Judul: Condition of Coral Reefs and Benthic Community Cover in Bontang City
Abstrak: ABSTRAK WAFIQ SALMAN ARROSADI. Kondisi Terumbu Karang dan Tutupan Komunitas Bentik di Kota Bontang. Dibimbing oleh BEGINER SUBHAN dan FERY KURNIAWAN. Indonesia merupakan negara dengan keanekaragaman hayati laut yang melimpah, memiliki sekitar 18% dari total luas terumbu karang di dunia dan dikenal sebagai salah satu titik pusat keanekaragaman hayati laut global. Terumbu karang, sebagai komponen penting dari ekosistem pesisir dan laut, sangat rentan terhadap gangguan. Penelitian ini bertujuan untuk mengevaluasi kondisi terumbu karang dan kualitas perairan di Perairan Kota Bontang, Kalimantan Timur. Data tutupan terumbu karang dianalisis dari sembilan stasiun pengamatan, sementara parameter kualitas air meliputi suhu, salinitas, pH, dan oksigen terlarut. Data yang digunakan dalam penelitian ini merupakan data sekunder yang diperoleh dari Pusat Kajian Sumberdaya Pesisir dan Lautan (PKSPL) IPB dan PT. Pupuk Kaltim. Data sekunder diperoleh dari sembilan stasiun pengamatan Hasil penelitian menunjukkan bahwa terumbu karang di kawasan ini umumnya mengalami degradasi, terutama ditandai dengan dominasi tutupan Rubble dan Dead Coral with Algae. Stasiun dengan tutupan karang hidup tertinggi adalah Stasiun 5 (22,67%), sedangkan Stasiun 4 menunjukkan tutupan terendah (0%). Lifeform karang keras yang dominan adalah Acropora tabulate dan Coral Mushroom. Meskipun demikian, kualitas air secara umum masih berada dalam batas toleransi, walaupun terdapat beberapa parameter yang tidak memenuhi baku mutu yang disarankan. Penelitian ini memberikan gambaran yang penting untuk memahami kondisi ekologis terumbu karang di Kota Bontang dan pentingnya upaya konservasi untuk memulihkan ekosistem ini di masa depan. Kata kunci: terumbu karang, kualitas air, Bontang, Kalimantan Timur, Indonesia., ABSTRACT WAFIQ SALMAN ARROSADI. Condition of Coral Reefs and Benthic Community Cover in Bontang City. Supervised by BEGINER SUBHAN and FERY KURNIAWAN. Indonesia is a country with abundant marine biodiversity, containing approximately 18% of the world's coral reefs and known as one of the global centers of marine biodiversity. Coral reefs, as a vital component of coastal and marine ecosystems, are highly vulnerable to disturbances. This study aims to evaluate the condition of coral reefs and water quality in the waters of Bontang City, East Kalimantan. Coral reef cover data were analyzed from nine observation stations, while water quality parameters included temperature, salinity, pH, and dissolved oxygen. The data used in this study were secondary data obtained from the Center for Coastal and Marine Resources Studies (PKSPL) at IPB University and PT. Pupuk Kaltim. Secondary data were collected from nine observation stations. The results indicate that the coral reefs in this area generally experience degradation, primarily marked by the dominance of Rubble and Dead Coral with Algae covers. Station 5 showed the highest live coral cover (22.67%), whereas Station 4 exhibited the lowest (0%). The dominant hard coral lifeforms were Acropora tabulate and Coral Mushroom. However, overall water quality remains within tolerance limits, although some parameters did not meet recommended standards. This research provides crucial insights into the ecological condition of coral reefs in Bontang City and underscores the importance of conservation efforts to restore this ecosystem in the future. Keywords: coral reefs, water quality, Bontang, East Kalimantan, Indonesia.
Keyword: terumbu karang, bentik, kota bontang

Judul: Coral Reef Ecosystem Analysis Related With The Quality of Water in Labuan Waters, Pandeglang District, Banten
Abstrak: Terumbu karang merupakan ekosistem dengan kerentanan tinggi terhadap perubahan lingkungan perairan, dapat disebabkan faktor alami (autogenic) ataupun faktor manusia (anthropogenic). Penelitian ini dilakukan untuk menganalisis kondisi kualitas perairan serta keterkaiatannya dengan terumbu karang yang dilakukan pada 9 lokasi pengamatan kualitas air dan 4 lokasi pengamatan kondisi ekosistem terumbu karang di wilayah Labuan Banten. Penelitian ini diharapkan dapat menjadi acuan pengelolaan lingkungan wilayah perairan Labuan Banten, serta sebagai bahan dasar pengelolaan sumberdaya ekosistem pesisir khususnya ekosistem terumbu karang perairan Labuan Banten. Metode yang digunakan adalah metode survey, pengambilan data ekosistem terumbu karang dilakukan dengan metode Line Intercept Transect (LIT). Pengukuran kualitas air dilakukan dengan melakukan pengukuran parameter fisika perairan yang dilakukan secara insitu menggunakan water quality meter, dan parameter kimia air laut dengan identifikasi laboratorium. Tutupan substrat dasar ekosistem terumbu karang perairan Labuan Banten memiliki persentase karang keras 1,72% hingga 13,34%. Nilai persentase tutupan karang tersebut menggambarkan kondisi terumbu karang termasuk dalam kategori Rusak. Persentase tutupan substrat dasar berupa algae memiliki nilai tertinggi 54,08%. Nilai kualitas perairan secara umum dicirikan oleh nilai nitrat dan nilai COD dengan kondisi kualitas perairan yang sudah melebihi ambang batas. Keterkaitan kualitas air dengan ekosistem terumbu karang dicirikan dengan persentase Alga yang tinggi akibat tingginya nitrat, Keberadaan komunitas alga yang tinggi pada ekosistem terumbu karang menggambarkan bahwa adanya kompetisi ruang terhadap kondisi terumbu karang di Perairan Labuan Banten., Coral reefs ecosystems are highly vulnerability to the underwater environment changes, both caused by autogenic or anthropogenic. This study has been carried out at nine water quality observation locations and four observation locations for coral reef ecosystem conditions in the Labuan Banten region, to observe the water quality and its relation with coral reefs ecosystem. The outcome this research can be used as reference for environmental management in the waters of Labuan Banten, as well as a primary material for managing coastal ecosystem resources. This research utilise surveys methods, in which the coral cover data used Line Intercept Transect (LIT). Water quality measurements were carried out by measuring the physical parameters of the waters using a water quality meter and the chemical parameters by laboratory identification. The percentage value of coral cover describes the condition of coral reefs included in the damaged category. The percentage of base substrate cover in the form of algae has the highest value of 54.08%. The value of water quality is generally characterized by the value of nitrate and COD with water quality conditions that have exceeded the threshold. A high percentage of algae characterizes the relationship between water quality and coral reef ecosystems due to high nitrate. A high algal community in coral reef ecosystems describes that there is space competition for coral reef conditions in Labuan Banten waters.
Keyword: Algae, Kualitas Air, Labuan Banten

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