Study Program Magistrate

Along with the rapid advancement of science and technology, the need for accurate and efficient data analysis has become increasingly urgent, making statistics and data science essential fields across various sectors, such as industry, government, healthcare, and economics. Statistics, which focuses on the collection, organization, analysis, and presentation of data, enables the transformation of raw data into meaningful information for decision-making. Meanwhile, data science, as an interdisciplinary field that integrates statistics, computer science, and contextual problem understanding, encompasses data acquisition, cleaning, modeling, and visualization on a large scale, as well as the application of machine learning and artificial intelligence techniques to discover patterns and generate predictions. With the continuous growth of technology and data volume, expertise in statistics and data science has become highly relevant and serves as a crucial foundation for data-driven decision-making in the era of digital transformation. Therefore, the Master’s Program in Statistics and Data Science at IPB University was established in response to these demands, aiming to prepare graduates who are competent in applying statistical theory and data science methods to solve complex problems and provide data-driven solutions across various fields, while also developing strong research capabilities in an increasingly interconnected and digitalized world.

A brief history of the Statistics and Data Science Study Program at IPB University began in 1968, initiated by the late Prof. Andi Hakim Nasoetion through the Biometrics Division within the Faculty of Agriculture. This division was officially established as the Department of Statistics and Computing in 1972, offering undergraduate education programs. Since 1975, the Department of Statistics and Computing has also offered a master’s degree program.

In 1975, the Master’s Program in Statistics was officially launched alongside the establishment of the Graduate School of IPB. At its inception, seven departments were opened, one of which was Applied Statistics, which later became the forerunner of the Master’s Program in Statistics. This program was designed to accommodate graduates of four-year undergraduate programs from IPB as well as other institutions, with a focus on developing a Master of Science (M.Sc.) program.

In 1982, it became the Department of Statistics, and in 2004 it was renamed the Department of Statistics. The Department of Statistics at IPB stands as a pioneering institution in statistics education in Indonesia, marking its excellence as the first to offer advanced education in statistics and the dynamic field of data science. Currently, the department offers comprehensive programs at the undergraduate, master’s, and doctoral levels, focusing on Statistics and Data Science.

Until 2020, the Department of Statistics at IPB offered two master’s programs: the Master’s Program in Statistics and the Master’s Program in Applied Statistics. After 2020, the Master’s Program in Statistics was renamed the Master’s Program in Statistics and Data Science, while the Master’s Program in Applied Statistics stopped admitting new students. In 2024, the Department of Statistics, together with the Department of Mathematics and the Department of Computer Science, merged to form the School of Data Science, Mathematics, and Informatics, resulting in the dissolution of the three departments. Currently, the Master’s Program in Statistics and Data Science operates under the School of Data Science, Mathematics, and Informatics and is supported by 31 faculty members (21 with doctoral degrees and 10 with master’s degrees), eight of whom are full professors.

Through these programs, the department has developed highly qualified professional human resources and earned recognition at both national and international levels. Leading institutions, industries, and government agencies unanimously acknowledge the reliability and adaptability of the department’s graduates, who are well-equipped to meet the demands and challenges of the contemporary workforce. The department’s success can be attributed to its strong learning process and the outstanding input provided by its students. This combination has driven graduates to excel in their respective fields, empowering them not only in statistics and data science but also across various applied domains.

Specifically, the Master’s Program in Statistics and Data Science is designed to admit 60 students annually. Graduates of this program possess competencies aligned with Level 8 of the Indonesian National Qualifications Framework (KKNI). They are strategically prepared for various roles, such as Data Analytics Leadership Managers (Head of Analytics, Data Processing Manager), leading researchers (Senior Researcher, Senior Executive Researcher, Senior Statistician), data scientists, and lecturers specializing in statistics and data science.

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Num Course Credit Precondition Semester Course Category
Code Name
1 PPS1503 English 3(3-0) - 1 PPKU/Common Core Courses
2 STA1501 Statistical Theory 3(2-1) - 1 Academic Core Courses
3 STA1501 Statistical Theory 3(2-1) - 1 Academic Core Courses
4 STA1511 Statistical Analysis 3(2-1) - 1 Academic Core Courses
5 STA1511 Statistical Analysis 3(2-1) - 1 Academic Core Courses
6 STA1561 Statistical Programming 3(2-1) - 1 Academic Core Courses
7 STA1581 Data Science 3(2-1) - 1 Academic Core Courses
8 STA1500 Quantitative Research Methods 3(2-1) - 2 PPKU/Common Core Courses
9 STA1500 Quantitative Research Methods 3(2-1) - 2 PPKU/Common Core Courses
10 STA1521 Analysis and Design of the Experiment 3(2-1) - 2 In-depth Courses
11 STA1521 Analysis and Design of the Experiment 3(2-1) - 2 In-depth Courses
12 STA1522 Sampling Methods 3(2-1) - 2 In-depth Courses
13 STA1523 Survey Design and Analysis 3(2-1) - 2 In-depth Courses
14 STA1531 Advanced Regression Analysis 3(2-1) - 2 In-depth Courses
15 STA1541 Multivariate Analysis 3(2-1) - 2 In-depth Courses
16 STA1541 Multivariate Analysis 3(2-1) - 2 In-depth Courses
17 STA1541 Multivariate Analysis 3(2-1) - 2 In-depth Courses
18 STA1542 Time Series Analysis 3(2-1) - 2 In-depth Courses
19 STA1542 Time Series Analysis 3(2-1) - 2 In-depth Courses
20 STA1543 Categorical Data Analysis 3(2-1) - 2 In-depth Courses
21 STA1544 Observational Data Analysis 3(2-1) - 2 In-depth Courses
22 STA1544 Observational Data Analysis 3(2-1) - 2 In-depth Courses
23 STA1552 Non-Parametric Modeling 3(2-1) - 2 In-depth Courses
24 STA1553 Spatial Statistics Analysis 3(2-1) - 2 In-depth Courses
25 STA1553 Spatial Statistics Analysis 3(2-1) - 2 In-depth Courses
26 STA1554 Psychometrics 3(2-1) - 2 In-depth Courses
27 STA1554 Psychometrics 3(2-1) - 2 In-depth Courses
28 STA1562 Statistical Data Management 3(2-1) - 2 In-depth Courses
29 STA1582 Statistical Machine Learning 3(2-1) - 2 In-depth Courses
30 STA1583 Text Analytics 3(2-1) - 2 In-depth Courses
31 STA1697 Colloquium 1(0-1) - 2 Final Year Project
32 STA169A Thesis Proposal 2(0-2) - 2 Final Year Project
33 PPS1691 Thesis Seminar 1(0-1) - 3 Final Year Project
34 PPS1692 National Scientific Publication 2(0-2) - 3 Final Year Project
35 PPS1692 National Scientific Publication 2(0-2) - 3 Final Year Project
36 PPS1695 International Scientific Publication 3(0-3) - 3 Final Year Project
37 PPS1698 International Seminar Proceedings 2(0-2) - 3 Final Year Project
38 STA1551 Classification Modeling 3(2-1) - 3 In-depth Courses
39 STA1563 Data Exploration and Visualization 3(2-1) - 3 In-depth Courses
40 STA1631 Generalized Linear Models 3(2-1) - 3 In-depth Courses
41 STA169B Thesis 6(0-6) - 4 Final Year Project
42 STA169C Thesis Exam 2(0-2) - 4 Final Year Project

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