Judul: Perubahan Karbohidrat Umbi Uwi (Dioscorea alata L) selama Penyimpanan
Abstrak: Tujuan dari penelitian ini ialah untuir mengecahui sifat - sifat umbi uwi dan perubahannya selama penyimpanan sehingga dapat memberikan informasi yang dapat dipergunakan bagi pemanfaatan dan pengembangan potensi penggunaan umbi uwi . Paraaeter yang diamati dalam penelitian ini meliputi morfologi umbi uwi, komposisi kimia, ekstraksi pati dan perubahan fisik dan kimia selama penyimpanan.
Keyword: 

Judul: Perubahan Sifat-Sifat Fisik dan Kimiawi Umbi Garut (Maranta arundinacea L.) Selama Penyimpanan
Abstrak: Tujuan penelitian ini adalah mempelajari arah perubahan sifat-sifat fisik dan kimiawi umbi garut segar dan kering selama penyimpanan. Pengamatan secara fisik terhadap umbi garut meliputi panjang, diameter dan berat umbi. Komposisi kimia umbi garut ditentukan dengan analisa kimia; meliputi kadar air pati, protein, lemak, serat, abu, total padatan terlarut, dan gula. Pengamatan perubahan fisik umbi garut selama penyimpanan dilakukan secara organoleptik; perubahan kimiawinya dilakukan dengan analisa kimia. Pengamatan secara mikroskopik dilakukan untuk mengetahui anatomi, histologi, dan bentuk granula pati garut. Tenunan umbi garut terdiri dari sel-sel pembentuk jaringan epidermis, hipodermis, pembuluh angkut, korteks dan empulur. Granula pati terdapat dalam sel-sel parenkim; bentuk umumnya adalah oval dan berukuran 6 - 27 mikron. Komposisi kimia umbi garut berumur 8 bulan adalah : 77.66 persen air, 1.80 persen protein, 0.02 persen lemak, 1.44 persen serat, 1.27 persen abu, 14.01 persen pati dan 3.5 sampai 3.8 persen total padatan terlarut serta 2.87 persen gula. Perubahan fisik umbi garut ditandai dengan perubahan warna sisik tidak lama setelah panen; penurunan bobot umbi secara drastis pada awal penyimpanan (0 sampai 10 hari penyimpanan); pertumbuhan mikroba dan kebusukan setelah umbi disimpan selama 4 hari, terutama pada umbi yang tidak utuh (luka, memar, patah); perubahan warna bagian kulit umbi setelah umbi disimpan selama 1 minggu; serta perubahan kekerutan kulit umbi yang tampak nyata setelah umbi disimpan selama 4 minggu. Perubahan kimiawi umbi garut terjadi sejalan dengan kejadian perubahan fisiknya. Pada minggu pertama penyim- panan, terjadi penurunan kadar air dari 77.66 persen sam- pai 77.18 persen; penurunan kadar pati dari 62.71 persen sampai 60.18 persen (basis kering); kenaikan kadar total padatan terlarut dari 17.10 sampai 18.06 persen (basis kering); penurunan kadar gula pereduksi dari 2.33 persen sampai 2.04 (basis kering); kenaikan kadar total gula da- ri 8.81 persen sampai 9.01 persen (basis kering); penu- runan kadar amilosa dari 12.98 persen 11.07 persen (ba- sis kering); penurunan kadar amilopektin dari 49.73 per- sen sampai 49.11 persen (basis kering)…dst
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