Judul: Dinamika Kandungan Bahan Organik dan Status Mutu Air Danau Garden House, Pantai Indak Kapuk, Jakarta Utara
Abstrak: Danau Garden House merupakan salah satu danau hias yang terdapat di kawasan Pantai Indah Kapuk, Jakarta Utara. Letak Danau Garden House yang dikelilingi perumahan berpotensi menerima limpasan limbah domestik yang cukup tinggi yang akan mempengaruhi kualitas air perairan tersebut. Penelitian ini bertujuan untuk menganalisis dinamika kandungan bahan organik dan status mutu air pada musim yang berbeda. Penelitian ini dilaksanakan pada bulan Juli 2017 hingga bulan Juni 2018. Analisis data terdiri atas dinamika kandungan bahan organik dan status mutu air. Status mutu air dianalisis dengan indeks Canadian Council of Minister of the Environment (CCME). Hasil penelitian menunjukkan adanya perbedaan dinamika kandungan bahan organik pada musim yang berbeda. Terdapat lima parameter kualitas air yang tidak memenuhi baku mutu kelas II menurut PPRI No. 82 Tahun 2001. Parameter tersebut ialah BOD, COD, P Total, dan hidrogen sulfida. Amonia dan ortofosfat termasuk parameter yang tidak memenuhi baku mutu untuk biota laut menurut Kepmen LH No. 51 Tahun 2004. Status mutu air berdasarkan indeks CCME menunjukkan kondisi perairan sangat buruk (poor) baik pada musim kemarau maupun musim hujan.
Keyword: bahan organik, indeks CCME, limbah, status mutu air

Judul: Status Kualitas Air Danau Garden House, Pantai Indah Kapuk, Jakarta Utara
Abstrak: Kualitas air di perairan Danau Garden House sangat dipengaruhi oleh kegiatan yang berada disekitar perairan, yaitu aktivitas perumahan. Penelitian ini bertujuan untuk menentukan status kualitas air di danau. Pengambilan data kualitas air dilakukan setiap bulan dari Juni 2015 sampai Juni 2016. Status kualitas air perairan ditentukan dengan menggunakan Indeks Pencemaran menurut Nemerow. Terdapat perbedaan pengelompokan stasiun pengamatan berdasarkan Indeks Canberra di musim kemarau dan musim hujan. Pada musim kemarau, tingkat pencemaran perairan Danau Garden House lebih tinggi dibandingkan dengan musim hujan. Tercemarnya danau Garden House dikarenakan tingginya bahan organik dari kegiatan domestik. Parameter kualitas air yang tidak sesuai dengan baku mutu adalah TSS, DO, BOD5, COD, total fosfat, amonia, dan nitrit.
Keyword: Indeks Pencemaran, kualitas air, aktivitas perumahan

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