Judul: Keragaan Kegiatan Jasmani, Status Gizi Dan Pola Konsumsi Penyandang Diabetes Melitus Tipe 2 Di Rumah Sakit Umum Pusat Nasional dr. Cipto Mangunkusumo, Jakarta
Abstrak: gizi dan pola makan penyandang Diabetes Melitus tipe 2 di Rumah Sakit Umum Pusat Nasional Dr. Cipto Mangunkusumo (RSUPN/RSCM), Jakarta. Sedangkan tujuan khususnya yaitu mempelajari: status gizi penyandang DM tipe 2, karakteristik dan gambaran demografi, kegiatan jasmani (aktivitas + olah raga), serta pola konsumsi makan dan rekomendasi diet yang diberikan pada contoh. Disain penelitian ini adalah cross sectional study.Lokasi penelitian di RSCM yaitu di Poliklinik Konsultasi Gizi RSCM pada tanggal 26 Juni-I Agustus 2003. Contoh dalam penelitian ini adalah penyandang DM tipe 2 yang berkonsultasi di Poliklinik tersebut pada saat penelitian berlangsung. Penarikan contoh dilakukan denganpurposive sampling, dengan kriteria pasien contoh berusia 20-65 tahun, tidak dalam keadaan hamil, pasien baru, paling sedikit memiliki kadar glukosa darah puasa atau kadar glukosa darah 2 jam PP dan kadar glukosa darah sewaktu, memiliki kesadaran yang baik, dapat berkomunikasi, dan bersedia menj adi responden. Dari 131 orang pasien yang berkonsultasi ke Poliklinik Konsultasi Gizi RSPUN yang memenuhi kriteria tersebut di atas sebanyak 39 orang dijadikan contoh dan sekaligus responden.
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Judul: Kebiasaan makan penderita diabetes mellitus tipe II (Non insulin dependent diabetes mellitus) sebelum didiagnosa dan faktor-faktor yang mempengaruhi kadar gula darah
Abstrak: Penelitian ini bertujuan untuk mengetahui kebiasaan makan penderita diabetes mellitus tipe II, yang berobat di Rumah Sakit Karya Bhakti Bogor, sebelum didiagnosa, mengetahui sebaran penderita DM tipe II menurut jenis kelamin, riwayat keluarga, olahraga, tingkat pendidikan, dan tingkat pendapatan, mengetahui status gizi, kadar gula darah acak, dan jenis komplikasi yang timbul; serta mengetahui faktor- faktor yang mempengaruhi kadar gula darah penderita. Penelitian dilakukan dengan rancangan retrospective study di Rumah Sakit Karya Bhakti, Bogor selama lima bulan, terhitung sejak bulan Juli 1996 hingga November 1996. Contoh adalah penderita diabetes mellitus tipe II yang berobat di Rumah Sakit Karya Bhakti Bogor selama penelitian berlangsung dan bersedia diwawancara. Data primer yang dikumpulkan meliputi identitas contoh (umur, jenis kelamin, riwayat keluarga, tingkat pendidikan, dan pendapatan), olahraga, kebiasaan makan contoh enam bulan sebelum didiagnosa menderita diabetes, berat badan, dan tinggi badan. Data sekunder meliputi kadar gula darah dan jenis komplikasi. Identitas contoh dikumpulkan pada saat penelitian berlangsung dengan cara wawancara menggunakan kuesioner. Olahraga, berat dan tinggi badan, serta kebiasaan makan contoh enam bulan sebelum didiagnosa, dikumpulkan secara retrospective study melalui wawancara. Sedangkan data berat dan tinggi badan contoh saat didiagnosa, kadar gula darah, dan jenis komplikasi dikumpulkan dari medical record. Pengumpulan data kadar gula darah dilakukan oleh petugas rumah sakit menggunakan glucometer. Untuk mengetahui faktor-faktor yang mempengaruhi kadar gula darah penderita dilakukan analisis regresi berganda menggunakan program SPSS/PC+.
Keyword: diabetes

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