Judul: Imotilisasi Ikan Mas (Cyprinus carpio) Dengan Ekstrak Ketumbar (Coriandrum sativum) Pada Transportasi Kering.
Abstrak: Ketumbar (Coriandrum sativum) merupakan tumbuhan asli Indonesia. Ketumbar mengandung senyawa aromatik yaitu volatil, hidrokarbon beroksigen, dan linaool yang bersifat menimbulkan daya halusinasi apabila dilakukan dengan konsentrasi tertentu. Bagian dari ketumbar yang sangat potensial untuk kepentingan penelitian pemingsanan ikan adalah biji ketumbar. Tujuan penelitian ini adalah untuk menentukan konsentrasi optimal ketumbar dalam pemingsanan dan kelulusan hidup ikan mas (Cyprinus carpio). Konsentrasi ekstrak yang digunakan yaitu 1%, 2%, dan 3%. Konsentrasi terbaik yang diperoleh adalah 2% dengan waktu waktu pingsan 1 menit 48 detik dan waktu sadar 1 menit 33 detik. Tingkat kelulusan hidup ikan mas pada jam ke-4 yaitu 75%. Hasil terbaik setelah simulasi transportasi yaitu simulasi dengan lama waktu waktu 180 menit yang memliki tingkat kelangsungan hidup 100%
Keyword: Anesthesia, aromatic, coriander extract

Judul: Teknik Imotilisasi Ikan Mas (Cyprinus carpio) Menggunakan Ekstrak Daun Kecubung (Datura metel L)
Abstrak: Datura metel L is a species of flora which destributed scattered around Indonesia, especially in dry areas, which contained anesthetic substances. The leaves contain alkaloid and saponion. The main objective of this research was to determine the concentration of Datura metel L leaves extract as an anesthetic for common carp fish and its survival rate. The treatment of this research is the differences between Datura metel L leaves from 1 through 5 and 6 through 10 with concentration differences of 15%, 20%, and 25%. The best Datura metel L leaves extract is on 1st through 5th leaf with the concentration of 20%, with 61 minutes of onset time with a life expectancy of 87%, with post anaesthesia water quality pH 5,3, DO 2,9 ppm, and TAN 3,4 mg/L. Leaf 6 through 10 performed with the longest amount of time, which is 116 minutes with the life expectancy of 97%.
Keyword: water quality, Datura metel L, anesthetic, alcaloid

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