2025-2028 CURRICULUM OF DOCTORAL PROGRAM IN STATISTICS

2025-2028 Curriculum of Doctoral Program In Statistics

Vision

To become an educational institution for doctoral program and developing statistics and data science international standard that contribute to science and technology, particularly in the fields of Computing, Business and Industry, Economics and Finance, Social and Population, and Environment and Health.

Mission

  1. The mission of the Doctoral Program of Statistics is to contribute to the development of science and technology in the field of Statistics and Data Science and its applications to realize community welfare through educational activities, research, community service, and management based on information and communication technology.
  2. The mission of the Doctoral Program of Statistics in the field of education:
    • Organizing postgraduate education based on information and communication technology with international quality curriculum, lecturers, and learning methods to produce graduates of international quality in the field of Statistics and Data Science and its applications ;
    • Producing graduates who believe in and are devoted to God Almighty and;
    • To equip graduates with technology-based entrepreneurial knowledge.
  3. The mission of the Doctoral Program of Statistics in the field of research is to play an active role in the development of science and technology in the fields of Statistics and Data Science based on computation and its applications through internationally quality research activities in the fields of Industry, Business, Economics, Social, Health, and Environment.
  4. The mission of the Doctoral Program of Statistics in the field of community service is to utilize the available resources to participate in solving problems faced by society, industry, and government by prioritizing information and communication technology facilities.
  5. The mission of the Doctoral Program of Statistics in the field of management:
    • The management of the Study Program is carried out by paying attention to the principles of good governance supported by information and communication technology;
    • To Create a conducive atmosphere and providing full support to Students, Lecturers, Education Personnel to be able to develop themselves and provide maximum contribution to society, industry, science and technology; and

Program Educational Objective

  • To Produce Doctoral graduates of Statistics who are noble, have good and independent personalities, have professional and ethical abilities, have high integrity and responsibility, and are able to develop themselves and compete at the international level.

  • To Produce qualified Doctoral graduates of Statistics who can have careers as lecturers, researchers, consultants, and practitioners in the field of Statistics and Data Science based on computing who are able to produce research in the development of high-quality Statistics and Data Science with its application in the fields of Industry, Business, Economy, Social, Health, and Environment and publish it internationally.

  • To Produce Doctoral graduates of Statistics who have the character of being able to develop themselves with lifelong learning through research, training, and professional activities.

Program Learning Outcome (PLO)

PLO-1: Able to demonstrate attitudes and characters that reflect: being pious to God Almighty, having ethics and integrity, virtuous character, sensitive and concern with social and environmental issues, respecting cultural differences and pluralism, upholding law enforcement, prioritizing the interests of the nation and the wider community, through creativity and innovation, excellence, strong leadership, synergy, and other potentials to achieve maximum results.
PLO-2: Able to develop new theories/concepts/ideas and solve scientific and/or technological problems in their field through research with inter, multi, and transdisciplinary approaches to produce creative, original, and tested works in the form of dissertations and papers that have been approved published in reputable international journals.
PLO-3: Able to manage their own learning and develop themselves as personal lifelong learners 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 the principle of sustainability.
PLO-4: Able to develop Statistical Theory to address statistical problems.
PLO-5: Able to develop methodologies for collecting structured and unstructured data based on observation, experimentation, sampling, and simulation.
PLO-6: Able to design and evaluate advanced statistical computing systems or new algorithms for big-data processing, and to assess their effectiveness in comparison with conventional approaches.
PLO-7: Able to create and validate innovative statistical computing techniques and to critically examine their strengths and limitations in the context of complex real-world data.
PLO-8: Able to develop new statistical methods or theoretical models, and to evaluate their contributions to the advancement of statistical science and its applications through an interdisciplinary approach.
PLO-9: Able to integrate and advance computational and analytical statistical methods to address real-world problems in business, industry, economics, finance, social and sustainable development, environment, and health, as well as to evaluate their impacts on decision-making.

Graduate Profile

The curriculum of the Doctoral Program of Statistics is designed based on the learning outcomes of graduates, referring to the Indonesian National Qualifications Framework (KKNI) and the National Higher Education Standards (SN-DIKTI). Our tracking study reveals that our graduates work in the following fields:

  • Lecturers: Carry out the Tri Dharma of Higher Education in the Statistics Study Program or related study programs.
  • Statistical Experts and Researchers: Conduct research in the field of Statistics or in applied fields supported by statistical knowledge.
  • Practitioners in the Field of Statistics and Data Science: Professionals in various fields who require and use statistical and data science methods to support their work.

Regular Track

Distribution of Courses per Semester

SEMESTER I
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256101 Advanced Mathematical Statistics 3 link link
2 SS256102 Generalized Linear Models 3 link link
3 SS256103 Science Phylosophy and Statistics 3 link link
4 UG256101 English 2 link link
Total Credit 11

 

SEMESTER II
No. Course Code Course Name Credit Document
Syllabus Handbook
1 UG256201 Academic Writing 2 link link
2 SS256202 Dissertation I 4 link link
3 SS2562– Elective Course I 3 link link
Total Credit 9

 

SEMESTER III
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256301 Dissertation II 3 link link
2 SS256302 Publication I 2 link link
Total Credit 5

 

SEMESTER IV
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256401 Dissertation III 3 link link
2 SS256402 Publication II 3 link link
Total Credit 6

 

SEMESTER V
No. Cource Code Course Name Credit Document
Syllabus Handbook
1 SS256501 Dissertation IV 3 link link
2 SS256502 Publication III 4 link link
Total Credit 7

 

