Judul: Identifikasi Kesehatan Karang Famili Fungiidae di Perairan Indonesia
Abstrak: Kondisi ekosistem terumbu karang saat ini mengalami tingkat kerusakan yang cukup tinggi. Hal ini disebabkan oleh beberapa faktor yaitu, faktor alam dan aktivitas manusia. Karang jamur (Fungiidae) merupakan salah satu karang yang dapat hidup soliter (free-living) dan hidup di berbagai macam substrat. Karang jamur (Fungiidae) dipilih karena memiliki kemampuan untuk menghindar dari organisme kompetitor yang berbahaya bagi dirinya. Penelitian ini bertujuan untuk mengetahui jenis-jenis gangguan kesehatan karang, kelimpahan gangguan kesehatan karang dan prevalensi karang sehat dan karang yang kesehatannya terganggu yang terdapat di perairan Indonesia. Penelitian dilaksanakan pada tahun 2011-2013 (diluar Pulau Pramuka) dan 2020 (Pulau Pramuka) dengan mengambil 67 titik pengamatan yang tersebar di 20 provinsi di perairan Indonesia. Metode yang digunakan adalah Belt Transect dengan ukuran 2 x 50 meter. Berdasarkan penelitian yang dilakukan ditemukan 8 genus dari Famili Fungiidae dengan genus Fungia yang mendominasi. Gangguan kesehatan karang yang ditemukan berjumlah 12 jenis. Gangguan Kesehatan karang yang paling banyak ditemukan adalah Yellow band disease dengan kelimpahan sebesar 3,064 ind/m2 dan prevalensi sebesar 26,377%., The condition of the coral reef ecosystem is currently experiencing a high level of damage. This is caused by several factors, namely, natural factors and human activities. Mushroom coral is one of the corals that can live solitary (free- living) and live in various kinds of substrates. Mushroom coral was chosen because it can avoid harmful competing organisms for itself. This study aims to determine the types of compromised coral health, the abundance of coral with compromised health, and the prevalence of healthy coral and coral with compromised health found in the Indonesian sea. The research was conducted in 2011-2013 (outside Pramuka Island) and 2020 (Pramuka Island) by taking 67 observation points spread across 20 provinces in Indonesian waters. The method used was Belt Transect with a size of 2 x 50 meters. Based on the research conducted, 8 genera of the Fungiidae family were found with the predominant genus Fungia. There were 12 coral with compromised health. The most common disease found was Yellow band disease with an abundance of 3.064 ind / m2 and a prevalence of 26.377%.
Keyword: terumbu karang, karang jamur, fungiidae, kesehatan karang

Judul: Kesehatan Karang Fungiidae di Pulau Pari, Kepulauan Seribu
Abstrak: Coral disease is one of the main causes of the decline of coral reef ecosystems. Fungiidae had been chosen because if compared to other corals, Fungiidae had an advantage in the ecological quantitative survey. The study aims to measure the level of coral health based on abundance and prevalence of coral health category. The study was conducted on 24 to 25 November 2013 in Pari Island, Thousand Islands on 4 stations spread. The method used in this study is Belt Transect method with 2 x 100 meters and Line Intercept Transect ( LIT ) along 30 meters with three replications. Based on the research conducted, 5 Fungiidae was found with Fungia genus dominated. The health condition of corals Fungiidae in Pari Island is divided into fourcategories that are 35% healty and 65% sick consisting of tissue discoloration-white (coral bleaching), tissue discoloration-non white (yellow band disease), and compromised health (sedimentation damage).
Keyword: coral disease., coral bleaching, coral health, Fungiidae

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