Judul: Korelasi kanonik antara sifat fisiko-kimia dengan mutu beras pada tiga kota besar di Indonesia
Abstrak: Penelitian ini bertujuan untuk menyelidiki hubungan kompleks antara peubah-peubah sifat fisiko-kimia beras dengan peubah-peubah mutunya, untuk varietas-varietas yang terdapat pada tiga kota, yaitu Medan, Jakarta dan Ujung Pandang. Data diperoleh dari hasil survei beras pada kota Medan, Jakarta dan Ujung Pandang. Survei tersebut dilakukan oleh Balai Penelitian Tanaman Pangan, Sukamandi, pada musim kemarau 1987, selama 3-7 hari. Dari hasil analisis korelasi kanonik diperoleh tiga peubah kanonik pertama yang mempunyai nilai cukup berarti secara statistik. Berdasarkan faktor loadingnya, dapat ditunjukkan bahwa sifat fisiko-kimia beras, yaitu kandungan amilosa dan suhu gelatinasi (uji alkali) dinyatakan sebagai penciri mutu rasa, yaitu kekerasan, kelekatan dan kepulenan. Dan sifat derajat putih, kejernihan dan pengapuran serta derajat sosoh dinyatakan sebagai penciri mutu fisik beras, yaitu bau, % campuran butiran yang tidak diinginkan, warna dan kilap. Kemudian sifat derajat putih dan densitas dinyatakan sebagai penciri mutu fisik juga, yaitu warna dan kekilapan.
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Judul: Pengenalan Butiran Beras Mengapur dan Kuning/Rusak dengan Menggunakan Pengolahan Citra dan Jaringan Saraf Tiruan
Abstrak: Salah satu masalah dalam dunia perberasan nasional adalah penentuan mutu beras. Standar mutu yang berlaku di pasar umumnya didasarkan pada karakteristik fisik butir beras dan penampakan biji beras yang mempunyai hubungan dengan preferensi dan perbedaan harga yang jelas. Parameter yang digunakan untuk menentukan mutu beras tersebut yaitu kadar air, derajat sosoh, butir utuh, butir patah, butir menir, butir hijau/kapur, butir kuning/rusak, benda asing, butir merah dan butir gabah. Dengan mengetahui kandungan butir mengapur dan kuning/rusak yang terdapat dalam suatu sampel beras maka dapat menentukan mutu beras secara fisik dan menggolongkannya ke dalam tingkat kelas tertentu.
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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