Judul: Cemas, Depresi, dan Aktivitas Fisik selama Masa  Pandemi Covid-19 di Indonesia
Abstrak: Many have reported that covid-19 pandemic contributes to mental health issues. Therefore, this study aims to determine anxiety and depression in relation to physical activity in Indonesia during covid-19 pandemic. Anxiety and depression were assessed using the Hospital Anxiety and Depression (HAD) scale. Meanwhile, physical activity was assessed using an International Physical Activity Questionnaire (IPAQ). Both instruments were presented in online form and distributed through social media in Bahasa Indonesia. Present findings show physical activity is associated with sex, age, marital and employment status, living area, and anxiety. Anxiety and depression are associated with each other, as well as with sex, age, marital and employment status, living area, and physical activity. Body Mass Index (BMI) is associated with depression exclusively. Recent research has shown that physical activity is inversely related to adverse mental health outcomes. Chronic illnesses such as covid-19 and existent mental health problems were common predictors of increased negative effects of anxiety and depression., Banyak yang melaporkan pandemi covid-19 berkontribusi pada masalah kesehatan mental. Karenanya, penelitian ini bertujuan menentukan cemas dan depresi terkait aktivitas fisik di Indonesia selama pandemi covid-19. Cemas dan depresi dinilai menggunakan skala Hospital Anxiety and Depression (HAD). Aktivitas fisik dinilai menggunakan International Physical Activity Questionnaire (IPAQ). Kedua instrumen diberikan dalam bentuk formulir daring dan disebarluaskan melalui media sosial dalam Bahasa Indonesia. Hasil studi menunjukkan aktivitas fisik berasosiasi dengan jenis kelamin, usia, status perkawinan dan pekerjaan, tempat tinggal, dan cemas. Cemas dan depresi berasosiasi satu sama lain, serta dengan jenis kelamin, usia, status perkawinan dan pekerjaan, area tempat tinggal, dan aktivitas fisik. Body Mass Index (BMI) hanya berasosiasi dengan depresi saja. Penelitian terbaru menunjukkan bahwa aktivitas fisik berbanding terbalik dengan hasil kesehatan mental yang merugikan. Penyakit kronis seperti covid-19 dan masalah kesehatan mental bawaan adalah prediktor umum dari peningkatan efek negatif dari cemas dan depresi.
Keyword: anxiety, depression, Indonesia's population, physical activity, psychological distress

Judul: Relationship between Diet Quality and Physical Activity with Nutritional Status of Adolescents during The Covid-19 Pandemic
Abstrak: Pandemi Covid-19 menyebabkan adanya pembatasan aktivitas yang dapat memengaruhi kualitas makan dan aktivitas fisik remaja. Tujuan dari penelitian ini adalah untuk menganalisis hubungan kualitas diet dan aktivitas fisik dengan status gizi remaja selama masa pandemi. Desain penelitian adalah cross sectional dengan jumlah subjek sebanyak 100 siswa di SMA Negeri 5 Bogor. Pengumpulan data dilakukan secara semi daring. Data kualitas diet dihitung dari konversi food recall 2x24 jam menggunakan indeks Diet Quality Indeks for Adolescents (DQI-A) yang dimodifikasi menggunakan Pedoman Gizi Seimbang 2014. Data aktivitas fisik didapatkan dengan wawancara subjek menggunakan International Physical Activity Questionnare Short Form (IPAQ-SF). Status gizi ditentukan menggunakan indikator z-score IMT/U. Sebagian besar subjek (60%) merupakan perempuan dengan rata-rata usia 16,8±0,6 tahun. Status gizi subjek berdasarkan IMT/U secara keseluruhan tergolong normal dengan persentase 78%. Rata-rata skor DQI-A subjek yaitu 52,6%±12,1% yang tergolong cukup baik. Aktivitas fisik subjek tergolong rendah ke sedang. Tidak terdapat hubungan yang signifikan antara kualitas diet dengan IMT/U (p>0,05). Namun, status gizi IMT/U memiliki hubungan signifikan dengan skor METs (p<0,05)., The Covid-19 pandemic has led to restrictions on activities that can affect the quality of food and physical activity in adolescents. The purpose of this study was to analyze the relationship between diet quality and physical activity with the nutritional status of adolescents during the pandemic. The research design was cross-sectional with the number of subjects as many as 100 students at SMA Negeri 5 Bogor. Data collection is done semi-online. Diet quality data was calculated from the 2x24 hour food recall conversion using the Diet Quality Index for Adolescents (DQI-A) modified using Balanced Nutrition Guidelines 2014. Physical activity data was obtained by interviewing subjects using the International Physical Activity Questionnare Short Form (IPAQ-SF). Nutritional status was determined using the BMI for age z-score indicator. Most of the subjects (60%) were female with an average age of 16.8±0.6 years old. Overall nutritional status based on BMI for age is normal with a percentage of 78%. The average DQI-A score of the subjects was 52.6%±12.1% which classified quite good. Physical activity is classified as low to moderate. There was no significant relationship between diet quality and BMI for age (p>0.05). However, BMI for age had a significant relationship with METs scores (p<0.05)
Keyword: Adolescents, diet quality, DQI-A, nutritional status, physical activity

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