Tuesday, September 13, 2022

Mathematical Modelling (MM)

This course discusses the knowledge of theories related to mathematical modeling required at the undergraduate level of the mathematics study program. An understanding of the basic concepts of modeling, systems of differential equations, various models, model approaches, and their application using MATLAB software is provided as a learning tool before implementing mathematical modeling in real life. Furthermore, problems are given as practice material in constructing and making programs to solve problems mathematically and systematically. Some examples of relevant applications are also given so that students understand the application of the concepts learned so that they can foster creativity and reasoning in students in solving a problem. 

You can download this lecture file here. For more information, don't hesitate to contact my email.

References:
  • E.A. Bender. 1978. An Introduction to Mathematical Modeling. John Wiley & Sons.
  • C. L. Dym. 2004. Principles of Mathematical Modeling. Elsevier.
  • M.W. Hirsch, S. Smale, and R. L. Devaney. 2013. Differential Equations, Dynamical Systems, and An Introduction to Chaos. Elsevier.

Thursday, June 2, 2022

Optimization Methods (OM)

This course provides explanations to methods for solving optimization problems. Explanations and variations of optimization problems are deepened as a provision for analyzing problems and pouring them into mathematical formulations. Both linear and non-linear optimization methods such as the Steepest-Descent method, Lagrange multiplier, least-squares, GA, PSO, and SDO are presented to enrich students' insight. Furthermore, problems are given as practice material in constructing and making simulations to solve problems mathematically. Some examples of relevant applications in defense are also given to understand the application of the concepts learned so as to foster creativity and reasoning in students for solving problems.


You can download this lecture file here. For more information, don't hesitate to contact my email.

References:
  • P. R. Adby and M. A. H. Dempster. 1974. Introduction to Optimization Methods. London Chapman and Hall.
  • Urmila Diwekar. 2000. Introduction to Applied Optimization. Springer.
  • E. M. T. Hendrix and B. G. Toth. 2010. Introduction to Nonlinear and Global Optimization. Springer.

Monday, February 21, 2022

Dynamical Systems (DS)

This course provides knowledge about the dynamic behavior of systems in the form of ordinary differential equations, both linear and non-linear by conducting stability analysis and system bifurcation. It also includes discussion of orbital analysis, phase portraits, fixed points, periodic solutions, and manifold invariants. Furthermore, problems are given as practice material in constructing and making simulations to solve problems mathematically. Some examples of relevant applications in defense are also given to understand the application of the concepts learned so as to foster creativity and reasoning in students for solving problems.


You can download this lecture file here. For more information, don't hesitate to contact my email.

References:
  • M.W. Hirsch, S. Smale, and R.L. Devaney. 2013. Differential Equations, Dynamical Systems, and An Introduction to Chaos. Elsevier.
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Wednesday, September 1, 2021

Integral Calculus (IC)

The topics in this lecture consist of integrals, integral applications, transcendent functions, integration techniques, indefinite forms of limit functions, improper integrals, and sequences and series of real numbers. This course provides various integral concepts and provides direction for solving problems related to lecture topics and their applications. 

You can download this lecture file here. For more information, don't hesitate to contact my email.

References:

  • Dale Varberg, Edwin Purcell, and Steve Rigdon. 2007. Calculus. Prentice Hall, 9th ed.
  • Thomas. 2005. Calculus. Pearson Education, 11th ed.
  • James Stewart. 1999. Calculus. Brooks/Cole Publishing Company, 4th ed.

Algorithms and Programming (AP)

This course discusses the theories related to algorithms and mathematical programming required at the undergraduate level of the mathematics study program. An understanding of the concept of algorithms, making flow charts, as well as an introduction to the MATLAB software is given as a learning tool before starting to make programs. Furthermore, problems are given as practice material in constructing and making programs to solve problems mathematically. Some examples of relevant applications are also given to understand the application of the concepts learned so as to foster creativity and reasoning in students in solving a problem.

You can download this lecture file here. For more information, don't hesitate to contact my email.

References:
  • S.R. Otto and J.P. Denier. 2005. An Introduction to Programming and Numerical Methods in MATLAB. Springer.
  • Alexander Stanoyevitch. 2005. Introduction to MATLAB with Numerical Preliminaries. A John Wiley & Sons, Inc.
  • Alex F. Bielajew. 2010. Introduction to Computers and Programming using C++ and MATLAB. University of Michigan.

Tuesday, August 31, 2021

Basic Mathematic (BM)

This course discusses the theories related to the basics of mathematics required at the undergraduate level of the mathematics study program. Concepts and theories regarding real numbers, function operations, limits, continuity, derivatives, integrals, and transcendent functions are given as the basis for stimulating systematic, critical, and logical thinking patterns. Some examples of the application of these concepts are also given to understand the use of the concepts learned so that they can foster creativity and reasoning in solving a problem.

You can download this lecture file here. For more information, don't hesitate to contact my email.

References:

  • Dale Varberg, Edwin Purcell, and Steve Rigdon. 2007. Calculus. Prentice Hall, 9th ed.
  • Thomas. 2005. Calculus. Pearson Education, 11th ed.
  • James Stewart. 1999. Calculus. Brooks/Cole Publishing Company, 4th ed.

Monday, August 30, 2021

Ordinary Differential Equation (ODE)

This course discusses the theories related to mathematics required at the undergraduate level of the mathematics study program. Concepts and theories regarding Ordinary Differential Equations (ODE) and several methods for solving various types of ODEs are discussed in this lecture. In addition, a more detailed explanation will be presented regarding the initial value problem, first-order ODE, homogeneous and non-homogeneous linear ODE, and Laplace transformation. Several examples of the application of the concept are also given so that undergraduate students understand its use so that it can spur creativity and students' thinking in solving a problem, especially in the field of national defense.

You can download this lecture file here. For more information, don't hesitate to contact my email.

References:

  • William E. Boyce, Richard C. DiPrima, and Douglas B. Meade. 2017. Elementary Differential Equations and Boundary Value Problems. Wiley, 11th ed.

  • H.J. Lee and W.E. Schiesser. 2004. Ordinary and Partial Differential Equation Routines in C, C++, Fortran, Java, Maple, and MATLAB. Chapman & Hall / CRC. 1th ed.

  • Erwin Kreyzig, Herbert Kreyzig, and Edward J. Norminton. 2011. Advanced Engineering Mathematics. Wiley, 10th ed.