Judul: Status Penyakit Yang Disebabkan Cendawan Pada Tanaman Pala (Myristica fragrans Houtt.) di Sentra Tanaman Pala Kabupaten Bogor, Jawa Barat
Abstrak: Tanaman pala (Myristica fragrans) merupakan salah satu komoditas ekspor potensial yang berasal dari Indonesia dan memiliki nilai ekonomi tinggi. Setiap tahun, terjadi peningkatan luas pertanaman pala di berbagai wilayah di Indonesia. Berdasarkan hal tersebut, Indonesia merupakan pemasok pala terbesar di dunia sehingga pala menjadi salah satu penyumbang bagi pendapatan negara. Salah satu daerah penghasil pala di Jawa Barat adalah Kabupaten Bogor. Beberapa masalah yang dapat menurunkan kualitas maupun kuantitas produksi pala adalah umur tanaman yang sudah tua dan penyakit tanaman yang beragam dan meluas. Penelitian ini bertujuan untuk mengamati status penyakit penting pada tanaman pala di Kecamatan Dramaga, Cijeruk dan Leuwisadeng, Kabupaten Bogor. Metode penelitian terdiri atas wawancara petani, penentuan lokasi pengamatan, pengamatan perkembangan penyakit dan pengambilan tanaman contoh, isolasi cendawan, uji patogenisitas, identifikasi cendawan dan analisis data. Hasil penelitian di Kecamatan Dramaga, Cijeruk dan Leuwisadeng, Kabupaten Bogor menunjukkan tiga penyakit penting yang menginfeksi tanaman pala. Penyakit tersebut adalah bercak tulang daun dan kanker ranting yang disebabkan Botryodiplodia sp. dan bintik buah yang disebabkan oleh hifa steril
Keyword: Botryodiplodia sp., hifa steril, identifikasi, patogen, patogenisitas

Judul: Penyakit pada pembibitan pala (Myristica fragrans Houtt) di kecamatan tamansari, kabupaten bogor
Abstrak: Pala merupakan tanaman rempah-rempah yang sangat penting dan memiliki banyak keuntungan. Penyakit tanaman dapat menurunkan produktivitas pala. Adanya penyakit tanaman di pembibitan pala menentukan kelangsungan hidup tanaman sampai tumbuh dan menghasilkan buah. Penelitian ini dilakukan untuk mengetahui keanekaragaman, kejadian penyakit, dan tingkat keparahan penyakit di pembibitan pala yang disebabkan oleh cendawan patogen. Metode penelitian ini terdiri dari wawancara, survei lokasi pengambilan contoh, observasi langsung dan pengumpulan contoh, dan identifikasi contoh tanaman gejala di laboratorium. Enam gejala penyakit diidentifikasi dari daun, cabang, dan akar. Gejala ini disebabkan oleh tujuh spesies yang berbeda dari cendawan patogen. Bercak nekrotik yang diidentifikasi disebabkan oleh Cylindrocladium sp., hawar daun disebabkan oleh Helminthosporium sp. dan Curvularia sp., sedangkan antraknosa disebabkan oleh Gloeosporium sp. Mati cabang dan bibit mati disebabkan oleh dua isolat berbeda Fusarium sp. (1 dan 2), sedangkan embun hitam diidentifikasi disebabkan oleh Meliola sp.
Keyword: Breeding, Fungi, Identification, Productivity, Spices, Curvularia Sp., Nutneg nursery, Pathogenetic fungi, Nerotic spot, Gloeosporium

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