Master Degree

Master Degree

Master of Mathematics Study Program (PSMM) has produced graduates who have contributed very significantly to the development of human resources, especially in eastern Indonesia. This is supported by the knowledge in analysis, algebra and computing related to the development of applied mathematics. Since its establishment in 2003, PSMM has graduated 472 masters of science until the 121st graduation period (March 2019). Currently, the lecturers in PSMM consist of 4 professors and 15 doctors who are competent in the fields of Max-Plus Algebra, Data Science, Graph Theory, Computational Fluid Dynamics, Dynamic Systems, Financial Mathematics, Bioinformatics, Systems Theory, Data Assimilation and Digital Image Processing. PSMM has collaborated with several universities, both within and outside the country, for example Shibaura Institute of Technology (Japan), University of Oxford (UK), University of Essex (UK), Technische Universiteit Delft (The Netherlands) and Universiti Malaysia Pahang (Malaysia). Since 2019, PSMM has been accredited A with SK number 4332/SK/BAN-PT/Akred/M/XI/2019.


Menjadi program studi unggulan dalam pendidikan magister matematika yang bereputasi internasional, terutama dalam bidang analisis, aljabar, dan komputasi untuk mendukung dan mengembangkan matematika terapan.


  1. Menyelenggarakan pendidikan magister matematika untuk menghasilkan lulusan yang bermoral, menguasai pokok-pokok bidang analisis, aljabar, dan komputasi serta penerapannya.
  2. Mengembangkan kerja sama nasional dan internasional di bidang pendidikan dan penelitian matematika.
  3. Menumbuhkan dan menjaga moral dan etika akademik.
  4. Meningkatkan kompetensi dosen agar lebih kreatif dan professional dalam menjalankan tugas


  1. Menghasilkan Magister Matematika berintegritas tinggi yang tanggap terhadap perubahan dan kemajuan ilmu pengetahuan dan teknologi.
  2. Menghasilkan Magister Matematika yang mempunyai kompetensi dalam bidang Analisis dan Aljabar Terapan, Pemodelan dan Simulasi, serta Ilmu Komputer.
  3. Menghasilkan Magister Matematika yang mempunyai kemampuan, motivasi dan perilaku belajar serta etos kerja yang tinggi dalam penelitian dan pengembangan keilmuan matematika.
  4. Menghasilkan Magister Matematika yang mampu memberikan kontribusi dalam menyelesaikan masalah-masalah nyata, khususnya yang berkaitan dengan bidang energi, transportasi, lingkungan, kelautan dan industri, serta teknologi informasi.


In the 2018 curriculum, the study load is 36 credits which are scheduled for 4 (four) semesters and a maximum of 8 (eight) semesters including the completion of a thesis (Academic Regulations of ITS 2019). Compulsory courses consist of 4 courses (11 credits), namely Module Theory, Functional Analysis, Mathematical Modeling and Numerical Computation.

The study load of the master program is at least 36 credits and at most 50 credits are scheduled for 4 (four) semesters and can be taken in less than 4 (four) semesters and for a maximum of 10 (ten) semesters including thesis, after an undergraduate program, or equivalent (Kepmendiknas No. 232 / U / 2000).

The study load that must be taken to complete studies at PSMM-ITS is 36 credits, with a period of 4 semesters.

All courses are grouped as follows:

  • Compulsory courses: Module Theory (3 credits), Functional Analysis (3 credits), Mathematical Modeling (3 credits) and Numerical Computation (2 credits).
  • The compulsory courses for each group is 6 credits: Approximate Theory (3 credits), Max-Plus Algebra (3 credits), Dynamic Systems (3 credits), Stochastic Calculus (3 credits), Computational Algorithms (3 credits), Mathematics of Machine Learning (3 credits).
  • Elective courses in the Applied Analysis and Algebra group: Discrete Transformation (3 credits), Graph Algebra (3 credits), Wavelets and Applications (3 credits), Graphs and Applications (2 credits), Topics in Applied Analysis (2 credits), Topics in Applied Algebra (2 credits) .
  • Elective courses in Modeling and Simulation group: Systems and Control (3 credits), Computational Fluid Dynamics (3 credits), Dynamic Optimization (3 credits), Financial Mathematics (3 credits), Biological Mathematics (3 credits), Data Assimilation (3 credits), Derivative Mathematics (3 credits), Risk Analysis (3 credits), Advanced Partial Differential Equations (2 credits), Inverse Problems (2 credits), Topics in Mathematical Modeling (2 credits), Topics in Optimization (2 credits).
  • Elective courses in Computer Science group: Formal Verification (3 credits), Digital Image Processing and Analysis (3 credits), Computational Biology (3 credits), Theory of Computations (3 credits), Fuzzy Systems (2 credits), Topics in Computations (2 credits).

