Judul: Tinjauan mikroskopik aktivitas sistem organ imun mencit yang diberi ekstrak buah merah (Pandanus conoideus Lam)
Abstrak: Penelitian ini bertujuan untuk mengetahui potensi ekstrak buah merah dalam mempengaruhi aktivitas sistem organ imun pada mencit betina dan mencit jantan. Digunakan 30 ekor mencit (15 ekor mencit jantan dan 15 ekor mencit betina) yang dibagi masing-masing menjadi 3 kelompok terdiri dari 5 ekor mencit, yaitu kelompok kontrol, tanpa perlakuan; kelompok preventif, pemberian ekstrak buah merah dengan dosis 1 x 0.1 ml/ekor/hari; kelompok kuratif, pemberian ekstrak buah merah dengan dosis 2 x 0.1 ml/ekor/hari. Setelah 4 minggu perlakuan, dilakukan pengambilan darah untuk dibuat sediaan ulas darah dan diambil organ imun mencit (timus, sumsum tulang, limfonodus dan limpa). Parameter yang diamati yaitu: perbandingan ketebalan korteks dan medula timus, perhitungan jumlah folikel limpa dan limfonodus, perhitungan jumlah megakariosit limpa dan sumsum tulang, diferensiasi sel-sel darah dari sumsum tulang dan sediaan ulas darah (eritrosit dan leukosit). Hasil penelitian menunjukkan bahwa pemberian ekstrak buah merah dosis preventif dan kuratif dapat meningkatkan aktivitas sistem organ imun mencit. Pemberian ekstrak buah merah dengan dosis kuratif menunjukkan aktivitas sistem organ imun mencit yang lebih baik dibanding dosis preventif. Respon mencit jantan terhadap pemberian ekstrak buah merah lebih baik dibandingkan mencit betina. Ekstrak buah merah yang diberikan pada mencit lebih berperan pada sistem imun spesifik dalam meningkatkan sel limfosit.
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Judul: Tinjauan mikroskopik aktivitas sistem organ imun mencit [Mus musculus] virgin coconut oil dan sari buah merah
Abstrak: Penelitian ini bertujuan untuk mengetahui potensi virgin coconut oil dan sari buah merah dalam mempengaruhi aktivitas organ imun mencit jantan dan mencit betina. Tiga puluh ekor mencit berumur 8-12 minggu yang terdiri dari 15 ekor mencit betina dan 15 ekor mencit jantan masing-masing dibagi menjadi 3 kelompok perlakuan. Kelompok I diberi air mineral, sebagai kontrol dengan dosis 1 x 0,2 ml/ekor/hari, kelompok II diberi virgin coconut oil dengan dosis 1 x 0,1 ml/ekor/hari dan kelompok III diberi sari buah merah dengan dosis 1 x 0,12 ml/ekor/hari. Setelah 2 bulan perlakuan, mencit dieutanasi dan dinekropsi. Organ imun mencit yaitu timus, limfonodus dan limpa diambil untuk dibuat preparate histopatologi menggunakan pewarnaan Hematoksilin Eosin (HE). Hasil pengamatan preparat histopatologi menunjukkan bahwa pemberian virgin coconut oil dan sari buah merah dapat meningkatkan aktivitas sistem organ imun mencit. Pemberian virgin coconut oil menunjukkan aktivitas sistem organ imun yang lebih baik dibanding sari buah merah. Respon mencit jantan terhadap pemberian virgin coconut oil dan sari buah merah lebih baik dibandingkan mencit betina…
Keyword: Mus musculus, Virgin coconut oil

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