Judul: Makrozoobenthos sebagai Bioindikator Kualitas Air Sungai Citarum Hulu (Sub DAS Cikeruh, Citarik, dan Cirasea)
Abstrak: Penggunaan lahan yang beragam pada DAS Citarum Hulu menghasilkan beban pencemar yang dapat menurunkan kualitas air. Hasil analisis indeks STORET berdasarkan parameter fisik-kimia menunjukkan kualitas perairan Sungai Cikeruh, Citarik, dan Cirasea mengalami cemar sedang hingga cemar berat. Identifikasi kualitas air juga dilakukan dengan menggunaakan makrozoobenthos sebagai biota sungai yang hidupnya menetap pada dasar sungai. Kondisi kualitas air berdasarkan Indeks Famili Biotik (HBI) makrozoobenthos menunjukkan bahwa kualitas air Sungai Cikeruh tergolong buruk, dan kualitas air Sungai Citarik dan Sungai Cirasea tergolong cukup, sedangkan identifikasi kondisi air sungai berdasarkan Indeks Keanekaragaman jenis makrozoobenthos menunjukkan bahwa Sungai Cikeruh, Citarik, dan Cirasea mengalami pencemaran berat. Kesesuaian status mutu air menggunakan makrozoobenthos dengan parameter fisik-kimia menunjukkan bahwa makrozoobentos dapat digunakan sebagai bioindikator untuk memantau kualitas air sungai.
Keyword: bioindicator, Citarum, macrozoobenthos

Judul: Makrozoobenthos Sebagai Bioindikator Kualitas Air Sungai Di Sub Das Ciliwung Hulu
Abstrak: Makrozoobenthos Memiliki Sifat Yang Relatif Menetap Dan Gerakan Yang Sangat Terbatas Yang Akan Terkena Dampak Langsung Dalam Hal Perubahan Kualitas Air, Karena Itu Makrozoobenthos Sering Digunakan Sebagai Bioindikator Kualitas Air. Penelitian Ini Dilakukan Pada Bulan Maret Sampai Juni 2015 Di Sub Das Ciseuseupan, Cisukabirus, Dan Cisuren Dengan Tujuan Menentukan Tingkat Kualitas Air Dan Pengaruh Penggunaan Lahan Terhadap Kualitas Air Dengan Menggunakan Makrozoobenthos. Indeks Biologis Yang Digunakan Untuk Menganalisis Makrozoobenthos Yaitu Fbi Dan Signal 2. Nilai Fbi Yang Diperoleh Di Sub Das Ciseuseupan Adalah 5.02 Dengan Kriteria Sedang, Di Sub Das Cisukabirus Adalah 3.96 Dengan Kriteria Sangat Baik, Dan Di Sub Das Cisuren Adalah 4.37 Dengan Kriteria Baik. Luas Penggunaan Lahan Hutan Yang Lebih Besar Daripada Penggunaan Lahan Permukiman Merupakan Faktor Utama Tingginya Kualitas Air Di Sub Das Cisukabirus.
Keyword: Kualitas Air, Makrozoobenthos, Penggunaan Lahan

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