ANALISIS KESALAHAN MENYELESAIKAN SOAL MATEMATIKA DALAM MATERI MATRIKS PADA SISWA KELAS XI IPS SMA NEGERI 1 ENDE

This study aims to determine: (1) mistakes have been made by the XI IPS grade students of SMA Negeri 1 Ende in solving matrix questions. (2) the factors that cause the XI IPS grade students of SMA Negeri 1 Ende in solving the matrix problem. (3) the efforts to solve students' errors in solving matrix questions in class XI IPS SMA Negeri 1 Ende. This study used a qualitative research approach using triangulation of sources and triangulation of techniques. The research subjects were 15 students of class XI IPS 3. The consideration of subject taking is based on the results of the error analysis according to the Newmann procedure. Methods of data collection using diagnostic tests, interviews, and documentation. The results of the research are: (1) the types of student errors are errors in understanding the concept of matrix count operations, process errors in solving matrix problems, and errors in concluding. 2) the factors that cause student errors are, students, choose the wrong formula, are not careful in solving matrix calculation operation problems, students are afraid to ask the teacher, and students' assumptions that mathematics is complicated, causing errors in determining the final answer. 3) while the efforts made were learning using rainbow matrix media which proved to be effective in learning matrix count operations.

Semi–definite programming for the nearest circulant semi–definite matrix problem

"Positive semi–definite circulant matrices arise in many important applications. The problem arises in various applications where the data collected in a matrix do not maintain the specified structure as is expected in the original system. The task is to retrieve useful information while maintaining the underlying physical feasibility often necessitates search for a good structured approximation of the data matrix. This paper construct structured circulant positive semi–definite matrix that is nearest to a given data matrix. The problem is converted into a semi–definite programming problem as well as a problem comprising a semi–defined program and second-order cone problem. The duality and optimality conditions are obtained and the primal-dual algorithm is outlined. Some of the numerical issues involved will be addressed including unsymmetrical of the problem. Computational results are presented."

Diffraction by a rigid strip in a plate modelled by Mindlin theory

We consider a plane flexural wave incident on a semi-infinite rigid strip in a Mindlin plate. The boundary conditions on the strip lead to three Wiener–Hopf equations, one of which decouples, leaving a scalar problem and a 2 × 2 matrix problem. The latter is solved using a simple method based on quadrature. The far-field diffraction coefficient is calculated and some numerical results are presented. We also show how the results reduce to the simpler Kirchhoff model in the low-frequency limit.

Finding Hadamard Matrices by a Quantum Annealing Machine

Finding a Hadamard matrix (H-matrix) among the set of all binary matrices of corresponding order is a hard problem, which potentially can be solved by quantum computing. We propose a method to formulate the Hamiltonian of finding H-matrix problem and address its implementation limitation on existing quantum annealing machine (QAM) that allows up to quadratic terms, whereas the problem naturally introduces higher order ones. For an M-order H-matrix, such a limitation increases the number of variables from M2 to (M3 + M2 − M)/2, which makes the formulation of the Hamiltonian too exhaustive to do by hand. We use symbolic computing techniques to manage this problem. Three related cases are discussed: (1) finding N < M orthogonal binary vectors, (2) finding M-orthogonal binary vectors, which is equivalent to finding a H-matrix, and (3) finding N-deleted vectors of an M-order H-matrix. Solutions of the problems by a 2-body simulated annealing software and by an actual quantum annealing hardware are also discussed.

Load Balancing of Unbalanced Matrix Problem of Maximum Machines with Min Min Algorithm

Most eminent computing technology related to the cloud is an exclusively web-based approach where resources are hosted on a cloud; it prospers the resources. Cloud computing is the most promising technologies that offer a standard for bulky sized computing. That is a structure for enabling applications to execution on virtualized resources and accessed by a network protocol. It provides resource and services in a very elastic behavior that can be scaled according to the required of the clients. Limited numbers of devices execute less number of tasks at that time. So it is more complex to perform each task at once. Several devices execute each task, so it has required balancing total loads that reduce the completion time and executes each task in a definite way. We have said earlier that there are not feasible to stay behind an equal server to execute similar tasks. The tasks that are to be executed by machine in the cloud system must be less than the united VM for a time. Overloaded servers have to perform a less number of jobs. Here in our approach, we want to show a scheduling algorithm for balancing of loads and presentation with minimum execution time and makespan.