Judul: Biologi dan Perkembangan Populasi Thrips palmi Karny (Thysanoptera: Thripidae) pada Tanaman Kentang
Abstrak: Penelitian ini bertujuan untuk biologi dan perkembangan populasi Thrips palmi Kamy (Thysarptera: Thriptdae) pada tanaman kentang. Guna mencapai tujuan tersebut telah dilakukan serangkaian percobaan untuk mengetahui: spesies-spesies Thrips dan komposisinya, biologi T. palmi, perkembangan populasi T. palmi dan faktor-faktor yang mempengaruhinya, survai dan inventarisasi musuh-musuh alami T. palmi, dan persebaran T. palmi pada tanaman kentang.
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Judul: Analisis Faktor Iklim Terhadap Serangan Thrips palmi
Tanaman Kentang di Kabupaten Majalengka.
Abstrak: Tinggi rendahnya produksi kentang dipengaruhi adanya faktor iklim dan serangan hama pada tanaman kentang. Hama yang sering menyerang tanaman kentang adalah hama Thrips palmi, hama ini tersebar luas di daerah subtropis terkhusus di wilayah Jawa dan Sumatera. Penelitian ini bertujuan untuk menganalisis dampak dari faktor iklim dan perubahan iklim terhadap kesesuaian iklim hama Thrips palmi di Kabupaten Majalengka. Metode yang digunakan dalam analisis ini yaitu metode analisis regresi parameter iklim terhadap luas serangan hama, fungsi compare location, compare years dan skenario iklim. Skenario iklim yang digunakan yaitu RCP 4.5 dan RCP 8.5 dengan model CCSM4 dan MIROC5. Hama Thrips palmi menunjukan sesuai untuk pertumbuhan dan perkembangannya di daerah Majalengka yang ditandai dengan nilai EI sebesar 57. Proyeksi iklim pada tahun 2050-an menunjukkan penurunan nilai EI menjadi 47 (RCP 4.5 MIROC5) dan 43 (RCP 4.5 CCSM4) serta 40 (RCP 8.5 MIROC5) dan 40 (RCP 8.5 CCSM4) yang menunjukan penurunan kesesuaian iklim terhadap pertumbuhan dan perkembangan hama Thrips palmi di Kabupaten Majalengka.
Keyword: climex, climate projections and pest suitability, EI

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