Judul: Pengaruh Financial Distress terhadap Return Saham pada Perusahaan Tbk Kelompok Sektor Pertanian
Abstrak: Badan Pusat Statistik (BPS) mencatat penduduk Indonesia paling banyak bekerja di sektor pertanian. Perusahaan di sektor pertanian harus menjaga kesehatan perusahaan tersebut agar tetap mampu menyerap tenaga kerja. Terkait dengan aktivitas perusahaan tentu membutuhkan tambahan dana. Dana diperoleh melalui pendanaan eksternal dari investor dengan menjual saham dan investor mengharapkan return. Pertimbangan investasi melalui analisis rasio keuangan yang mampu menggambarkan kondisi perusahaan. Salah satu kondisi perusahaan yaitu financial distress. Financial distress merupakan peringatan dini untuk mencegah kebangkrutan, dihitung dengan metode Springate. Penelitian ini bertujuan menganalisis kondisi perusahaan dan pengaruh financial distress terhadap return saham pada perusahaan Tbk kelompok sektor pertanian periode 2012-2016. Penelitian ini menggunakan metode Springate dan regresi data panel. Metode springate memperhitungkan 4 rasio keuangan yaitu: Working Capital to Total Assets Ratio, Net Profit Before Interest and Taxes to Total Assets Ratio, Net Profit Before Taxes to Current Liabilities, dan Sales to Total Assets Ratio. Hasil s-score < 0,826 mengindikasikan bahwa perusahaan tidak sehat. Hasil membuktikan 3 perusahaan selalu sehat, 6 fluktuatif dan 6 selalu financial distress selama periode penelitian. Secara simultan financial distress tidak berpengaruh terhadap return saham dan secara parsial terdapat dua rasio yang berpengaruh.
Keyword: financial distress, regresi, return saham, springate

Judul: nalisis Faktor-Faktor yang Memengaruhi Financial Distress pada Perusahaan Sektor Agriculture
Abstrak: Financial distress merupakan suatu tahap penurunan kondisi keuangan perusahaan yang terjadi sebelum timbulnya kebangkrutan. Penelitian ini bertujuan untuk menganalisis tingkat financial distress; menganalisis rasio profitabilitas, likuiditas, leverage, aktivitas, ukuran perusahaan sektor agriculture; dan menganalisis pengaruh profitabilitas, likuiditas, leverage, aktivitas, ukuran perusahaan terhadap financial distress sektor agriculture. Penelitian ini menggunakan data sekunder yang berdasarkan laporan keuangan perusahaan sektor agriculture di BEI (Bursa Efek Indonesia) periode 2012-2016. Metode purposive sampling digunakan untuk menentukan sampel sesuai dengan kriteria yang digunakan, sehingga ditemukan sampel sebanyak 16 perusahaan. Penelitian ini dilakukan dengan metode Altman Z-score untuk mengindikasi tingkat financial distress dan analisis menggunakan regresi data panel. Hasil penelitian menunjukkan bahwa rasio likuiditas berpengaruh positif, leverage berpengaruh negatif dan ukuran perusahaan berpengaruh negatif terhadap financial distress, sedangkan variabel profitabilitas dan aktivitas tidak berpengaruh terhadap financial distress.
Keyword: Altman Z-score, Financial distress, Leverage, Likuiditas, Profitabilitas

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