Judul: Etnobotani Pangan dan Obat Masyarakat Desa Pauh Tinggi di Sekitar Taman Nasional Kerinci Seblat
Abstrak: Ethnobotany is a study about traditional utilization of plants by local community. The objective of this research was identified the diversity of food and medicinal plants utilized by local community in Pauh Tinggi village around Kerinci Seblat National Park. The method of data collection were interview, field observation, literature review and herbarium. The result showed that total of 236 species were identified from 64 families, which consisted of 90 species of food plants from 35 families and 187 species of medicinal plants from 58 families. Zingiberaceae was the most frequent food plants family found in this research, while solanaceae and zingiberaceae were the most frequent medicinal plants family. Herbs was the most frequent habitus of food and medicinal plants found in this research. Fruit was the most frequent part of plants that used for food plants, while leaf is the most frequent part of plants that used for medicinal plants. Local community at Pauh Tinggi village used the plants based on their traditional knowledge
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Judul: Etnobhotany of Kerinci Ethinic Around Bukit Tinggai Indigenous Forest Sungai Deras Village, Kerinci Regency of Jambi Province).
Abstrak: Hutan adat dengan masyarakatnya merupakan kesatuan yang tidak dapat dipisahkan. Masyarakat ini biasanya memiliki pengetahuan mengenai peranan kearifan lokal. Peranan kearifan lokal tersebut antara lain dalam penggunaan bahan-bahan alam terutama tumbuhan maupun kearifan pengelolaan hutan. Melihat hal tersebut serta proses pendokumentasian yang masih sangat kurang dan adanya perubahan tentang pengelolaan kawasan hutan di beberapa daerah seperti di Hutan Adat Bukit Tinggai, maka perlu dilakukan penelitian untuk menindaklanjuti hal tersebut. Tujuan dari penelitian ini yaitu (1) mengetahui pemanfaatan jenis tumbuhan oleh masyarakat Suku Kerinci di Desa Sungai Deras Kecamatan Air Hangat Timur Kabupaten Kerinci Provinsi Jambi; (2) inventarisasi jenis tumbuhan di Hutan Adat Bukit Tinggai Desa Sungai Deras, Kecamatan Air Hangat Timur, Kabupaten Kerinci Provinsi Jambi. Penelitian dilakukan dengan tiga tahap yaitu (1) studi pustaka berupa pencarian dokumen untuk data sekunder; (2) kajian lapang etnobotani berupa wawancara, survei lapang dan inventarisasi lapang, analisis vegetasi dan pembuatan herbarium; (3) pengolahan dan analisis data yeng meliputi klasifikasi kelompok kegunaan, persentase habitus dan bagian yang digunakan, indeks nilai penting (INP), keanekaragaman spesies Shannon–Wienner, dan persentase potensi tumbuhan berguna. Jumlah jenis tumbuhan yang ditemukan berdasarkan wawancara dan analisis vegetasi adalah 194 jenis. Hasil wawancara etnobotani ditemukan sebanyak 132 jenis dari 55 famili yang juga telah diketahui manfaatnya dan dikelompokkan kedalam 13 kelompok kegunaan. Jumlah jenis hasil analisis vegetasi sebanyak 107 jenis dari 52 famili. Jumlah jenis tumbuhan berguna berdasarkan habitusnya paling banyak adalah tingkat pohon dengan jumlah 55 jenis. Pada tingkat semai satepau memiliki dominansi terbesar yaitu 20,45 %, pada tingkat pancang adalah jenis kayu pecah pinggang (Castanopsis malaccensis Gamble.) dengan nilai 16,70 %, pada tingkat pertumbuhan tiang yaitu semantao (Ficus padana) sebesar 33,61 %, dan kayu pecah pinggang (Castanopsis malaccensis Gamble.) pada habitus pohon yaitu 23,27 %. Kegunaan tumbuhan yang paling banyak dimanfaatkan adalah untuk pengobatan sebanyak 54 spesies dari 39 famili. Spesies-spesies tumbuhan berguna potensial yang ada di Hutan Adat Bukit Tinggai antara lain kopi (Coffea sp.), kayu manis (Cinnamomum subavenium Miq.) dan cengkeh (Eugenia aromatica)
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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