Master

Master Degree

Vision

To become an educational institution for Master level 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 Master Program of Statistics is to contribute in the development of science and technology in the fields of statistics, data science, and its applications to realize public welfare through education, research, community service, and management based on information and communication technology.
  2. The mission of the Master Program of Statistics in Education field:
    • organize Master study program based on information and communication technology to produce international quality graduates in the fields of statistics, data science, and their applications;
    • produce graduates who believe and fear God Almighty and have entrepreneurial knowledge.
  3. The mission of the Department of Statistics in research is to play an activate role in the development of science and technology in the field of statistics, data science, and their applications through international quality research activities.
  4. The mission of the Department of Statistics in community service is to utilize the resources of the department to play an active role in solving problems faced by society, industry, and government.
  5. The mission of the Department of Statistics in management:
    • professional management of resources in the department in organizing Tridharma Perguruan Tinggi based on information and communication technology;
    • develop networks and synergize with domestic and foreign universities, industry, society, and government in organizing Tridharma Perguruan Tinggi.

Program Educational Objectives

  1. The Program Educational Objectives (PEO) reflect the achievement of graduates of study programs after three years. The PEO of Master of Statistics degree program (MSP) is to produce qualified Masters in Statistics so that they can have careers as lecturers, researchers, and practitioners in the field of Statistics and Data Science with the following characteristics:
    • Able to use and develop knowledge, skills, and competence professionally to solve problems in their profession using an interdisciplinary approach [PEO-1: professional accomplishment].
    • Has a character who wants to learn throughout his life so that he/she can develop himself through further studies at the Doctoral level at home and abroad, research, training, and professional activities [PEO-2: academic accomplishment].
    • Have a good and independent personality, have professional abilities and professional ethics, have high integrity, responsibility and can develop a network system [PEO-3: social accomplishment].

Programme Learning Outcome

PLO-1: Able to apply knowledge of statistical theory, mathematics, and computation in various fields and develop them
PLO-2: Able to design and implement data collection with the correct methodology
PLO-3: Able to identify, formulate, and analyze data with appropriate statistical methods and interpret them to solve statistical problems in various applied fields
PLO-4: Able to conduct studies and compare the strengths and weaknesses of a statistical methodology (method or model) in solving a multidisciplinary system/problem in statistics and data science, both using mathematical proof and using computational techniques and modern computing tools.
PLO-5: Able to communicate effectively and work together in interdisciplinary and multidisciplinary teams
PLO-6: Able to apply an attitude of responsibility, professional ethics, and uphold human values
PLO-7: Able to motivate oneself to think creatively and learn lifelong

Profile of Graduates

The curriculum of Master Degree Program of Statistics is arranged based on the learning achievements of graduates that refer to the Indonesian National Qualification Framework (KKNI) and National Standard of Higher Education (SN-DIKTI). Our tracer study reveals that our graduates work in the following areas:

  • Lecturer: applying knowledge and skill in statistics to give a lecture on statistical courses and related fields;
  • Statistician and researcher: applying knowledge and skill in statistics to support or conduct research in various fields, including the governmental institution;
  • Data scientist and information technology: applying knowledge and skill of statistical method, computational statistics, and statistical machine learning for data processing and data analysis as well as its visualization;
  • Finance, banking, and insurance: applying knowledge and skill of statistical methods in finance, banking, and insurance;
  • Further study in a doctoral program, and
  • Entrepreneur: applying the knowledge and skill of statistical thinking to business and entrepreneurship

List Of Courses For Master Program

SEMESTER: I
No. Course Code Course Name Credit
1 KS185111 Probability Theory 3
2 KS185112 Sampling Methods 3
3 KS185113 Linear Model 3
4 Elective Course 1 3
Total credit 12

 

SEMESTER: II
No. Course Code Course Name Credit
1 KS185211 Statistika Inferensia / Inference Statistics 3
2 KS185212 Analisis Multivariat / Multivariate Analysis 3
3 Elective Course 2 3
4 Elective Course 3 3
Total credit 12

 

SEMESTER: III
No. Course Code Course Name Credit
1 KS185311 Analisa Data / Data Analysis 3
Thesis proposal*
Total credit 3*

 

SEMESTER: IV
No. Course Code Course Name Credit
1 KS185411 Thesis 9
Total credit 9

List Of Elective Courses

No Course Code Course Name Credit
Elective Courses
1 KS185131 Experimental Design 3
2 KS185132 Statistical Process Control 3
3 KS185133 Simulation Technique 3
4 KS185134 Survival Analysis 3
5 KS185135 Population Study 3
6 KS185136 Econometrics 3
7 KS185137 Stochastic Process 3
8 KS185138 Statistical Analysis 3
9 KS185139 Quality Design 3
10 KS185231 Bayesian Analysis 3
11 KS185232 Meta Analysis 3
12 KS185233 Market Research 3
13 KS185234 Official Statistics 3
14 KS185235 Qualitative Data Analysis 3
15 KS185236 Nonparametric Regression 3
16 KS185237 Time Series Analysis 3
17 KS185238 Statistical Machine Learning 3
18 KS185239 Enterprise Data Analytics 3
19 KS185240 Advance Data Organization 3
20 KS185331 Reliability Analysis 3
21 KS185332 Intensive Computational Statistics 3
22 KS185333 Spatial Statistics 3
23 KS185334 Financial Statistics 3
24 KS185335 Research Method and Colloquium 3
25 KS185336 Consulting Statistics 3
26 KS185337 Capita Selecta 3

Module Handbook

SEMESTER: I
No. Course Code Course Name Credit
1 KS185111 Probability Theory 3
2 KS185112 Sampling Methods 3
3 KS185113 Linear Model 3
4 Elective Course 1 3
Total credit 12

 

SEMESTER: II
No. Course Code Course Name Credit
1 KS185211 Statistika Inferensia / Inference Statistics 3
2 KS185212 Analisis Multivariat / Multivariate Analysis 3
3 Elective Course 2 3
4 Elective Course 3 3
Total credit 12

 

SEMESTER: III
No. Course Code Course Name Credit
1 KS185311 Analisa Data / Data Analysis 3
Thesis proposal*
Total credit 3*

 

SEMESTER: IV
No. Course Code Course Name Credit
1 KS185411 Thesis 9
Total credit 9

List Of Elective Courses

No Course Code Course Name Credit
Elective Courses
1 KS185131 Experimental Design 3
2 KS185132 Statistical Process Control 3
3 KS185133 Simulation Technique 3
4 KS185134 Survival Analysis 3
5 KS185135 Population Study 3
6 KS185136 Econometrics 3
7 KS185137 Stochastic Process 3
8 KS185138 Statistical Analysis 3
9 KS185139 Quality Design 3
10 KS185231 Bayesian Analysis 3
11 KS185232 Meta Analysis 3
12 KS185233 Market Research 3
13 KS185234 Official Statistics 3
14 KS185235 Qualitative Data Analysis 3
15 KS185236 Nonparametric Regression 3
16 KS185237 Time Series Analysis 3
17 KS185238 Statistical Machine Learning 3
18 KS185239 Enterprise Data Analytics 3
19 KS185240 Advance Data Organization 3
20 KS185331 Reliability Analysis 3
21 KS185332 Intensive Computational Statistics 3
22 KS185333 Spatial Statistics 3
23 KS185334 Financial Statistics 3
24 KS185335 Research Method and Colloquium 3
25 KS185336 Consulting Statistics 3
26 KS185337 Capita Selecta 3

Guideline of Writing Master Thesis

Pedoman-Tesis_2018.pdf

Registration