Judul: Analisis Risiko Produksi Jamur Tiram Putih Dd. Mushroom Di Kecamatan Ciawi Kabupaten Bogor Provinsi Jawa Barat
Abstrak: Usaha budidaya jamur tiram putih pada DD.Mushroom memiliki tingkat keberhasilan yang berbeda-beda dalam proses produksinya. Hasil produksi yang bermacam-macam dapat mempengaruhi jumlah produktivitas sehingga menyebabkan terjadinya fluktuasi. Fluktuasi produktivitas tersebut merupakan salah satu indikasi adanya risiko produksi. Adanya risiko di DD Mushroom kemudian diidentifikasi sumber-sumber risikonya. Sumber risiko kemudian dianalisis seberapa besar probabilitas dan dampaknya dengan metode analisis kualitatif dan analisis kuantitatif yaitu metode z-score dan var. Hasil analisis selanjutnya dilakukan strategi penanganan untuk mengatasi risiko pada budidaya jamur tiram putih. Berdasarkan hasil penelitian, diketahui sumber risiko produksi yang terdapat diperusahaan yaitu sumberdaya manusia, hama dan penyakit, serta perubahan cuaca.
Keyword: Metode z-score, Risiko produksi, Value at risk

Judul: Analisis Risiko Produksi Jamur Tiram Putih di Kecamatan Ciawi, Kabupaten Bogor, Jawa Barat
Abstrak: Kecamatan Ciawi merupakan salah satu sentra penghasil jamur tiram putih terbesar di Kabupaten Bogor, namun produktivitas jamur tiram putih di Kecamatan Ciawi mengalami fluktuasi. Tujuan dari penulisan ini adalah untuk mengetahui sumber risiko produksi dan menganalisis pengaruh faktor-faktor produksi terhadap risiko produksi jamur tiram putih yang dihadapi oleh petani responden di Kecamtan Ciawi. Metode yang digunakan dalam penentuan sampel adalah simple random sampling dengan 38 responden. Penelitian ini menggunakan metode Just and Pope sebagai metode analisis data. Hasil penelitian ini menunjukkan bahwa peningkatan penggunaan kapur, air, obat perangsang pertumbuhan, dan dummy musim masingmasing sebesar 0.156414, 0.293629, 0.172506, dan 0.307521 dapat dikatakan mampu meningkatkan produktivitas jamur tiram putih. Namun, hanya variabel tenaga kerja saja yang menurunkan produktivitas jamur tiram putih, sebesar 0.213802. Faktor produksi yang meningkatkan risiko (risk inducing factor) adalah peningkatan kapur, air, obat perangsang pertumbuhan, dan dummy musim, masingmasing sebesar 0.14755, 0.287325, 0.165568, 0.330521, sedangkan faktor produksi yang merupakan faktor yang mengurangi risiko (risk reducing factor) yaitu tenaga kerja masing-masing sebesar 0.170191.
Keyword: fluktuasi, risiko produksi, and metode Just and Pope

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