Judul: Uji Performansi Pengabut Tipe AU3000 Pada Pesawat Terbang Untuk Penyemprotan Zat Pemacu Kemasakan (ZPK) Tebu
Abstrak: Di perkebunan tebu milik PT. Gula Putih Mataram, Zat Pemacu Kemasakan diberikan dengan menggunakan pesawat terbang model PC-6 Pilatus Porter, dengan peralatan semprot volume ultra rendah (Ultra Low Volume) dan tipe pengabutnya adalah Micronair Compact Rotary Atomizer AU 3000. Pada penelitian sebelumnya diketahui bahwa pola sebaran droplet yang terjadi pada penyemprotan dengan menggunakan pesawat terbang PC-6 Pilatus Porter ini menunjukkan bahwa timbunan droplet banyak terdapat pada bagian bawab badan (pusat) pesawat, sedangkan pada daerah ujung sayap pesawat jumlah dropletnya lebih sedikit.
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Judul: Mempelajari pola sebaran dan ukuran butiran semprot dari penyemprot volume ultra rendah (Ulv sprayer) untuk pesawat terbang ringan
Abstrak: Masalah pengendalian hama serangga dan penyakit tanaman menyebabkan sebagian besar petani dan perkebunan merasa perlu untuk menambahkan dalam alat usaha taninya mesin-mesin untuk pemberian pestisida. Pemakaian pesawat terbang untuk memberi dan menyebarkan bahan semprotan di Amerika Serikat telah menjadi salah satu metode yang paling populer dan ekonomis dalam pemberian pestisida pada tanaman budidaya (Smith dan Wilkes, 1990). IPB bekerja sama dengan FASI (Federasi Aerosport Seluruh Indonesia) cabang Swayasa telah mampu mengembangkan pesawat terbang ringan jenis Minimax tipe Vmax 1550. Salah satu fungsi pesawat terbang ringan ini adalah untuk kegiatan pengendalian hama dan penyakit. Pesawat terbang ringan tersebut merniliki keterbatasan dalam kekuatan membawa beban. Oleh karena itu diperlukan adanya perangkat alat penyemprot yang dapat menggunakan bahan semprot dengan jumlah sedikit untuk setiap luasan penyemprotan dan mampu memenuhi fungsi utamanya. Fungsi utama suatu alat penyemprot adalah memecah cairan menjadi butiran-butiran dengan ukuran yang efektif, mendistribusikan secara merata dan mengatur banyaknya pemberian bahan semprot (Smith dan Wilkes, 1990). ...
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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