Introduction
Vision & Mission
Program Objective
Expected Learning Outcomes
Prospective Career of The Graduate
Course Structure
Prerequisites
Quality Controlled Examination (UPM)

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Introduction

Nowadays, all kinds of data are being generated when business processes are conducted or when enterprises interoperate. This vast amount of data is called as Big Data and it can be analysed using process-mining and data-mining techniques to understand how a business is performing and to identify new opportunities. The combination of Statistics and Computer Science into one program is designed to maximize the learning opportunities for the student in of handling Big Data, techniques for analyzing it, and simulation techniques for exploring the new business scenarios. This interdisciplinary study addresses the complexity of manipulating, analysing and using Big Data in business. The program can be completed within 4 - 4.5 years. Furthermore, to provide work experience for students, there are industrial internships, interesting research or entrepreneurship programs for 1 semester.

 

Catalog 2017/ B2021 (PDF), Catalog 2018/ B2022 (PDF), Catalog 2019/ B2023 (PDF),
Catalog 2020/ B2024 (PDF), Catalog 2021/ B2025 (PDF), Catalog 2022/ B2026 (PDF), Catalog 2023/ B2027 (PDF), Catalog 2024/ B2028 (PDF)

Vision

A World Class study program by providing excellent educational experiences in Statistical Computing, Fostering and Empowering the Society in Serving and Building the Nation.


Mission

The mission of Computer Science and Statistics Program is to contribute to the global community through the provision of world-class education by:
  1. Educating students to effectively apply their educational experiences in Statistical Computing to solve real-world problems.
  2. Preparing our graduates to develop exemplary soft skills & technical skills required as ICT professionals, leaders and entrepreneurs in global market.
  3. Promoting high impact research that contributes to the nation.
  4. Fostering BINUSIAN as lifelong learners through self-enrichment.
  5. Empowering BINUSIAN to continuously improve society’s quality of life.
 

Program Objective

The objectives of the program are:
  1. Graduates will become successful professionals in ICT fields;
  2. Graduates will obtain employment in global companies or become entrepreneurs;
  3. Graduates will obtain professional certification or continue their study to the postgraduate level;
  4. Graduate will have ability to pursue higher degree of education.

Student Outcomes

After completing the study, graduates are:
  1. Able to analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions
  2. Able to design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of computer science
  3. Able to communicate effectively in a variety of professional contexts
  4. Able to recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles
  5. Able to function effectively as a member or leader of a team engaged in activities appropriate to computer science
  6. Able to apply computer science theory and software development fundamentals to produce computing-based solutions
  7. Able to conduct data management, including data design and collection in the form of surveys and experiments, data organization, exploration, and analysis based on statistical methods, using statistical software.
  8. Able to solve estimation problems and hypothesis testing through data utilization and several methods of estimation and hypothesis testing.
  9. Able to conduct data science project flow to solve real business and industry problems
  10. Able to develop software by implementing statistical models.
  11. Able to apply interdisciplinary knowledge and skills in developing alternative solutions for problem-solving

Prospective Career of the Graduates

The graduates of the double study program Statistics and Computer Science can follow careers in:

  1. Business analyst, DSS Manager, or business strategist
  2. Actuary analyst, risk analyst, or quantitative credit analyst
  3. Strategy consultant or evaluator of company performance
  4. Data scientist, market researcher, or researcher of analysis techniques
  5. Database designer, database administrator, or system analyst