SEMESTER VI
No. Kode MK Nama Mata Kuliah (MK) Sks Dokumen
Silabus Handbook
1 SS256601 Dissertation V 6 link link
Total Credit 6

Research Track

Distribution of Courses per Semester

SEMESTER I
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256103 Science Philosophy and Statistics 3 link link
2 SS256173 Research Dissertation I 3 link link
3 UG256101 English 2 link link
4 UG256201 Academic Writing 2 link link
Total Credit 10

 

SEMESTER II
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256271 Research Publication I 5 link link
2 SS256272 Research Dissertation II 4 link link
Total Credit 9

 

SEMESTER III
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256371 Research Dissertation III 3 link link
Total Credit 3

 

SEMESTER IV
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256471 Research Dissertation IV 3 link link
2 SS256472 Research Publication II 5 link link
Total Credit 8

 

SEMESTER V
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256571 Research Dissertation V 3 link link
2 SS256572 Research Publication III 6 link link
Total Credit 9

 

SEMESTER VI
No. Kode MK Nama Mata Kuliah (MK) Credit Document
Syllabus Handbook
1 SS256671 Research Dissertation VI 5 link link
Total Credit 5

List of Elective Course

List of Elective Course
No. Course Code Course Name Credit Document
Syllabus Handbook
1 SS256211 Advanced Intensive Computational Statistics 3 link link
2 SS256212 Advanced Bayesian Analysis 3 link link
3 SS256221 Advanced Process Control Analysis 3 link link
4 SS256222 Advanced Optimization Methods 3 link link
5 SS256231 Advanced Econometrics 3 link link
6 SS256232 Advanced Time Series Analysis 3 link link
7 SS256233 Advanced Financial Statistics 3 link link
8 SS256234 Capita Selecta 3 link link
9 SS256241 Nonparametric and Semiparametric Regression 3 link link
10 SS256251 Advanced Multivariate Analysis 3 link link
11 SS256252 Advanced Categorical Data Analysis 3 link link
12 SS256253 Advanced Survival Analysis 3 link link
13 SS256254 Advanced Spatial Statistics 3 link link
14 SS256255 Generalized Structural Equation Modeling 3 link link
15 SS256256 Biostatistics and Epidemiology 3 link link
16 SS256257 Advanced Bioinformatic Statistics 3 link link
17 SS256258 Extreme Value Statistics 3 link link

Module Handbook

Regular Track

SEMESTER: I
No Course Code Course Name Credit
1 SS256101 Advanced Mathematical Statistics 3
2 SS256102 Generalized Linear Models 3
3 SS256103 Science Phylosophy and Statistics 3
3 UG256101 English 2
Total Credit 11

 

SEMESTER: II
No Course Code Course Name Credit
1 UG256201 Academic Writing 2
2 SS256202 Dissertation I 4
3 SS2562– Elective Course I 3
Total Credit 9

 

SEMESTER: III
No Course Code Course Name Credit
1 SS256301 Dissertation II 3
2 SS256302 Publication I 2
Total Credit 5

 

SEMESTER: IV
No Course Code Course Name Credit
1 SS256401 Dissertation III 3
2 SS256402 Publication II 3
Total Credit 6

 

SEMESTER: V
No Course Code Course Name Credit
1 SS256501 Dissertation IV 3
2 SS256502 Publication III 4
Total Credit 7

 

SEMESTER: VI
No Course Code Course Name Credit
1 SS256601 Dissertation V 6
Total Credit 6

Research Track

SEMESTER: I
No Course Code Course Name Credit
1 SS256103 Science Phylosophy and Research 3
2 SS256173 Research Dissertation I 3
3 UG256101 English 2
4 UG256201 Academic Writing 2
Total Credit 10

 

SEMESTER: II
No Course Code  Course Name Credit
1 SS256271 Research Publication I 5
2 SS256272 Research Dissertation II 4
Total Credit 9

 

SEMESTER: III
No Course Code  Course Name Credit
1 SS256371 Research Dissertation III 3
Total Credit 3

 

SEMESTER: IV
No Course Code  Course Name Credit
1 SS256471 Research Dissertation IV 3
2 SS256472 Research Publication II 5
Total Credit 8

 

SEMESTER: V
No Course Code  Course Name Credit
1 SS256571 Research Dissertation V 3
2 SS256572 Research Publication III 6
Total Credit 9

 

SEMESTER: VI
No Course Code  Course Name Credit
1 SS256671 Research Dissertation VI 5
Total Credit 5

List of Elective Course

List of Elective Course
No Course Code Elective Course Name Credit
1 SS256211 Advanced Intensive Computational Statistics 3
2 SS256212 Advanced Bayesian Analysis 3
3 SS256221 Advanced Process Control Analysis 3
4 SS256222 Advanced Optimization Methods 3
5 SS256231 Advanced Econometrics 3
6 SS256232 Advanced Time Series Analysis 3
7 SS256233 Advanced Financial Statistics 3
8 SS256234 Capita Selecta 3
9 SS256241 Nonparametric and Semiparametric Regression 3
10 SS256251 Advanced Multivariate Analysis 3
11 SS256252 Advanced Categorical Data Analysis 3
12 SS256253 Advanced Survival Analysis 3
13 SS256254 Advanced Spatial Statistics 3
14 SS256255 Generalized Structural Equation Modeling 3
15 SS256256 Biostatistics and Epidemiology 3
16 SS256257 Advanced Bioinformatic Statistics 3
17 SS256258 Extreme Value Statistics 3

Dissertation Guidebook

Pedoman-Disertasi_2018

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