Judul: Faktor-faktor yang berkaitan dengan asupan energi dan zat gizi pasien kanker di Rumah Sakit Kanker Dharmais Jakarta
Abstrak: WHO (2003) reported that more than 10 million people suffering from cancer which rate of development was about 20% annually. In Indonesia, prevalence of cancer was 4.3 out of 1000 and it’s predicted that 12 million people are suffering from cancer each year (Riskesdas 2008). Shike (1996) stated that the result of cancer treatment (operation, chemotherapy, and/or radiation) was malnourished which about more than 40% patients of cancer. The objectiveof this studywas toanalyze factorsassociated withenergy and nutrients intake of cancer patients at Cancer Hospital of DharmaisJakarta. The study was conductedusinga cross-sectional design.The number of samplesin this studywere 63who were hospitalizedat least threedays and can consump which were served by hospital .Based on thesurvey showed that the most prevalent of cancer was breast cancer(19%) and there are 19 kind of tumors and cancers. More than half(60%) of samples had anormal nutritional status, 41% ofsamplescome tohospitalaims tocarry outthe chemotherapy, and 56% of samples were hospitalize during5-10 days. The averageadequacy level ofenergy andprotein were 50.1% and 44.9%, respectively.Furthermore, the adequacy level ofvitamin A, C, and E were 19.3%, 82%, and 8.2%, respectively. Based onlinearregressionanalysis showed thatperiod of hospitalizationand medication/treatment significantly influenced theenergy and protein intake by21.6% and 21.7%, respectively.
Keyword: 

Judul: Adequency level of Energy and Protein Intake, Level of Nutrition Knowledge, Type of Cancer Therapy and Nutritional Status of Cancer Hospitalized Patients at Dharmais Cancer Hospital.
Abstrak: Penyakit kanker merupakan salah satu penyakit tidak menular yang menjadi masalah kesehatan masyarakat, baik di dunia maupun di negara berkembang seperti Indonesia. Menurut Riset Kesehatan Dasar (Riskesdas) tahun 2007 diantara penyakit tidak menular. Pada semua kelompok umur di Indonesia, kanker (tumor ganas) berada pada urutan keenam setelah diabetes mellitus yaitu 4.3‰. Kanker dapat dianggap sebagai penyakit dari sel-sel tubuh yang berkembang secara abnormal. Pengembangannya melibatkan kerusakan sel-sel DNA, dan kerusakan ini terakumulasi dari waktu ke waktu. Seiring dengan perjalanan penyakitnya dapat menimbulkan masalah gizi,terutama menyebabkan penurunan status gizi bagi penderitanya. Secara umum penelitian ini bertujuan untuk mempelajari tingkat kecukupan energi dan protein, tingkat pengetahuan gizi, jenis terapi kanker dan status gizi pasien kanker rawat inap di Rumah Sakit Kanker Dharmais. Penelitian ini menggunakan desain cross sectional study, karena pengambilan data dilakukan pada satu waktu tidak berkelanjut. Bertempat di Rumah Sakit Kanker Dharmais. Dilakukan pada bulan Juli 2011. Populasi adalah pasien kanker rawat inap di kelas II, III, dan Jamkesmas. Contoh adalah bagian dari populasi yang diambil dengan teknik purposive sampling dengan kriteria inklusi yaitu laki-laki atau perempuan, berusia > 18 tahun, pasien rawat inap kunjungan maksimal 3 hari rawat, kondisi sadar dan bersedia menjadi contoh penelitian. Jumlah contoh yang diambil yaitu sebanyak 80 orang. Data yang digunakan dalam penelitian ini adalah data primer dan data sekunder. Data primer meliputi data karakteristik contoh (usia, jenis kelamin, tingkat pendidikan, dan pekerjaan), tingkat pengetahuan gizi contoh diperoleh menggunaka kuesioner dengan pertanyaan sebanyak 20 pertanyaan, asupan makan contoh diperoleh dengan menggunakan recall 2 x 24 jam, antropometri (berat badan) contoh diperoleh dengan pengukuran menggunakan timbangan injak. Data sekunder meliputi data profil Rumah Sakit Kanker Dharmais, data tinggi badan, jenis kanker dan jenis terapi kanker yang diperoleh dari rekam medik. Data yang dikumpulkan diolah dan dianalisis, pengolahan data dimulai dari coding, editing, entry data kemudian dianalisis dengan menggunakan program nutrisurvey, komputer perangkat lunak microssoft excel 2007 dengan analisis deskriptif. Untuk melihat hubungan antar variabel, uji yang digunakan yaitu uji korelasi Pearson. Secara keseluruhan sebagian besar dari contoh (70%) adalah perempuan. Secara keseluruhan usia contoh berkisar antara 45-54 tahun (45%), hampir separuh dari contoh (39%) dengan tingkat pendidikan SMA/sederajat, separuh dari contoh (59%) tidak bekerja, hal ini dikarenakan contoh pada penelitian ini sebagian besar adalah ibu rumah tangga. Berdasarkan status gizi, separuh dari contoh (50%) dengan status gizi lebih maupun kurang, yaitu sebesar 16.25% contoh status gizi kurus berat, 11.25% kurus ringan, sebesar 15% contoh gemuk ringan dan 7.5% contoh gemuk berat. Berdasarkan tingkat pengetahuan gizi, hampir separuh dari contoh (43.8%) tingkat pengetahuan gizi rendah < 60% dengan rata-rata pengetahuan gizi 61.3%. Sebagian besar dari contoh (90%) memiliki tingkat kecukupan energi dengan kategori defisit berat, dan contoh (55%) dengan tingkat kecukupan protein defisit berat. Rata-rata asupan energi contoh 862±340 kkal dan rata-rata asupan protein contoh 34±17 gram. Dimana pada contoh yang memiliki tingkat kecukupan defisit berat ratarata asupan energi contoh yaitu 805±291 kkal dan rata-rata asupan protein 32±15 gram, contoh dengan tingkat kecukupan defisit sedang rata-rata asupan energi 878 kkal dan protein 43 gram, contoh dengan tingkat asupan defisit ringan rata-rata asupan energi yaitu 1578±173 kkal dan protein
Keyword: 

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