Judul: Toksisitas Insektisida Karbamat dan Pengaruhnya Terhadap Struktur Histologis dan Biometrik Insang, Usus, dan Hepatopancreas Ikan Mas (Cyprinus carpio L.).
Abstrak: Karbamat merupakan sumber pencemar yang sangat toksik bagi hewan non-target perairan meskipun insektisida bergolongan karbamat mudah terurai di alam baik pada media air maupun pada organisme. Salah satu organisme perairan yang berpeluang terkontaminasi adalah ikan mas (Cyprinus carpio L.). Efek yang diakibatkan oleh insektisida karbamat dapat bersifat akut atau kronik. Tujuan dari penelitian ini adalah menentukan nilai LC50-96 dari insektisida karbamat (Marshal 200 EC) pada ikan mas (Cyprinus carpio L.), mengkaji pengaruh insektisida karbamat berbahan aktif karbosulfan (Marshal 200 EC) terhadap tingkat kerusakan struktur histologis organ insang, usus dan hepatopancreas serta beberapa parameter biometrik ikan mas (Cyprinus carpio L.) (laju pertumbuhan bobot rata-rata hepatopancreas, empedu, usus, dan insang), dan menganalisa kandungan insektisida karbamat berbahan aktif karbosulfan (Marshal 200 EC) ikan mas (Cyprinus carpio L.) dan air media uji. Penelitian ini dilaksanakan pada bulan Desember 2017 hingga April 2018. Ikan mas (Cyprinus carpio L.) yang digunakan memiliki ukuran panjang badan 6-8 cm dengan bobot tubuh 5-12,9 g. Bahan toksikan yang digunakan ialah insektisida karbamat (Marshal 200 EC), wadah pemeliharaan berupa akuarium dengan ukuran 29,9x29,9,40,5 cm dengan volume air sebanyak 20 liter. Penelitian ini terdiri atas tiga tahapan yaitu uji pendahuluan, uji toksisitas akut, dan uji subkronik. Hasil penelitian menunjukkan bahwa nilai LC50-96 insektisida karbamat (Marshall 200 EC) sebesar 1,68 mgL-1. Kandungan residu insektisida karbamat dalam air berkisar 0,001-0,021 mgL-1, tubuh ikan mas 0,006-0,114 mgkg-1. Nilai Tolerable Weekly Intake (TWI) untuk orang dewasa (60 kg) sebesar 52,63-1.000 g daging minggu-1 dan untuk anak-anak (15 kg) sebesar 13,16-250 g daging minggu-1. Pemberian insektisida karbamat tidak memberikan pengaruh yang nyata (p>0,05) terhadap laju pertumbuhan bobot (SGR) rata-rata, gill index, intestine somatic index, dan hepatopancreas somatic index, namun memberikan pengaruh nyata (p<0,05) pada gall bladder index. Insektisida karbamat menyebabkan kerusakan pada organ insang (hyperplasia, hemoragi, nekrosis, kongesti, fusi, dan edema), usus (kongesti, hemoragi, inflamasi, nekrosis, dan proliferasi), dan hepatopancreas (kongesti, inflamasi, nekrosis, dan cloudy swelling).
Keyword: biometrik, ikan mas, karbamat, preparat histologi

Judul: Pengaruh Insektisida Baycarb 500 EC terhadap Pertumbuhan Burayak Ikan Mas (Cyprinus carpio L.)
Abstrak: Penelitian ini dilakukan dari tanggal 13 Juli sampai, dengan 1 September 1987 di Balai Penelitian Perikanan Air Tawar, Bogor. Tujuan penelitian adalah untuk mengetahui : (1) pengamh akut dan bioaktivitas insektisida Baycarb 500 EC terhaaap burayak ikan Mas, (2) pengamh beberapa ambang lconsentrasi insektisida Baycarb 500 EC yang dianjurkan bagi pengendalian hama Wereng Coklat (Nilaparvata lugens), terhadap laju kematian, laju pertwnbuhan dan produksi burayak ikan Mas, dan (3) nilai Maximum Acceptable Toxicant Concentration (MATC) dan Application Factor (AF). Hewan uji adalah burayak ikan Mas dengan ukuran panjang 1 - 3 cm. Burayak ikan Mas diperoleh dari peternakan PI Akuakultura Nasional, Desa Cibening, Kabupaten Bogor. Bahan uji yang digunakan adalah insektisida Baycarb 500 EC dengan bahan aktif BPMC (2-(1-methyl propyl) phenyl methyl carbamate. Penelitian ini diran~ang menurut pola rancangan acak lengkap. Konsentrasi uji adalah kontrol, 1 ppm (dosis aplikasi di sawah.), 4 ppm dan 8 ppm.
Keyword: 

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