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 523 masters of science until the 128 st graduation period (September 2023). Currently, the lecturers in PSMM consist of 6 professors and 24 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.
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Vision
Becoming a Master of Mathematics Study Program with an international reputation in the fields of analysis, algebra and computation for theoretical and applied development, especially in industry and marine with an environmental perspective
Mission
Mission of Education
Organizing master mathematics education to produce graduates of international quality and mastering concepts in the fields of analysis, algebra, and computation and their applications.
To produce masters of mathematics who believe in and fear God Almighty
Mission of Research
Actively involved in the development of mathematics and its application through international quality research activities, especially in the fields of algebra, analysis, modeling and computation.
Mission of Community Service
Empowering departmental resources to play an active role in solving problems faced by society, industry and government by integrating analysis, algebra, modeling and computation.
Mission of Management
Developing networks and synergizing with domestic and foreign universities, industry, society, and government in implementing the Tridharma of Higher Education in the field of mathematics and its applications.
Improving the competence of lecturers and education staff so that they are more creative and professional in carrying out their duties
Program Educational Objectives
Produce graduates who can have careers as academics, researchers, practitioners in the industrial sector who can use their knowledge, skills and experience to solve real problems when carrying out their professional practice.
Individuals who are able to develop research networks related to the application of mathematics to real life problems, especially in the fields of industry, energy, maritime, finance and information technology, as well as producing innovative mathematical works based on local wisdom
Individuals who are able to develop their careers, can work individually and in teams, have a leadership and managerial skill.
Alumni Profile
The graduates of MoMath are expected to work in the following areas:
Academics
Practitioners (Industry and Government)
Research Associate
Data Scientist
Financial and Banking Analyst
Program Learning Outcomes
Attitude
Able to demonstrate attitudes and character that reflect: devotion to God Almighty, ethics and integrity, noble character, sensitivity and care for social and environmental problems, respecting cultural differences and pluralism, upholding law enforcement prioritizing the interests of the nation and wider community, through creativity and innovation, excellence, strong leadership, synergy, and other potential to achieve maximum results.
General Skills
Able to develop and solve scientific and technological problems in their scientific field through research with an inter- or multidisciplinary approach to produce innovative and tested work in the form of theses and papers that have been accepted in accredited national scientific journals or accepted at reputable international conferences
Able to manage one's own learning, and develop oneself as a lifelong learner to compete at national and international levels, in order to make a real contribution to solving problems by implementing information and communication technology and paying attention to sustainability principles.
Special Skills
Able to solve mathematical problems by applying basic mathematical statements, methods and calculations
Able to analyze mathematical problems in one of the areas: analysis, algebra, modeling, systems, optimization or computational science
Able to work and research collaboratively on mathematical problems in the fields of pure mathematics, applied mathematics or computational science
Able to communicate and present mathematical ideas clearly and coherently, both in writing and orally
Knowledge
Able to identify and explain the quality of complex mathematical problems
Curriculum
In the 2023 curriculum, the required credits on Master students was set at 36 credits scheduled for 4 (four) semesters and no later than 8 (eight) semesters including completion of thesis (2019 ITS Academic Regulations). The Study Program has three fields of interest, namely Applied Analysis and Algebra, Applied and Industrial Mathematics, as well as Data and Computing Science. The course is prepared based on the expected competencies from graduates of the Study Program, which are divided into compulsory courses, compulsory courses for each field of interest and elective courses for each field of interest. In the following table, the curriculum structure is presented based on the distribution of study load components and interest fields. The field of interest is determined when students register.
Table 1. Curriculum Structure
Study Component
Credits
Information
Compulsory Courses
8
Functional Analysis (3 Credits)
Matrix Computations (3 Credits)
Research and Writing in Mathematics (2 Credits)
Compulsory Courses for each Field of Interest
9
Compulsory Courses for Applied Analysis and Algebra consist of:
Approximation Theory (3 Credits)
Module Theory (3 Credits)
Algebraic Graph (3 Credits)
Compulsory Courses for Applied and Industrial Mathematics choose 3 couses among the following 4 courses:
Mathematical Modeling (3 Credits)
Dynamic Systems (3 Credits)
Numerical Computation (3 Credits)
Calculus of Variations (3 Credits)
Compulsory Courses for Data and Computing Science consist of:
Computer Vision (3 Credits)
Machine Learning (3 Credits)
Data Science Concepts (3 Credits)
Thesis
8
Elective Courses
11
Students must take 11 credits of elective courses in their field of interest.
Total
36
Table 2. The recommended scheme of taking courses in 4 semesters for each field of interest
Field of Interest
Applied Analysis and Algebra
Applied and Industrial Mathematics
Data and Computing Science
Semester 1
Compulsory Courses (8 Credits)
Functional Analysis (3 Credits)
Matrix Computations (3 Credits)
Research and Writing in Mathematics (2 Credits)
Compulsory Courses in their Field of Interest (3 Credits)
Semester 2
Compulsory Courses in their Field of Interest (6 Credits)
Elective Courses in their Field of Interest (3 Credits)
Semester 3
Elective Courses in their Field of Interest (8 Credits)
Semester 4
Thesis (8 SKS)
Table 3. Elective Courses in each Field of Interest
The amount of credits after semester 1 is determined by the grade in the previous semester:
If the grade in the previous semester is less than 3,00 then the maximum credits are 12
If the grade in the previous semester is greater than or equal to 3,00 then the maximum credits are 15
ECTS
The minimum study load of students in MoMath is 36 SKS, which is equivalent to 170 minutes self study and attendance-based learning every week. In every semester, there are 16 weeks of lecture or other scheduled activities, including evaluation. The study load and other required activities are equivalent to 99.96 ECTS, where 1 ECTS equals 25 working hours. The other required activities (outside the study load) are:
Some elective courses in Semester 2 and 3 requires the students to work on a specific problem, write the results in a technical report and present the results in an internal seminar. The activities are equivalent to 3 SKS.
As a requirement for graduation, each student must publish some results of the thesis to an international conference or a journal. The activities are preparing the paper, writing the paper, revising the paper, preparing the camera-ready version, presenting the paper. The activities are equivalent to 5 SKS.
There are some activities in thesis, which take some time, such as writing the proposal, presenting the proposal, revising the proposal, presenting the results in an internal seminar. The activities are equivalent to 5 SKS.
The conversion table between the minimum study load and other required activities, from SKS to ECTS is described in the following table:
The research-track master's program is designed to facilitate master's-level education through a research-based learning process. This program spans a two-year period with a study load of 36 credits, comprising 12 credits of coursework, research, and thesis publication. The courses taken are those that support the thesis research.
Table 4. Curriculum Structure of the Master Program in Mathematics (Research Track)
Semester
Course Name
SKS
Information
1
Course on Recognition of Prior Learning
3
Writing a Thesis Proposal
3
Supervision
Thesis-Supporting Course
6
2
Thesis I
4
Supervision
Publication I
6
International Conference
3
Thesis II
6
Proposal Seminar and Thesis Defense
4
Publication II
8
International Journal
Recognition of Prior Learning—hereinafter abbreviated as RPL—is the recognition of an individual's learning outcomes—acquired through formal, non-formal, or informal education and/or work experience—for the purpose of formal education. The RPL and thesis-support courses in the Research Track are identical to the courses in the Regular Track.
