Judul: Pengujian Tetrazolium Dan Respirasi Benih Koro Pedang (Canavalia Ensiformis)
Abstrak: Koro pedang saat ini dikembangkan sebagai komoditas substitusi kedelai karena kandungan proteinnya yang cukup tinggi. Tujuan penelitian ini adalah untuk menguji viabilitas benih koro pedang dengan pengujian tetrazolium dan pengujian respirasi benih. Penelitian ini menggunakan tiga lot benih koro pedang yang berbeda yaitu lot benih A (dipanen bulan Maret 2014 di Bojong Bogor, disimpan dalam ruang kamar), lot benih B (dipanen bulan November 2013 di Ciherang Bogor, disimpan dalam ruang ber-AC), dan lot benih C (dipanen bulan September 2012 di Leuwikopo Bogor, disimpan dalam ruang ber-AC). Penelitian ini terdiri dari dua percobaan. Percobaan 1 ialah pengujian tetrazolium. Percobaan 2 ialah penguijian respirasi benih. Masing-masing percobaan menggunakan rancangan acak lengkap dengan pengusangan cepat secara fisik sebagai faktornya, yang terdiri atas 0, 8, 12, 16, dan 20 jam. Hasil percobaan 1 menunjukkan bahwa pola topografi pewarnaan tetrazolium benih koro pedang belum bisa digunakan untuk mengevaluasi mutu fisiologis benih koro pedang. Hasil percobaan 2 menunjukkan bahwa metode pengujian respirasi benih dengan cosmotector belum bisa digunakan untuk mengevaluasi mutu fisiologis benih koro pedang.
Keyword: pengujian respirasi benih, pengujian tetrazolium, viabilitas benih, vigor benih

Judul: Efektivitas Pupuk Boron dan Mikoseedcookies® Terhadap Mutu Fisiologis Benih Koro Pedang
Abstrak: Koro pedang adalah tanaman bernilai ekonomi tinggi yang dapat ditunjang budidayanya melalui pemupukan. Penelitian ini bertujuan mengevaluasi mutu fisiologis dari benih kacang koro pedang yang merupakan produk panen dari tanaman induk hasil pemberian kombinasi perlakuan pupuk boron dan Mikoseedcookies®. Rancangan penelitian yang digunakan adalah (RAL) faktorial yang terdiri atas 2 faktor dan 4 ulangan. Faktor pertama adalah dosis pupuk boron: P1 = 0 mg/L, P2 = 23 mg/L, P3 = 46 mg/L, P4 = 69 mg/L. Faktor kedua adalah diameter Miko-seedcookies: M1 = 4 cm, M2 = 5 cm, M3 = 6 cm. Peubah yang diukur meliputi potensi tumbuh maksimum (PTM), daya berkecambah (DB), kecepatan tumbuh (KCT), keserempakan tumbuh (KST), dan indeks vigor (IV). Data yang diperoleh dianalisis menggunakan ANOVA dan apabila data berbeda nyata diuji lanjut menggunakan uji Tukey. Hasil penelitian menunjukkan bahwa kombinasi perlakuan pada benih berpengaruh nyata (P<0,05) terhadap vigor benih hasil panen 1. Secara keseluruhan perlakuan yang diberikan terhadap tanaman induk menghasilkan mutu fisiologis benih sesuai kriteria pedoman International Seed Testing Association. Kata-kata kunci: benih kacang koro, boron, Miko-seedcookies®, viabilitas, vigor
Keyword: Boron, Viabilitas, vigor, Benih kacang koro, miko-seedcookies

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