Judul: Adoption Integrated Pest Management (IPM) in Koto Kenagarian Koto Tinggi, Agam District, West Sumatera Province
Abstrak: Pengendalian hama terpadu (PHT) merupakan upaya yang berencana dan terkoordinasi untuk pembangunan pertanian yang berkelanjutan dan berwawasan lingkungan agar hama penyakit tetap diambang batas dan produksi tetap meningkat. Adapun penelitian ini bertujuan: (1) menganalisis tingkat penerapan PHT oleh petani dan (2) menganalisis faktor-faktor yang berpengaruh terhadap PHT., Integrated pest Management (IPM) is aimed to promote sustainable agricultural development based on benign and environment in order to increace production and protect environment. The aim of this study: (1) analyze the adoption of IPM by farmers and (2) analyze the factors that influence the IPM adoption.
Keyword: role extension, adoption, characteristic of innovation

Judul: Pengetahuan, Sikap, dan Tindakan Petani dalam Pengendalian Hama Terpadu Tanaman Padi di Kecamatan Malingping, Kabupaten Lebak, dan Kecamatan Petir, Kabupaten Serang.
Abstrak: As the main food crop, rice plays a pivotal role on supporting physiological needs of Indonesian society as well as has high economic value. In order to increase rice yield, farmers have several obstacles to confront such as decreasing land productivity, climate change and outbreak of pest and disease. The problem of pest and diseases inflict a financial loss of farmers, therefore it needs appropriate strategyto control it in order to minimizing the damage. Integrated pest management (IPM) is a comprehensive approach to control pest and disease that had been stated in government policy and environmental friendly. Unfortunately, although the government had socialized to the farmers, the implantation of IPM is still rare. The objective of this research is to study the level of knowledge, attitude, problems and action of farmers on cultivation management of rice including the strategy in controlling pest and disease. The research was conducted in Subdistrict of Malingping (Lebak Regency) and Petir (Serang Regency), Banten Province from May to June 2012. The data was collected by direct interview to the farmers using questionnaire. The result showed that the knowledge of farmers on rice cultivation management was based on heredity knowledge from their ancestor as well as developed from their own experience. Generally, the farmers in Malingping and Petir do not familiar with IPM, this is based on information from the farmers that they did not receive education about IPM from Indonesian government. In fact, the farmer is aware about the important of using healthy seeds, monitoring pest and disease, utilizing natural enemies and using pesticide wisely, that those are important aspect on IPM. In the management of cultivation, the farmers still depend on synthetic pesticide to control pest and disease due to practically simple to apply. Related to climate problem, the farmers tend to defenseless and do nothing without preventive or adaptive approach such as plant rotation that recommended by government.
Keyword: 

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