Judul: Fluktuasi Oksigen Terlarut, Suhu, dan pH Air Selama 3x24 Jam, Periode Juli 2015-Januari 2016 di Cengkareng Drain, Pantai Indah Kapuk, Jakarta Utara
Abstrak: Muara Cengkareng Drain merupakan lokasi intake air untuk air baku air minum. Permasalahan yang muncul diduga pasang surut memberikan pengaruh terhadap kualitas air Muara Cengkareng Drain. Penelitian ini bertujuan untuk mendeskripsikan fluktuasi dan keterkaitan antara pasang surut dengan nilai DO, suhu, dan pH. Penelitian dilakukan dengan metode deskriptif dan uji hipotesis. Pengamatan dilakukan setiap bulan selama enam periode (Juli 2015-Januari 2016), setiap periode dalam waktu pengamatan 3x24 jam. Berdasarkan hasil pengamatan, fluktuasi DO dan suhu tergolong rendah, dan suhu tergolong tinggi. Hasil analisis data dan uji hipotesis menunjukkan pasang surut tidak memiliki keterkaitan terhadap DO, suhu,dan pH terkecuali pada pH periode September-Oktober 2015. Kisaran nilai DO, salinitas, dan kekeruhan air menunjukkan nilai yang melebihi ketentuan baku mutu (Kelas I) dan perairan muara Cengkareng Drain dapat dinyatakan tidak layak dijadikan sebagai air baku air minum sesuai dengan PP RI Nomor 82 tahun 2001.
Keyword: Cengkareng Drain, oksigen terlarut, suhu, pH. pasang surut

Judul: Kualitas Air Cengkareng Drain, Pantai Indah Kapuk, Jakarta Utara Dan Kaitannya Dengan Pasang Surut
Abstrak: Cengkareng Drain merupakan salah satu wilayah yang masih dipengaruhi oleh pasang surut. Perairan Cengkareng Drain dijadikan sebagai titik pengamatan untuk mengkaji keterkaitan antara karakteristik kualitas air dengan pasang surut. Penelitian ini dilakukan satu bulan sekali selama empat bulan pemantauan (Juli-Oktober 2015). Pengambilan contoh air dilakukan pada saat pasang dan surut tiap bulan pemantauan. Indeks Pencemaran menunjukkan bahwa tingkat pencemaran di Cengkareng Drain tergolong tercemar sedang, dengan skor antara 7,7-8,6. Berdasarkan hasil uji t dan analisis similaritas, karakteristik kualitas air pada saat pasang tidak berbeda nyata dengan karakteristik kualitas air pada saat surut. Selama penelitian, nilai total tertinggi pada matrik pembobotan menunjukkan bahwa waktu terbaik pengambilan bahan baku air minum adalah saat surut pada bulan ke-2 pemantauan (Agustus).
Keyword: Cengkareng Drain, kualitas air, pasang surut

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