Judul: Ketahanan Empat Kultivar Ubi Kayu terhadap Tetranychus kanzawai Kishida (Acari : Tetranychidae
Abstrak: Tungau merah (Tetranychus kanzawai Kishida) merupakan hama penting pada ubi kayu. Hama tersebut menyebabkan kehilangan hasil sebesar 95%. Penggunaan kultivar merupakan faktor yang mempengaruhi kehilangan hasil. Kultivar ubi kayu yang tahan terhadap tungau merah dapat digunakan sebagai salah satu alternatif pengendalian. Penelitian ini bertujuan mengetahui ketahanan kultivar Manggu, Roti, Jimbul, dan Mentega terhadap T. kanzawai. Penelitian di rumah kaca dilakukan untuk mengetahui intensitas kerusakan pada kultivar Mannggu, Roti, Mentega, dan Jimbul. Pengamatan biologi T. kanzawai dilakukan di laboratorium. Hasil pengamatan menunjukkan bahwa setiap kultivar menunjukkan ketahanan terhadap T. kanzawai yang berbeda-beda. Kultivar Manggu menunjukkan intensitas kerusakan paling rendah dan kultivar Mentega menunjukkan intensitas kerusakan paling tinggi. Pada kultivar Manggu T. kanzawai menunjukkan waktu perkembangan yang lebih panjang dan memiliki keperidian yang lebih rendah.
Keyword: intensitas kerusakan, kultivar, keperidian, ketahanan, siklus hidup, Tetranychus kanzawai.

Judul: . The Strategy of Using a Predatory Mite, Neoseiulus  longispinosus Evans (Phytoseiidae), to Control Tetranychus kanzawai Kishida (Tetranychidae) on Cassava Plant
Abstrak: Tetranychus kanzawai Kishida (Acari: Tetranychidae) merupakan hama penting yang banyak menyebabkan kerugian pada beberapa jenis tanaman di Indonesia. Pengendalian tungau ini umumnya dilakukan secara kimiawi dengan akarisida. Penggunaan akarisida yang intensif dan tidak bijaksana dapat memicu munculnya dampak negatif. Metode alternatif yang lebih aman untuk mengendalikan hama ini perlu terus dikembangkan, salah satunya dengan memanfaatkan tungau predator sebagai agen pengendalian hayati. Salah satu musuh alami yang penting bagi T. kanzawai adalah tungau predator famili Phytoseiidae, di antaranya Neoseiulus dan Phytoseiulus. Neoseiulus longispinosus Evans (Acari: Phytoseiidae) merupakan tungau predator tipe II atau predator generalis yang memiliki preferensi terhadap tungau Tetranychidae. Penelitian ini bertujuan menentukan rasio dan waktu pelepasan N. longispinosus yang paling efektif dalam mengendalikan T. kanzawai pada tanaman ubi kayu. Percobaan menggunakan rancangan strip plot dengan tiga ulangan. Rasio pelepasan predator:mangsa adalah faktor A dengan empat taraf yaitu rasio pelepasan predator:mangsa 0 : 5, 1 : 5, 2 : 5, dan 3 : 5. Waktu pelepasan predator adalah faktor B dengan tiga taraf, yaitu satu, dua, dan tiga minggu T. kanzawai diinfestasi. (tiga minggu setelah tanam (MST), 4 MST, dan 5 MST). Infestasi T. kanzawai dilakukan pada tanaman ubi kayu kultivar Mentega saat tanaman berumur 2 MST. Pengamatan pengaruh pelepasan predator N. longispinosus terhadap intensitas serangan dan populasi T. kanzawai dilakukan saat tanaman berumur 6 MST. Pelepasan predator N. longispinosus dapat menekan populasi dan intensitas serangan T. kanzawai pada tanaman ubi kayu. Rasio predator:mangsa (N. longispinosus: T. kanzawai) yang optimum untuk menekan populasi T. kanzawai adalah rasio 2:5 dan 3:5. Penekanan populasi T. kanzawai tertinggi terjadi pada perlakuan pelepasan predator satu minggu setelah infestasi tungau hama. Pelepasan N. longispinosus hanya mampu menurunkan intensitas serangan T. kanzawai pada tanaman ubi kayu paling tinggi sebesar 8,55%., Tetranychus kanzawai Kishida is an important pest that causes a lot of damage to several types of crops in Indonesia. The control of this mite is generally carried out chemically using acaricide. The intensive use of acaricide triggers many negative impacts. Alternative ways for the control this pest are needed, and one of which is by using predatory mites as biological control agents. Some important natural enemies of T. kanzawai are phytoseiid mites, including Neoseiulus and Phytoseiulus. Neoseiulus longispinosus Evans (Acari: Phytoseiidae) is a type II predator or generalist predator which has preference for tetranychid mites. This study was aimed to determine the most effective release ratio and time of N. longispinosus in controlling T. kanzawai in cassava plants. The experiment was carried out using a strip plot design with three replications. The predator release ratio to prey as the factor A consisting of four levels, namely 0:5, 1:5, 2:5, and 3:5 of predator:prey ratio. Predator release time as factor B with three levels, namely one, two, and three weeks after T. kanzawai release (three weeks after planting (WAP), 4 WAP, and 5 WAP). Infestation of T. kanzawai was carried out on cassava plant cultivar Mentega when the plants were 2 WAP. Observations on the effect of N. longispinosus release on the attack intensity and population of T. kanzawai were carried out at 6 WAP. The results in
Keyword: biological control, predatory mite, predator to prey ratio, spider mite

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