Judul: Isolasi Dan Penapisan Khamir Dari Permukaan Buah Untuk Mempertahankan Kesegaran Pascapanen Buah Cabai Merah
Abstrak: Cabai merah (Capsicunr amunr TM 999)mempakan komoditas penting di Indonesia. Bagaimanapnn, cabai merah mempakm buah yang rentan terhadap penyakit, oleh sebab itn perlu dicari alternatif untuk mempertahankankesegaran pascapanen buah cabai merah. Perlindungan hayati menggunakan khamir yang diisola~di ari pennnkaan buah dipilih untuk melindungi pascapanen buah cabai merah dari serangan cendawanpatogen. Penapisan khamir untnk mencari isolat yang unggnl sebagai pelindung hayati (biokontml) ditentukan berdasarkan kemampuamya mempertahankan kesegaran tekstur, mengurangi bercakantraknosa dan mempertahankan bobot buah. Ada 19 isolat yang berhasil diisolasi dari permukaan buah belimbing (Averrhoa carambola), pepaya (Carica papaya), jambu bangkok (Psidium guujavo), mengkudu (Morinda citrifolia), mangga (Mangifera indica), jemk bali (Citrus nrmima), erbis (Passrpora quadrangularis), markisa (PassrJ70ra edulis), pala (Myristica fragrans), dan srikaya (Annona squamosa). Setelah penapisan bertahap, diperoleh hasil bahwa cabai yang dilapisi khan~itri dak menunjukkan pengaruh yang berbeda nyata dengan cabai kontrol dalam mempertahankan tekstnr dan meminimnmkan bercak. Isolat PI menunjukk& kemampuannya dalam meminimnrnkan kelulangan bobot buah lebih baik daripada kehilangan bobot buah cabai kontrol.
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Judul: Potensi Khamir sebagai Agen Pengendalian Hayati Colletotrichum capsici, Cendawan Penyebab Antraknosa pada Buah Cabai
Abstrak: Antraknosa pada buah cabai yang disebabkan oleh Colletotrichum capsici dapat menyebabkan penurunan produksi dan kualitas buah cabai. Penggunaan agen pengendalian hayati dapat menjadi salah satu alternatif untuk mengendalikan C. capsici. Khamir merupakan salah satu agen pengendalian hayati yang berpotensi mengendalikan C. capsici. Penelitian ini bertujuan menguji potensi antagonistik khamir pada buah-buahan dan sayuran terhadap C. capsici. Sebanyak 22 isolat khamir diisolasi dari buah rambutan, pisang, cabai merah besar, tomat, dan terung ungu. Konsentrasi konidium C. capsici 5x106 konidium mL-1 menyebabkan luas gejala antraknosa tertinggi pada buah cabai merah var. IPB Perbani, sehingga konsentrasi tersebut digunakan pada uji selanjutnya. Seleksi khamir antagonis menggunakan uji sumur diperoleh sebanyak 5 isolat khamir, yaitu isolat CMM-1, CMM-3, CMM-4, TMM-1, dan EMM-11 mencegah total pertumbuhan C. capsici. Isolat CMM-3, CMM-4, TMM-1, dan EMM-11 mencegah total pertumbuhan C. capsici in vivo. Berdasarkan hasil identifikasi secara morfologi dan molekuler, isolat CMM-3, CMM-4, TMM-1, dan EMM-11 adalah Issatchenkia orientalis
Keyword: antagonistic yeast, antrachnose, biocontrol, Issatchenkia orientalis

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