Computer Science Curriculum


The following are important components of the Computer Science study program curriculum:

  1. Objectives
  2. Title of Degree Program
  3. Qualification Profile
  4. Program Learning Outcomes (PLO)
  5. Structure of Curriculum
  6. List and Distribution of Courses
  7. Teaching Methodology
  8. Examination
  9. Mapping PLO versus Qualification Profile
  10. Mapping PLO versus Courses

1. Objectives

The Study Program of Computer Science,FPMIPA,UPI was established with decree number of 1342/J33/PP.03.02/2005 on March 16, 2005and began to offer courses on July 17, 2005.It has received accreditation A (excellent) from the National Accreditation Board for Higher Education (BAN PT No. 4850/SK/BAN-PT/Akred/VIII/2020). As seen in the 2018 Curriculum structure, the Computer Science Study Program focuses on several areas of study and expertise, namely:(i) Software Engineering; (ii) Robotics Control, Artificial Intelligence, and Internet of Thing (IoT); (iii) Multimedia and Design; (iv) Computer Engineering and Network Systems; (v) Big Data Analysis; and (vi) Information Systems. In the 2018 Curriculum structure, all fields of study and expertise are represented in 6 packages of elective courses.


2. Title of Degree Program

Based on the Decree of the Minister of Research, Technology and Higher Education Number 57/M/KPT/2019 of 2019 about the Name of Study Programs in Higher Education, the titles of the degree program for study programs of Computer Science is "S.Kom."


3. Qualification Profile

Based on lecturer discussion on several focus group discussions, a survey of alumni, and expectations of students as well as consideration of the results of discussions at the professional association of each study program, the following are the qualification profiles of study program of Computer Science:

  1. Academic: who hashigh education and work as lecturer or teacher and worker at training / education institutions.
  2. Research Assistant: who hascompetencies in assisting to identify real-worldproblems, find alternative solutions through scientific procedures, and publish and disseminate research results.
  3. Consultant: who can be an employee in companies by providing consulting services in computer science fields or other related fields.
  4. Practitioner: who hasprofessional skills in computer science field as programmer, software engineer, network engineer, multimedia designer, or data analyst.
  5. Enterpreneur: who hasand usesskills and knowledges to be an entrepreneur in computer science fields as excellence in entrepreneurship.

4. Program Learning Outcomes (PLO)

The following are the Program Learning Outcomes of Computer Science:

PLO-1:  
Being a good citizen, having faith and devotion to God Almighty, proud and loving the homeland and having good morals, ethics and personality.
PLO-2:  
Mastering literacy, critical and creative thinking competencies as well as communication and collaborationskills in the fields of mathematics, science, technology and engineering to solve various problems in an integrated and/or multidisciplinary manner.
PLO-3:  
Mastering theoretical concepts related to computing, algorithms and programming including specialization in the fields of software engineering, artificial intelligence, multimedia, computer networks, data analysis, and information systems in accordance with the dynamics of technological development.
PLO-4:  
Have the ability to use computer hardware and software effectively that upholds professionalism and integrity.
PLO-5:  
Able to conduct research in the field of information technology by paying attention to the values of the humanities, scientific ethics, and scientific approach.
PLO-6:  
Able to produce original and solution information technology products/applications to solve problems effectively and efficiently in society, industry, government, and other institutions.
PLO-7:  
Able to disseminate innovative and creative ideas both orally and in writing through a lifelong learning process and self-development that follows the times.

5. Structure of Curriculum

UPI rector's regulation number 52/UN40/HK/2019 regarding Guidelines for the Implementation of Education at Universitas Pendidikan Indonesia of 2020, outlines that the study load of undergraduate program is between 144 and152 credits (or SKS, which is a credit system in Indonesia). In general, the curriculum structure of the undergraduate program consists of the core curriculum, which aims to develop the main competencies of graduates (which amounts to about 85% of the total credits can be taken by students) and the elective curriculum, which aims to strengthen the main competencies (which amounts to about 15% of the total credits can be taken by students). In detail, the curriculum structures of the undergraduate program are grouped into General Courses (MKU), Basic Education Courses (MKDK), Faculty Expertise Courses (MKKF), Field of Study Learning Courses (MKKPBS), Core Expertise Competencies Courses (MKIPS), and Study Program Elective Expertise Courses (MKKPS)

