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.
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 |
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:
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 |
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 |
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 |
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