaikan proses bila diperlukan dan mengamati konsitensi mutu selama beberapa periode.
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Judul: Analisis Kualitas Air Pada Jalur Distribusi Air Bersih di Gedung Baru Fakultas Ekonomi dan Manajemen Institut Pertanian Bogor
Abstrak: Salah satu penyebab menurunnya kualitas air adalah meningkatnya kegiatan manusia yang tidak bijak sehingga menimbulkan pencemaran air. Sungai Cihideung dijadikan sebagai sumber air di kawasan kampus yang airnya dimanfaatkan untuk berbagai keperluan di Kampus IPB Dramaga. Tujuan penelitian ini adalah menganalisis kualitas air bersih dari ground water tank (GWT) Cihideung sampai gedung baru FEM serta membandingkannya dengan baku mutu yang berlaku, menentukan kriteria mutu air bersih berdasarkan metode STORET, dan menganalisis pengaruh waktu pengukuran dan cuaca terhadap kualitas air. Parameter yang tidak melebihi baku mutu adalah TDS, kekeruhan, suhu, besi, fluorida, klorida, mangan, dan sulfat, serta parameter biologi yaitu total koliform/E.Coli. Parameter yang melebihi baku mutu adalah nilai warna sebesar 60 TCU pada kondisi sore hujan yang terdapat di GWT Cihideung dan nilai pH sebesar 6.38 pada kondisi pagi hujan terdapat di saniter wing 1. Kriteria mutu air jalur distribusi gedung baru FEM menurut sistem US-EPA termasuk ke dalam Kelas B yang artinya cemar ringan.
Keyword: baku mutu, jalur distribusi, kualitas air, pencemaran air

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