Judul: Evaluasi Kondisi Air Sungai dan Mata Air PDAM Tirta Pakuan Kota Bogor
Abstrak: Air merupakan kebutuhan vital yang menjadi barang publik dan sekaligus menjadi elemen terpenting bagi kelangsungan hidup man usia. Air bersih yang digunakan oleh manusia harus memenuhi syarat dari segi kualitas maupun kuantitas. Kualitas air dapat dilihat dari segi fisik, kimia, dan biologi. Pengolahan air minum secara khusus dilakukan oleh Perusahaan Air Minum (PAM). Aktifitas PDAM dalam pengel61aan air minum dimulai dari mengumpulkan, mengolah dan menjernihkan, sarnpai mendistribusikan air minum ke pelanggan.
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Judul: Kajian terhadap Efisiensi Pengolahan Air di Perusahaan Daerah Air Minum (PDAM) Tirta Pakuan Kota Bogor
Abstrak: Perusahaan Daerah Air Minum (PDAM) Tirta Pakuan Kota Bogor menyediakan air bersih bagi masyarakat kota Bogor. Sumber air baku yang diolah oleh PDAM Tirta Pakuan Kota Bogor berasal dari Sungai Cisadane dan tiga sumber mata air. Untuk memperbaiki kualitas air sungai Cisadane sebagai air minum, PDAM Tirta Pakuan Kota Bogor telah melakukan tahapan-tahapan pengolahan yang secara garis besar terdiri dari: koagulasi, flokulasi, sedimentasi, filtrasi, dan desinfeksi. Penelitian ini dilakukan pada bulan April – Agustus 2009 di Perusahaan Daerah Air Minum (PDAM) Tirta Pakuan Kota Bogor dan bertujuan untuk mengkaji tingkat efisiensi pengolahan air oleh perusahan yang bersangkutan. Air contoh pada penelitian ini diambil sebelum dan sesudah melewati berbagai unit-unit bak pengolahan air untuk selanjutnya dianalisa berbagai parameter kualitas fisika-kimianya. Data hasil analisis ini selanjutnya diolah secara kuantitatif maupun kualitatif, termasuk di dalamnya analisis terhadap beban pencemaran, analisis efisiensi pengolahan dan keseimbangan massa.
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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