Judul: Risiko Penyimpangan Perilaku Makan pada Mahasiswi dan Hubunganya dengan Konsumsi Pangan dan Status Gizi.
Abstrak: Beberapa penelitian mengungkapkan adanya penyimpangan perilaku makan pada remaja. Penelitian ini bertujuan untuk menganalisis risiko penyimpangan perilaku makan pada mahasiswi dan hubunganya dengan konsumsi pangan. Contoh dalam penelitian ini adalah mahasiswi tingkat tiga program sarjana Fakultas Ekonomi dan Manajemen, Institut Pertanian Bogor. Design penelitian yang digunakan adalah cross - sectional study dengan jumlah contoh sebesar 60 orang (30 orang berisiko mengalami penyimpangan perilaku makan, dan 30 orang tidak berisiko) yang dipilih secara acak . Data yang digunakan berupa data primer yang diperoleh secara langsung melalui wawancara dengan menggunakan instrumen EAT - 26, instrumen FRS, foodrecall, kuesioner kritikan teman sebaya, riwayat diet, pengetahuan gizi serta status giz i melalui pengukuran antropometri berupa tinggi badan dan berat badan. Hasil penelitian menunjukkan bahwa terdapat hubungan yang signifikan anta rapenyim pangan perilaku makan dengan dampak kritikan oleh teman sebaya tentang bentuk danu kuran tubuh , riwayat diet, dan tingkat kecukupan energi. Tidak terdapat hubungan yang signifikan antar penyimpangan perilaku makan dengan body image , dan pengetahuan gizi. Faktor risiko penyimpangan perila kumakan pada penelitian ini meliputi kritikan teman sebaya dan riwayat diet.
Keyword: diet, body image, kritikan, pengetahuan gizi

Judul: Hubungan persepsi tubuh dengan gangguan makan pada mahasiswa
Abstrak: Tujuan penelitian ini adalah mengetahui hubungan persepsi tubuh dengan gangguan makan pada mahasiswa. Desain penelitian ini cross sesctional study pada mahasiswa baru Program Studi Ilmu Gizi di Institut Pertanian Bogor (IPB) dengan jumlah 120 remaja. Hasil studi menunjukkan proporsi subjek dengan status gizi normal 83.3%, 10.0% overweight, 4.2% obesitas dan 2.5% kurus. Penilaian MBSRQ-AS diperoleh subjek memiliki persepsi negatif terhadap evaluasi penampilan sebesar 80%, orientasi penampilan 99.2%, dan kepuasan terhadap bagian tubuh 80.8%; sedangkan 57.5% subjek cemas menjadi gemuk dan 71.7% subjek perempuan memiliki persepsi negatif terhadap kategori ukuran tubuh. Tidak terdapat gangguan makan pada subjek laki-laki sedangkan 7.8% subjek perempuan mengalami gangguan makan dengan risiko lebih karena merasa memiliki keinginan untuk makan terus-menerus dan tidak dapat berhenti makan (2-3x sebulan). Terdapat hubungan yang signifikan antara persepsi tubuh (MBSRQ-AS) pada subskala kecemasan menjadi gemuk dengan gangguan makan (p<0.05). Namun tidak terdapat hubungan yang signifikan pada subskala yang lain dan antara persepsi tubuh (FRS) dan (BIQ) dengan gangguan makan (p>0.05)., The objective of this study was to determine the relationship of body image perception and eating disorders in undergraduated students. The design of this study is cross sectional with new students that major in nutritional program in Bogor Agricultural University (IPB) with the number was 120 students. The result showed that the proportion of subjects with normal nutritional status is 83.3%, 10.0% overweight, 4.2% obesity and 2.5% thin. MBSRQ-AS’ assessment obtained that subjects have negative perception of appearance evaluation is 80%, appearance orientation 99.2% and body areas satisfaction 80.8%; whereas 57.5% subjects is anxious of being fat and 71.7% female subject has negative perception of self-classified weight. There wasn’t eating disorders in male, whereas 7.8% female subject have eating disorders with more risk (have attitute the desire to eat continously and can’t stop eating 2-3 times a month). There was significant correlation between body image perception (MBSRQ-AS) in overweight preoccupation subscale with eating disorders (p<0.05). However there were no significant correlations for other subscales and between body image perception of FRS and BIQ and eating disorders (p>0.05).
Keyword: gangguan makan, mahasiswa, persepsi tubuh

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