Expexted Learning Outcomes

  1. fear of God Almighty and able to demonstrate a religious attitude
  2. uphold the values of humanity in the line of duty based on religion, morals, and ethics
  3. contribute to improve the quality of life of the society, the nation, the country and the progress of civilization based on Pancasila
  4. role as citizens who take pride and love of the country, had nationalism and sense of responsibility to the state and nation
  5. appreciate cultural diversity, religions, and beliefs, as well as the opinion or original findings of others
  6. in collaboration and social sensitivity and concern for people and the environment
  7. obey the law and discipline in the life of society and state
  8. internalize the values, norms, and academic ethics
  9. show an attitude responsible for the work in the field of expertise independently
  10. internalize the spirit of self-reliance, innovation, effort and entrepreneurship
  11. earnestly tries to achieve maximum results
  12. working together in order to take full advantage of the potential possessed
  1. able to develop logical thinking, critical, systematic, and creatively through scientific research, the creation of the design or work of art in the field of science and technology that observe and apply the value of the humanities according to their expertise, develop scientific conception and the results of the study by the rules, ordinances, and scientific ethics in the form of a thesis or other equivalent form, and uploaded to the university website, as well as papers that have been published in national accredited scientific journals or accepted in international journals
  2. able to perform appropriate validation studies academic or assessments in their areas of expertise in solving problems in relevant communities or industries through the development of their knowledge and expertise
  3. able to develop ideas, the result of thinking, and scientific arguments in a responsible manner and on the basis of academic ethics, as well as communicating through the media to the academic community and wide community
  4. able to identify field of science that became the object of research and position into a road map research were developed through an interdisciplinary or multidisciplinary approach
  5. able to take decisions in the context resolve the issue of science and technology development that observe and apply the value of the humanities based studies or experimental analysis of the information and data
  6. able to manage, develop and maintain networking with colleagues, peers in the institution and the wider research community
  7. can improve the learning capacity independently
  8. capable of documenting, storing, securing, and rediscover the data research in order to ensure the validity and prevent plagiarism
  9. able to develop themselves and compete at national and international level
  10. able to implement an environmental insight in developing knowledge
  11. able to implement information and communication technologies in the context of the implementation of the work
  1. Able to master and develop mathematical concepts in analysis and applied algebra
  2. Able to master and develop mathematical concepts in modeling and optimization system
  3. Able to master and develop mathematical concepts in mathematics computing
  4. Being able to follow knowledge of recent/latest issues, advanced, and frontier in mathematics
  5. Be able to formulate a real problem in mathematical models
  6. Being able to construct a computational algorithm to resolve issues related
  7. recent / lates issues, advanced, and frontier in mathematics
  1. Being able to apply mathematical subjects areas of analysis and applied algebra to support research in mathematics and other fields
  2. Being able to apply mathematical subjects field of Modeling and Optimization System to support environmental, residential, marine, energy, or information technology research
  3. Being able to apply mathematical subjects Computing field to support environmental research, residential, marine, energy, or information technology
  4. able to conduct a study on the accuracy of a mathematical model for an inter- or multi-disciplinary problem
  5. able to assest/simulate numerically to know the performance of a computing method
  6. capable of deepening or wider of sciencetific mathematics by producing models / methods / development of a tested and innovative theory

List of Courses

No. Course Code Course Name Credit
1. KM185101 Module Theory 3
2. KM185102 Functional Analysis 3
3. KM185103 Mathematical Modeling 3
4. KM185104 Numerical Computing 2
Total credits 11
No. Course Code Course Name Credit
1. KM1852xx Compulsary Courses 6
2. KM1852xx Elective Courses 3
Total credits 9
No. Course Code Course Name Credit
1. KM1853xx Elective Courses 8
Total credits 8
No. Course Code Course Name Credit
1. KM185401 Thesis 8
Total credits 8
No. Code Compulsary Courses Credits
1. KM185211 Approximation Theory 3
2. KM185212 Max-Plus Algebra 3
3. KM185221 Dynamical Systems 3
4. KM185222 Stochastics Calculus 3
5. KM185231 Computational Algorithm 3
6. KM185232 Mathematics of Machine Learning 3
No. Code Elective Courses Credits
1. KM185271 Discrete Transformation 3
2. KM185272 Formal Verification 3
3. KM185273 Systems and Controls 3
4. KM185274 Computational Fluid Dynamics 3
5. KM185275 Dynamical Optimization 3
6. KM185276 Financial Mathematics 3
7. KM185277 Digital Image Processing and Analysis 3


No. Code Elective Courses Credits
1. KM185372 Mathematical Biology 3
2. KM185373 Data Assimilation 3
3. KM185374 Computational Biology 3
4. KM185375 Mathematics of Derivatives 3
5. KM185376 Risk Analysis 3
6. KM185377 Graph Algebra 3
7. KM185378 Theory of Computing 3
8. KM185379 Wavelet and Applications 3
9. KM185380 Advanced Partial Differential Equations 2
10. KM185381 Inverse Problems 2
11. KM185382 Fuzzy Systems 2
12. KM185383 Graph and Applications 2
13. KM185384 Topics of Applied Analysis 2
14. KM185385 Topics of Computing 2
15. KM185386 Topics of Mathematical Modeling 2
16. KM185387 Topics of Applied Algebra 2
17. KM185388 Topics of Optimization 2