Judul: Struktur Vegetasi, Komposisi, dan Serapan Karbon Pekarangan di Desa Duyung, Kecamatan Trawas, Kabupaten Mojokerto
Abstrak: Pekarangan merupakan salah satu bentuk agroforestri yang umumnya berada di bagian depan, belakang, dan/atau samping rumah. Susunan kanopi tajuk yang berjenjang serta kedalaman perakaran yang beragam menjadikan agroforestri dapat mencegah pemanasan global. Penelitian ini bertujuan untuk mengetahui struktur vegetasi, komposisi, dan serapan karbon pekarangan di Desa Duyung, Kecamatan Trawas, Kabupaten Mojokerto. Pengambilan data menggunakan purposive sampling method dimana area kerja dibagi menjadi 3 zona yaitu zona terdekat (zona A), tengah (zona B), dan terjauh (zona C) berdasarkan jarak dari gunung ke desa dengan 3 sampel pekarangan setiap zonanya. Hasil penelitian menunjukkan bahwa indeks nilai penting (INP) tertinggi pada tingkat pancang yaitu jenis kopi (Coffea sp.) sebesar 45%, tingkat tiang yaitu pisang (Musa sp.) sebesar 95%, dan pada tingkat pohon yaitu durian (D. zibethinus) sebesar 55%. Indeks keanekaragaman (H’), indeks kekayaan (R), dan indeks kemerataan (E) pada tingkat pancang memiliki nilai terbesar. Stratifikasi tajuk yang ditemukan adalah strata C dan D. Nilai biomassa tertinggi terdapat pada zona A yaitu sebesar 229,95 ton ha-1 atau simpanan karbon sebesar 105,78 ton ha-1 .
Keyword: Agroforestry, Carbon absorption, Species composition, Vegetation structure

Judul: Perbandingan Struktur, Komposisi Jenis, dan Simpanan Karbon Pekarangan antara Desa Ayamputih, Kebumen dan Desa Gunturharjo, Wonogiri
Abstrak: Pekarangan merupakan sistem agroforestri sederhana yang dapat digunakan untuk mengurangi emisi gas rumah kaca di udara. Tujuan dari penelitian ini yaitu mengidentifikasi struktur dan komposisi jenis tanaman pekarangan, serta menghitung simpanan karbon pekarangan di dua daerah yang berbeda. Penelitian ini menggunakan metode purposive sampling dengan pengambilan data secara sensus. Hasil penelitian menunjukkan komposisi jenis tanaman pada pekarangan Desa Gunturharjo memiliki jenis tanaman yang lebih banyak daripada pekarangan Desa Ayamputih. Nilai INP tertinggi untuk pancang, tiang, dan pohon pada kedua desa tersebut yaitu jenis kersen dengan nilai 37,91%, pisang senilai 48,30%, kelapa senilai 134,62% dan nangka senilai 35,19%, melinjo senilai 47,90% dan 69,55%. Pekarangan pada kedua lokasi memiliki kekayaan jenis tinggi dengan keanekaragaman jenis yang cukup rendah dan kemerataan jenis yang cukup merata kecuali pada tingkat pohon di Desa Gunturharjo. Total biomassa tertinggi terdapat pada Desa Ayamputih yaitu sebesar 57,66 ton/ha dengan simpanan karbon sebesar 28,82 ton/ha., The yard is a simple agroforestry system that can be used to reduce greenhouse gas emissions in the air. The purpose of this study is to identify the structure and composition of garden plant species, as well as to calculate the carbon storage of the yard in two different areas. This research uses a purposive sampling method with census data collection. The results showed that the composition of plant species in the Gunturharjo Village yard had more types of plants than the Ayamputih Village yard. The highest INP values for saplings, poles, and trees in the two villages namely cherry species with a value of 37.91%, bananas worth 48.30%, coconuts worth 134.62% and jackfruits valued at 35.19%, melinjo valued at 47.90% and 69.55%. Yards at both locations have high species richness with fairly low species diversity and fairly even species distribution except at the tree level in Gunturharjo Village. The highest total biomass was found in Ayamputih Village, which was 57.66 tons/ha with carbon storage of 28.82 tons/ha.
Keyword: carbon storage, species composition, vegetation structure, yard

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