Judul: Pengaruh wadah kemasan dan bahan pengisi terhadap mutu buah pisang raja bulu(Musa "AAB" raja bulu
Abstrak: Penelitian ini bertujuan untuk mempelajari pengaruh wadah kemasan, bahan pengisi serta interaksi antara wadah kemasan dan bahan pengisi terhadap mutu dan daya simpan buah pisang Raja Bulu: Buah pisang Raja Bulu diperoleh dari kebun petani yang terletak di daerah Ciapus Bogor, dengan bantuan seorang pedagang pengumpul pisang. Pengemasan buah dilakukan di rumah pedagang, penyimpanan buah di Laboratorium Produksi Tanaman dan analisis mutu buah dilaksanakan di Laboratorium Research Group on Crop Improvement (RGCI), Departemen Agronomi dan Hortikultura, Fakultas Pertanian, Institut Pertanian Bogor yang terletak di Darmaga. Penelitian dilaksanakan pada bulan Januari 2006 sampai dengan Maret 2006...
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Judul: Pengaruh perlakuan air hangat dan kemasan plastik terhadap  kondisipisang Musa paradisiaca L.varietas raja bulu pada dua suhu simpan
Abstrak: Penelitian ini dilakukan untuk mengetahui pengaruh perlakuan air hangat, kemasan plastik dan penyerap etilen (KMnO4) terhadap kondisi buah pisang (Musa paradisiaca L.) varietas Raja Bulu pada dua kondisi suhu simpan, yang dilaksanakan pada periode Desember 2003-Januari 2004 di Laboratorium Pilot Plant PAU Pangan dan Gizi serta Laboratorium Pengemasan, Departemen Teknologi Industri Pertanian, Fakultas Teknologi Pertanian. Institut Pertanian Bogor. Rancangan yang digunakan pada penelitian ini adalah Rancangan Acak Lengkap (RAL) untuk setiap suhu simpan. Perlakuan yang digunakan adalah perlakuan pra-kemas (perendaman air hangat), faktor kemasan (jenis plastik dan penyerap etilen) yang dikombinasikan menjadi 8 jenis perlakuan, yaitu: 1). Kontrol: Tanpa kemasan, tanpa perendaman air hangat (50 °C selama 5 menit), dan tanpa pemberian KMnO4. 2). AH: Perendaman air hangat tanpa kemasan. 3). PE: Kemasan plastik polietilen. 4). PE+KMnO4: Kemasan plastik polietilen dan KMnO4. 5). AH, PE: Air hangat, kemasan plastik polietilen. 5). PVC: Kemasan plastik polivinilklorida. 6). PVC+KMnO4: Kemasan plastik polivinilklorida dan KMnO4 dan 8). AH, PVC: Air hangat, kemasan plastik polivinilklorida. Setiap jenis perlakuan dilakukan dalam tiga ulangan secara tersarang sehingga diperoleh 8x3-24 satuan unit percobaan. Untuk setiap unit percobaan digunakan setengah sisir pisang. Masing-masing perangkat satuan percobaan disimpan di ruangan yang berbeda yaitu seperangkat disimpan dalam cool storage/suhu dingin (13-15 °C) dan seperangkat lagi disimpan pada suhu kamar (26-27 °C). Data hasil pengamatan dianalisis secara statistik dengan menggunakan uji F; bila berbeda nyata dilanjutkan dengan Uji Wilayah Berganda Duncan (DMRT) pada taraf 5%. Sedangkan untuk setiap perlakuan yang sama pada suhu simpan yang berbeda dilakukan uji beda nilai tengah dengan uji t (t-test) pada taraf 1% dan 5%. ...
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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