Course Structure for Binusian 2028

Sem Code Course Name SCU Total
1 CHAR6013049 Character Building: Pancasila 2 20
COMP6047049 Algorithm and Programming2 (AOL) 4/2
MATH6031049 Calculus 4
MATH6025049 Discrete Mathematics1 4
STAT6152049 Introduction to Data Science2 2
COMP6798049 Program Design Methods1 (AOL) 2
Foreign Language Courses 0
2 CHAR6014049 Character Building: Kewarganegaraan 2 20
COMP6048049 Data Structures1&2 (AOL) 4/2
MATH6030049 Linear Algebra1 2
MATH6191049 Advanced Calculus1 4
STAT6171049 Basic Statistics 2
ENPR6311001 Creativity and Innovation 2
LANG6027049 Indonesian 2
Foreign Language Courses 0
3 SCIE6063049 Computational Physics (AOL) 2/1 24
COMP6708049 Object Oriented Programming 2/2
STAT6166049 Survey and Sampling Methods1 4
MATH6144049 Advanced Linear Algebra1 2
STAT6185049 Theory of Statistics I  (AOL) 4
MATH6183049 Scientific Computing (AOL) 2/1
STAT6157049 Data Mining and Visualization1&2 (AOL) 2
STAT6037049 Non Parametric Statistics 2
Foreign Language Courses 0
4 SCIE6062049 Computational Biology 2/1 24
CPEN6247049 Computer Networks (AOL) 2/1
COMP6799049 Database Technology** (AOL) 2/1
STAT6193049 Theory of Statistics II *   4
COMP6065049 Artificial Intelligence** (AOL) 4
MATH6221049 Machine Learning1&2 (AOL) 2
CHAR6015049 Character Building: Agama 2
STAT6048049 Regression Analysis1  (AOL) 2/1
Foreign Language Courses 0
5 COMP6738049 Web Programming 2 23
COMP6800049 Human and Computer Interaction2 (AOL) 2/1
COMP6049049 Algorithm Design and Analysis1 (AOL) 4
STAT6011049 Design and Analysis of Experiments1&2 (AOL) 4
STAT6162049 Bayesian Data Analysis 2
MATH6165049 Deep Learning and Optimization Methods1 4
STAT6044049 Categorical Data Analysis1 (AOL) 2
STAT6158049 Data Management and Organization 2
6 COMP6100049 Software Engineering2 (AOL) 4 24
COMP6697049 Operating System (AOL) 2
STAT6053049 Multivariate Statistics1&2 (AOL) 4
STAT6215049 Time Series Analysis1&2 2/2
STAT6036049 Stochastic Process1 4
MATH6178049 Text Mining 2
STAT6159049 Big Data Infrastructure and Technology 2
STAT6196049 Spatial Statistics 2
7 ENPR6312001 Venture Creation 2 21
COMP6062049 Compilation Techniques 4
COMP6696049 Research Methodology in Computer Science1 (AOL) 2
STAT6197049 Econometrics1&2 2/1
STAT6181049 Financial and Actuarial Science1 4
MATH6166049 Data Security 2
Free Electives 4
8 Enrichment Program 20 20
9 STAT6188049 Pre-Thesis 2 6
STAT6189049 Thesis 4
STAT6030049 Thesis 6
Total Credits 182 SCU

1) This course is delivered in English
 2) Global Learning System Course

-) (AOL) - Assurance of Learning Process System

 Free Electives:
-) For Free Electives, students are required to choose from the list of Free Electives in Appendix.

Foreign Language Courses:
Students will take foreign language courses according to Beelingua Placement Test results. See foreign language courses appendix for the details. Students must pass with a minimum Grade of C.

 Pre-thesis (2 SCU) & Thesis (4 SCU) can be taken in the 7th and/or 8th semester by the students who meet the requirements from the Study Program/Program

Appendix: Free Electives (7th Semester)
Because free electives will be implemented on the 7th semester, data will be collected from Curriculum 2025

Enrichment Program (8th Semester):
-) Student will take one of enrichment program tracks (off campus). See enrichment appendix for the tracks detail.

Enrichment Track Scheme

Track Semester 8
IN RS EN CD SA IS etc
1 v
2 v
3 v
4 v
5 v
6 v

Note:

IN            : Certified Internship
RS          : Certified Research
EN          : Certified Entrepreneurship
CD          : Certified Community Development
SA           : Certified Study Abroad
IS            : Certified Specific Independent Study
etc           : Study Program Special Purposes

Description:
Student will take one of enrichment program tracks

Prerequisites for Binusian 2028

There is no prerequisite for this program

Quality Controlled Courses for Binusian 2028

Student should pass all of these quality controlled courses as listed below:
No Course Code Course Name Minimal Grade
1. CHAR6013049 Character Building: Pancasila B
2. COMP6047049 Algorithm and Programming* C
3. COMP6798049 Program Design Methods* C
4. COMP6048049 Data Structures* C
5. STAT6185049 Theory of Statistics I* C
6. STAT6157049 Data Mining and Visualization C
7. MATH6221049 Machine Learning C
8. COMP6799049 Database Technology C
9. STAT6048049 Regression Analysis* C
10. STAT6044049 Categorical Data Analysis C
11. COMP6100049 Software Engineering* C
12. COMP6697049 Operating System C
13. STAT6053049 Multivariate Statistics* C
14. ENPR6312001 Venture Creation C
*) Tutorial