  1. The general courses (MKU) consist of compulsory subjects such as Religion course, Religion Educational Seminar course (these first two courses are taken by students according to their religion, which are Islam, Christianity, Catholicism, Buddhism, Confucianism, or Hinduism), Indonesian Language course, Sports Education course, Arts Education course, Civic Education course and Pancasila Education course. The study load for these courses is 2 credits (SKS) each. The aims of these courses are to increase the student’s understanding and practice of their respective religions, to develop the character 21 ASIIN SAR of Formal Science-2021of students in regard to nationality, culture, love of the homeland, and to maintain the fitness of their body.
  2. The basic education courses (MKDK) is a group of courses providing the students with the foundation for educational sciences, teaching and learning, educational management, and educational psychology. Moreover, the courses provide knowledge of didactic methods ofteaching and learning in the classroom. This group of courses must be taken by students who are in education study programs of UPI. This group of courses is not is not offered in the non-education programs.
  3. The faculty expertise courses (MKKF), whose total amount is 6 credits (SKS), is a group of courses that distinguishes FPMIPA UPI’s students from other the students of other faculties. Courses offered in this group are Mathematics, Science, Technology, and Engineering (MSTR) course and Mathematics, Science, Technology and Engineering Applications (AMSTR) course. Both of these courses apply the Science, Technology, Engineering, Art, and Mathematics (STEAM) concept in the teaching and learning process. In these two courses, the students are provided with competencies such as developing literacy in mathematics, science, technology, and engineering, solving problems that exist in everyday life in a critical, creative, integrative and multidisciplinary manner through collaboration within teams with an emphasis on communicating actively and making decisions effectively by taking into account local, regional and global challenges, and forming a caring and tolerant attitude towards social, economic and environmental issues in order to realize Education for Sustainable Development (ESD) and the Sustainable Development Goals (SDGs).
  4. The field of study learning courses (MKKPBS) is a group of courses that provide students with knowledge and skills related to teaching and learning planning, teaching and learning strategies, the use of media and learning aids, and teaching and learning evaluation, which are supported by courses related to ICT literacy to support teaching and learning-nuanced courses. Through this group of courses, it is expected that students will master the 22 ASIIN SAR of Formal Science-2021knowledge and skills on how to design, implement, and evaluate teaching and learning process appropriately (if possible, by utilizing ICT tools). This group of courses is intended for students of education study programs. This group of courses is not offered to the non-education study program students.
  5. The Internship program (PPLSP) in the educationstudy program weighs 4 credits (SKS). It is developed in the form of real teaching with a block system and is placed in both odd and even semesters. PPLSP focuses on reflective models through clinical supervision not on microteaching as implemented in learning simulation activities. PPLSP is aimed at making the graduates of educational study programs master the knowledge, skills, and attitudes related to education (pedagogical knowledge and pedagogical content knowledge). In the non-education study program, this field practice course is called Internship program (PPL) carrying 4 credits (SKS). Students of non-education study program are given the opportunity to do internships work for one semester in various government or privately owned companies or agencies. The PPL course can be taken by students in semester VII. Internship provides students with the opportunity to implement the knowledge or skills that they have learned in college and to gain new experiences that they have not learned in class.
  6. The core expertise competency courses (MKIPS) and the study program elective expertise courses (MKKPPS) are two groups of courses consisting of particular courses that represent the characteristics of each study program, i.e., Computer Science Education Study Program. MKKPPS is a group of courses that expand students’with abilities by studying the implementation of science and technology, paying attention to and applying scientific procedures and ethics to produce solutions, ideas, designs, and by being able to compile scientific descriptions of the results of their studies in the form of published report/paper. In addition, it also provides students with the skills in making appropriate and professional decisions based on the results of data analysis, and in 23 ASIIN SAR of Formal Science-2021choosing various alternative solutions both independently and in groups to solve problem at work with or without using software.

Table Group of Expertise in Computer Science Study Program

Computer Science Study Program
1. Software Engineering
2. Computer Engineering and Network Systems
3. Multimedia and Design
4. Artificial Intelligence Robotics Control and IoT
5. Big Data Analysis
6. Information Systems
 

The placement of study program courses in each semester is arranged in such a way so that the courses in particular semester which are prerequisite for courses of following semester canbe taken. This arrangement is expected to support student needs so that they will be able to master appropriately and comprehensively the material presented in all courses in order to achieve all determined PLO. It is also expected that the students can complete their studies in accordance with the milestones of the curriculum.

The placement of study program courses in each semester is arranged in such a way so that the courses in particular semester which are prerequisite for courses of following semester canbe taken. This arrangement is expected to support student needs so that they will be able to master appropriately and comprehensively the material presented in all courses in order to achieve all determined PLO. It is also expected that the students can complete their studies in accordance with the milestones of the curriculum.

