Judul: Karakteristik Pengeringan Beku Sari Temulawak (Curcuma xanthorrhiza Roxb.)
Abstrak: In this study, the process of freezing is done by using media temperature stratified. It aimed to see the influence of the freezing system with media temperature stratified to the characteristic and porosity of freeze dried curcuma extract products. The quality of the freeze dried curcuma extract was analyzed from the value of the level of curcumin and generated pore size. The results analyzed visually showed that the pore size to scenario 2 (Tma = -15ºC, Tmf = -20ºC, Tmb = -20ºC) was larger then scenario 1 (Tma = -15ºC, Tmf = -15ºC, Tmb = -20ºC) and scenario 1 was larger than the pore size in scenario 3 (Tma = -20ºC, Tmf = -20ºC, Tmb = -20ºC). The difference of pore size was affected by the moisture content of the material and freezing rate, although the freezing rate had no significant dependability because measuring is not sure. In addition, the influence of the freezing process does not show definite effect of the freeze drying characteristics. Content of curcumin that obtained after the freeze drying process already meet the standards, that is of 2.66%.
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Judul: Pengaruh Penyusutan Terhadap Karakteristik Pengeringan Lapisan Tipis Temu Putih (Curcuma zedoaria (Berg) Roscoe)
Abstrak: Proses pengeringan lapisan tipis temu putih dipengaruhi oleh faktor internal dan eksternal. Faktor internal diantaranya meliputi sifat termofisik bahan, sedangkan faktor eksternal adalah suhu, kelembaban udara dan kecepatan pengering. Semakin tinggi suhu dan kecepatan udara serta semakin rendah kelembaban udara, maka laju pengeringan semakin cepat dan menyebabkan proses penurunan kadar air serta penyusutan bahan semakin cepat. Penyusutan pada permukaan bahan menyebabkan pengerutan, keretakan dan pembengkokan serta case hardening. Hal ini dapat dapat diminimalkan dengan penurunan laju pengeringan, sehingga pengkerutan pada permukaan bahan berkurang. Perubahan bentuk dan ukuran yang terjadi selama pengeringan perlu diamati lebih lanjut, karena selama ini dalam berbagai model pengeringan penyusutan yang terjadi selalu diabaikan. Tujuan dari penelitian ini adalah untuk mempelajari penyusutan bahan pada proses pengeringan lapisan tipis temu putih dengan image processing dan menentukan pengaruh penyusutan temu putih terhadap karakteristik pengeringan. Untuk mengetahui seberapa besar penyusutan bahan yang terjadi selama proses pengeringan digunakan bantuan pengolah citra (image processing) dengan menggunakan web camera. Pengolahan citra merupakan proses mengolah pikselpiksel dalam citra digital untuk memperoleh citra dengan karakteristik tertentu. Dengan menggunakan sistem standar pengambilan citra berupa web camera, komputer (hardware dan software) semua parameter yang berhubungan dengan bentuk (area) dianalisa. Sehingga perubahan area pada bahan selama pengeringan berlangsung dengan interval waktu 8-13 jam akan diketahui. Bahan uji yang digunakan dalam penelitian ini adalah irisan temu putih yang berumur ±9 bulan dan diperoleh dari Kebun Petak Pamer Balai Penelitian Tanaman Obat dan Aromatik Cimanggu Bogor.
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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