2023-2028 CURRICULUM OF DOCTORAL PROGRAM IN STATISTICS

2023-2028 Curriculum of Doctoral Program In Statistics

Vission

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 Objectives

  • 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.

Programme 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 do in-depth study and apply Mathematical Statistics to solve statistical problems
PLO-5: Able to use modern computing devices to solve statistical problems
PLO-6: Able to apply and develop computational techniques to solve statistical problems
PLO-7: Able to apply statistical methods appropriately as well as evaluate and develop them to analyze theoretical and real problems
PLO-8: Able to apply Computing-based Business, Industrial, Financial Economics, Social-Population, Environmental, or Health Statistics methods to real problems

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
1 SS236101 Advanced Mathematical Statistics 3
2 SS236102 Generalized Linear Models 3
3 SS236103 Science Phylosophy and Statistics 3
Total Credit 9

 

SEMESTER: II
No Course Code Course Name Credit
1 SS236201 Scientific Publication and Seminar 2
2 SS236202 Disertation I 3
3 SS2362– Elective Course I 3
Total Credit 8

 

SEMESTER: III
No Course Code Course Name Credit
1 SS236301 Disertation II 4
2 SS236302 Publication I 2
Total Credit 6

 

SEMESTER: IV
No Course Code Course Name Credit
1 SS236401 Disertation III 3
2 SS236402 Publication II 4
Total Credit 7

 

SEMESTER: V
No Course Code Course Name Credit
1 SS236501 Disertation IV 3
2 SS236502 Publication III 4
Total Credit 7

 

SEMESTER: VI
No Course Code Course Name Credit
1 SS236601 Disertation V 5
Total Credit 5

RESEARCH TRACK

Distribution of Courses per Semester

SEMESTER: I
No Course Code Course Name Credit
1 SS236171 Science Phylosophy and Research 3
2 SS236172 Research Seminar 3
3 SS236173 Research Disertation I 3
Total Credit 9

 

SEMESTER: II
No Course Code Course Name Credit
1 SS236271 Research Publication I 5
2 SS236272 Research Disertation II 3
Total Credit 8

 

SEMESTER: III
No Course Code Course Name Credit
1 SS236371 Research Disertation III 3
Total Credit 3

 

SEMESTER: IV
No Course Code Course Name Credit
1 SS236471 Research Disertation IV 3
2 SS236472 Research Publication II 5
Total Credit 8

 

SEMESTER: V
No Course Code Course Name Credit
1 SS236571 Research Disertation V 3
2 SS236572 Research Publication III 6
Total Credit 9

 

SEMESTER: VI
No Course Code Course Name Credit
1 SS236671 Research Disertation VI 5
Total Credit 5

List of Elective Course

No Course Code Course Name Credit
1 SS236211 Advanced Intensive Computational Statistics 3
2 SS236212 Advanced Bayesian Analysis 3
3 SS236221 Advanced Process Control Analysis 3
4 SS236222 Advanced Optimation Methods 3
5 SS236231 Advanced Econometrics 3
6 SS236232 Advanced Time Series Analysis 3
7 SS236233 Advanced Financial Statistics 3
8 SS236234 Capita Selecta 3
9 SS236241 Nonparametric and Semiparametric Regression 3
10 SS236251 Advanced Multivariate Analysis 3
11 SS236252 Advanced Categorical Data Analysis 3
12 SS236253 Advanced Survival Analysis 3
13 SS236254 Advanced Spatial Statistics 3
14 SS236255 Generalized Structural Equation Modeling 3
15 SS236256 Biostatistics and Epidemiology 3
16 SS236257 Advanced Bioinformatic Statistics 3
17 SS236258 Extreme Value Statistics 3

Module Handbook

REGULAR TRACK

SEMESTER: I
No Course Code Course Name Credit
1 SS236101 Advanced Mathematical Statistics 3
2 S236102 Generalized Linear Models 3
3 SS236103 Science Phylosophy and Statistics 3
Total Credit 9

 

SEMESTER: II
No Course Code Course Name Credit
1 SS236201 Scientific Publication and Seminar 2
2 SS236202 Disertation I 3
3 SS2362– Elective Course I 3
Total Credit 8

 

SEMESTER: III
No Course Code Course Name Credit
1 SS236301 Disertation II 4
2 SS236302 Publication I 2
Total Credit 6

 

SEMESTER: IV
No Course Code Course Name Credit
1 SS236401 Disertation III 3
2 SS236402 Publication II 4
Total Credit 7

 

SEMESTER: V
No Course Code Course Name Credit
1 SS236501 Disertation IV 3
2 SS236502 Publication III 4
Total Credit 7

 

SEMESTER: VI
No Course Code Course Name Credit
1 SS236601 Disertation V 5
Total Credit 5

RESEARCH TRACK

SEMESTER: I
No Course Code Course Name Credit
1 SS236171 Science Phylosophy and Research 3
2 SS236172 Research Seminar 3
3 SS236173 Research Disertation I 3
Total Credit 9

 

SEMESTER: II
No Course Code  Course Name Credit
1 SS236271 Research Publication I 5
2 SS236272 Research Disertation II 3
Total Credit 8

 

SEMESTER: III
No Course Code  Course Name Credit
1 SS236371 Research Disertation III 3
Total Credit 3

 

SEMESTER: IV
No Course Code  Course Name Credit
1 SS236471 Research Disertation IV 3
2 SS236472 Research Publication II 5
Total Credit 8

 

SEMESTER: V
No Course Code  Course Name Credit
1 SS236571 Research Disertation V 3
2 SS236572 Research Publication III 6
Total Credit 9

 

SEMESTER: VI
No Course Code  Course Name Credit
1 SS236671 Research Disertation VI 5
Total Credit 5

List of Elective Course

No Course Code Elective Course Name Credit
1 SS236211 Advanced Intensive Computational Statistics 3
2 SS236212 Advanced Bayesian Analysis 3
3 SS236221 Advanced Process Control Analysis 3
4 SS236222 Advanced Optimation Methods 3
5 SS236231 Advanced Econometrics 3
6 SS236232 Advanced Time Series Analysis 3
7 SS236233 Advanced Financial Statistics 3
8 SS236234 Capita Selecta 3
9 SS236241 Nonparametric and Semiparametric Regression 3
10 SS236251 Advanced Multivariate Analysis 3
11 SS236252 Advanced Categorical Data Analysis 3
12 SS236253 Advanced Survival Analysis 3
13 SS236254 Advanced Spatial Statistics 3
14 SS236255 Generalized Structural Equation Modeling 3
15 SS236256 Biostatistics and Epidemiology 3
16 SS236257 Advanced Bioinformatic Statistics 3
17 SS236258 Extreme Value Statistics 3

Dissertation Guide Book

Pedoman-Disertasi_2018

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