The placement of courses for each semester along with the linkages between courses that describe the breadth and depth of each course in Computer Science study program is presented in the Figures below:

 

Figure Course Mapping based on Field of Study Group in Computer Science Study Program

 

Type of Course Credit
General Courses (MKU) 14 SKS
University Specificity Courses (MKKU) 2 SKS
Faculty Skill Courses (MKKF) 6 SKS
Core Expertise Courses of Study Program (MKKIPS) 102 SKS
Expertise Elective Of Study Programs Courses (MKKPS) 9 SKS
Field Experience Program Courses (MKPPL) 4 SKS
 

Expertise courses in the Computer Science Study Program are divided into 6 course packages or called Professional Competencies (KBK). The six KBKs are Software Engineering, Artificial Intelligence and IoT Robotics Control, Multimedia and Design, Computer Engineering and Network Systems, Big Data Analysis, and Information Systems.


6. List and Distribution of Courses

The following table is a complete list of courses in the Computer Science Study Program. The handbook modules can be accessed by pressing the name of each course or you can download the module file here.

A. General Courses (MKU)

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 KU100 Islamic Education
2
X              
2 KU101 Protestant Education
2
X              
3 KU102 Catholic Education
2
X              
4 KU103 Hindu Education
2
X              
5 KU104 Buddhist Education
2
X              
6 KU109 Khonghucu Education
2
X              
7 KU110 Pancasila
2
  X            
8 KU105 Civic Education
2
X              
9 KU106 Indonesian Language
2
X              
10 KU108 Physical Education*
2
  X            
11 KU119 Art Education*
2
  X            
12 KU300 Seminar for Islamic Education
2
        X      
13 KU301 Seminar for Protestan Education
2
        X      
14 KU302 Seminar for Catholic Education
2
        X      
15 KU303 Seminar for Hindu Education
2
        X      
16 KU304 Seminar for Buddhist Education
2
        X      
17 KU309 Seminar for Khonghucu Education
2
        X      
18 KU400 Community Service Program /Student Study Service
2
          X    
NUMBER OF CREDIT
14
6
4
0
0
2
2
0
0
 

B. University Specificity Courses (MKKU)

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 HU300 Introduction of Education
2
  X            
NUMBER OF CREDIT
2
0
2
0
0
0
0
0
0
 

C. Faculty Skill Courses (MKKF)

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 MA100 Mathematics, Science, Technology and Engineering
3
X              
2 MA200 Applied Mathematics, Science, Technology and Engineering
3
  X            
NUMBER OF CREDIT
6
3
3
0
0
0
0
0
0
 

D. Core Expertise Courses of Study Program (MKKIPS)

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK100 Algorithm and Programming 1
3
X              
2 IK110 Calculus
3
X              
3 IK120 Programming Paradigm
2
X              
4 IK130 Informatics Logic
3
X              
5 IK140 English
2
  X            
6 IK150 Statistics
2
  X            
7 IK160 Algorithm and Programming 2
3
  X            
8 IK170 Database System
3
  X            
9 IK180 Linier Algebra and Metrics
2
  X            
10 IK190 Professional Ethics of Information and Communication Technology
2
  X            
11 IK200 Architecture and Organization Computer
3
    X          
12 IK210 Numerical Method
2
    X          
13 IK220 Control System
3
    X          
14 IK230 Design and Web Programming
3
    X          
15 IK240 Data Structure
3
    X          
16 IK250 Operating System
3
    X          
17 IK260 Automata Theory and Languages
3
    X          
18 IK270 Software Engineering
3
      X        
19 IK280 Artificial Intelligence
3
      X        
20 IK290 Design and Object-Oriented Programming
3
      X        
21 IK207 Computer Network
3
      X        
22 IK217 Information System
3
      X        
23 IK227 Techniques of Operations Research
2
      X        
24 IK237 Design and Analysis of Algorithms
3
      X        
25 IK300 Visual Programming and Mobile Device
3
        X      
26 IK310 Cryptography
2
        X      
27 IK320 Computer Graphics and Multimedia
3
        X      
28 IK330 Software Project Management
3
        X      
29 IK340 Intelligent system
2
        X      
30 IK350 Computer and Human Interaction
3
          X    
31 IK360 Capita Selecta
2
          X    
32 IK370 Simulation and Modeling Techniques
2
          X    
33 IK380 Non-Relational Databases
2
          X    
34 IK400 Research Methodology
3
            X  
35 IK410 Computer Science Entrepreneurship
2
            X  
36 IK420 Seminar
2
            X  
37 IK430 E-Business
2
            X  
38 IK598 Undergraduate Thesis
6
              X
39 IK599 Thesis Defense
0
              X
NUMBER OF CREDIT
102
11
14
20
20
13
9
9
6
 

