Judul: Study of mealiness phenomena in apple (MAlus sylvestris Mill.) cultivar "Rome Beauty"
Abstrak: Masir adalah sifat organoleptik/inderawi yang hanya dapat dikenali dengan pengamatan menggunakan cicip, rabaan serta seringkali dapat terlihat oleh mata. Istilah masir mempunyai cakupan yang cukup luas, dan dinyatakan untuk banyak jenis komoditas seperti, salak, ubi jalar, singkong, kentang, apel, sawo dan bahkan untuk beberapa jenis makanan lain yang menyimpang seperti es krim, susu gula manis dan madu. Namun informasi tertulis mengenai kemasfran banyak diperoleh hanya dari umbi kentang. Informasi teknis tentang kemasiran buah-buahan termasuk apel, masih sangat terbatas, padahal kemasiran memegang peran penting dalam penanganan, perdagangan dan pengolahan buah-buahan dan umbi-umbian.
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Judul: Pengelompokan buah apel (Malus sylvestris Mill) varietas manalagi berdasarkan kememaran dengan sistem NIR (Near Infrared Reflectance)
Abstrak: Untuk memperoleh buah apel yang segar dan bermutu tinggi, buah apel harus dipilih dan ditangani secara hati-hati. Penanganan yang kurang hati-hati pada proses pemanenan maupun pasca panen dapat menyebabkan terjadinya kerusakan pada buah, sehingga dapat menurunkan mutu dan mengurangi pendapatan para petani maupun produsen buah. Salah satu kerusakan akibat penanganan yang kurang hati-hati pada buah apel adalah memar. Kememaran sulit untuk diketahui, karena tidak segera kelihatan dan baru dapat diketahui setelah proses pelunakan dan munculnya warna coklat pada jaringan buah yang terpengaruh. Karena itu dibutuhkan suatu sistem yang dapat mendeteksi secara dini kememaran pada buah sebelum buah tersebut dipasarkan dan sistem Near Infrared Reflectance (NIR) dianggap mampu untuk maksud tersebut, karena sifat penyerapan cahaya yang besar oleh molekul air yang terdapat pada buah. Tujuan dari penelitian ini adalah menentukan panjang gelombang pada NIR untuk mendeteksi kememaran buah apel Manalagi dan Pengelompokan buah apel Manalagi yang memar dengan yang tidak memar...
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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