Judul: Deteksi penyakit pada benih Eucalyptus alba Reinw
Abstrak: Pemeriksaan kesehatan Benih adalah suatu upaya untuk mencari keadaan yang optimum bagi pertumbuhan dan/atau bagi sporulasi patogen, sehingga patogen yang telah ada dalam benih dapat menampakkan diri dan mudah diidentifi- kasi. IPR Cara penyimpanan benih yang kurang tepat memberi peluang bagi beberapa jenis fungi yang terbawa benih baik di lapangan maupun selama penyimpanan, untuk tumbuh dan berkembang. Terdapat tiga hubungan antara benih dengan patogen yaitu : (a) patogen terbawa secara internal di dalam jaringan benih (b) patogen terbawa sebagai kontaminan pada permukaan benih dan (c) patogen secara terpisah terbawa bersama benih. Penelitian dilaksanakan di rumah kaca dan Laboratori- um Penyakit Hutan Pusat Penelitian dan Pengembangan Hutan dan Konservasi Alam Gunung Batu, Bogor. Penelitian ini bertujuan : 1. Mencari metode deteksi yang murah dan sederhana untuk fungi yang terbawa benih Eucalyptus alba 2. Untuk mengetahui jenis-jenis fungi yang terbawa benih E. alba. Deteksi fungi yang terbawa benih E. alba yang dipakai dalam penelitian ini adalah metode agar, metode kertas saring, metode campuran batubata dengan tanah topsoil (1: 2) dan metode campuran pasir dengan tanah topsoil (1: 2). Pada metode agar dan metode kertas saring benih E.alba diberi perlakuan perendaman dalam larutan Natrium hipoklorit 18 selama satu menit dan tanpa perendaman dalam...
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Judul: Inventarisasi Hama dan Penyakit pada Pembibitan Tanaman Eucalyptus di Sentra Pembibitan 2 PT RAPP, Kabupaten Pelalawan, Riau
Abstrak: Perkembangan industri pulp dan kertas di Indonesia terus meningkat dari tahun ke tahun sehingga perlu adanya teknologi dan bahan baku yang cukup serta memadai. Bahan baku yang umumnya digunakan berupa jenis kayu hardwood yang telah dipersiapkan di area Hutan Tanaman Industri (HTI). Tanaman Eucalyptus sp. merupakan salah satu jenis tanaman prioritas yang dikembangkan dalam pengelolaan HTI yang diperuntukkan sebagai kayu serat. Salah satu masalah yang dapat mengganggu pertumbuhan tanaman dan mengakibatkan kerugian adalah serangan dari organisme pengganggu tanaman (OPT). Dalam beberapa kasus, serangan penyakit pada tanaman dapat mengakibatkan terhambatnya pertumbuhan tanaman, menurunnya kualitas kayu, bahkan kematian tanaman. Penelitian bertujuan mengetahui jenis-jenis hama dan penyakit, serta budi daya tanaman Eucalyptus dari sampel bibit bergejala yang diambil dengan metode purposive sampling di Sentra Pembibitan 2 PT RAPP, Kecamatan Pangkalan Kerinci, Kabupaten Pelalawan, Riau. Identifikasi patogen dilakukan dengan membandingkan hasil pengamatan gejala serta tanda di lapangan dan laboratorium dengan literatur. Inventarisasi hama dilakukan dengan studi literatur berdasarkan data hama ditemukan yang telah tersedia. Penyakit yang menyerang bibit Eucalyptus adalah bercak daun Quambalaria, bercak daun dan batang Cylindrocladium, bercak daun Kirramyces, layu pucuk dan daun Rhizoctonia, dan hawar daun Xanthomonas. Hama yang ditemukan menyerang bibit tanaman Eucalyptus, yaitu ulat penggulung daun (Strepsicrates macroptena), tungau, kutu kebul (eucalyptus whitefly), thrips (Thrips autralis), wereng, kutu daun, dan Helopeltis theivora., The development of the pulp and paper industry in Indonesia continues to increase from year to year, which requires adequate technology and raw materials. Raw materials that are generally used are hardwood species that have been prepared in the Industrial Plantation Forest (HTI) area. Eucalyptus sp. is one of the priority plant species developed in HTI management which is intended as fiber wood. One of the problems that can interfere with plant growth and cause losses is the attack of plant pest organisms (OPT). In some cases, disease attacks on plants can result in inhibition of plant growth, decreased wood quality, and even plant death. This study aims to determine the types of pests and diseases, as well as the cultivation of Eucalyptus from symptomatic seedling samples taken by purposive sampling method at PT RAPP Nursery Center 2, Pangkalan Kerinci District, Pelalawan Regency, Riau. Pathogen identification was carried out by comparing observations of symptoms and signs in the field and laboratory with the literature. Pest inventory was conducted by literature study based on available pest data. Diseases that attack Eucalyptus seedlings are Quambalaria leaf spot, Cylindrocladium leaf and stem spot, Kirramyces leaf spot, Rhizoctonia shoot and leaf wilt, and Xanthomonas leaf blight. Pests found attacking Eucalyptus seedlings were leafroll caterpillars (Strepsicrates macroptena), mites, whitefly (eucalyptus whitefly), thrips (Thrips autralis), leafhoppers, aphids, and Helopeltis theivora.
Keyword: Eucalyptus sp., industrial forest plantations, pathogens, diseases

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