E. Expertise Elective Of Study Programs Courses (MKKPS)

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK500 Machine Learning
3
        X      
2 IK510 Parallel and Distributed Computing
3
        X      
3 IK520 Project Expertise
3
          X    
4 IK530 Mobile Application Development
3
          X    
NUMBER OF CREDIT
12
0
0
0
0
6
6
0
0

E.1. Package 1: Software Engineering KBK

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK501 Testing and Software Management
2
          X    
2 IK511 Applied Marine Engineering
2
          X    
3 IK521 Service Computing Engineering
2
          X    
4 IK531 Game Application Development
2
          X    
5 IK541 Interfacing Technique
3
          X    
6 IK551 Software Quality Management
3
            X  
7 IK561 Business Application Engineering
2
            X  
8 IK571 Information Engineering
3
            X  
9 IK581 Software Quality Assurance
2
            X  
10 IK591 Compilation Techniques
3
            X  
NUMBER OF CREDIT
9
0
0
0
0
0
4
5
0
 

E.2. Robotics, Artificial Intelligence, and Internet Of Thing (IoT) KBK

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK502 Digital Image Processing
2
          X    
2 IK512 Intelligent Games
2
          X    
3 IK522 Natural Language Processing
2
          X    
4 IK532 Deep Learning
3
          X    
5 IK542 Computer Vision
2
            X  
6 IK552 Internet of Things
2
            X  
7 IK562 Control and Robotics
3
            X  
8 IK572 Expert System
3
            X  
9 IK582 Speech Recognition and Synthesis
3
            X  
NUMBER OF CREDIT
9
0
0
0
0
0
4
5
0
 

E.3. Package 3: Multimedia and Design KBK

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK503 Audio and Video Techniques
2
          X    
2 IK513 Game Programming
2
          X    
3 IK523 Visual Communication Design
2
          X    
4 IK533 Audio and Video Manipulation
2
          X    
5 IK543 Multimedia Production
3
            X  
6 IK553 Social and Media Innovation
2
            X  
7 IK563 Animation Techniques
3
            X  
8 IK573 Open Distance Learning
3
            X  
NUMBER OF CREDIT
9
0
0
0
0
0
4
5
0
 

E.4. Package 4: Computer Engineering and Network Systems KBK

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK504 Mobile Networking
2
          X    
2 IK514 Cloud Technology
2
          X    
3 IK524 Network Administration
2
          X    
4 IK534 Wireless Technology
3
          X    
5 IK544 Computer Forensics
2
            X  
6 IK554 Telecommunications Network Design
2
            X  
7 IK564 Information System Security
3
            X  
8 IK574 Advanced Computer Network
3
            X  
NUMBER OF CREDIT
9
0
0
0
0
0
4
5
0
 

E.5. Package 5: Big Data Analysis KBK

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK505 Data Mining and Warehouse
3
          X    
2 IK515 Computational Statistics
2
          X    
3 IK525 Decision Support System
3
          X    
4 IK535 Data Visualization
2
          X    
5 IK545 Big Data Platforms
2
            X  
6 IK555 Data Analysis
2
            X  
7 IK565 Time Series Data Analysis
2
            X  
8 IK575 Data Management
2
            X  
9 IK585 Financial Technology
3
            X  
NUMBER OF CREDIT
9
0
0
0
0
0
5
4
0
 

E.6. Package 6: Information System KBK

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK506 Information Technology Strategic Planning
3
          X    
2 IK516 Architecture and Integration Enterprise Application
2
          X    
3 IK526 Information System for Accounting
2
          X    
4 IK536 Information System for Education
3
          X    
5 IK546 Information System Audit
2
            X  
6 IK556 IT Infrastructure and Emerging Trends
2
            X  
7 IK566 Business Intelligence
2
            X  
8 IK576 Application Systems for Business Functions
2
            X  
9 IK586 Geographic Information System
3
            X  
NUMBER OF CREDIT
9
0
0
0
0
0
5
4
0
 

F. Field Experience Program Courses (MKPPL)

NO COURSE CODE
COURSE
CREDITS
SEMESTER
1 2 3 4 5 6 7 8
1 IK590 Internship
4
              X
NUMBER OF CREDIT
4
0
2
0
0
0
0
0
4
TOTAL
146
20
23
20
20
21
18
14
10

7. Teaching Methodology

To achieve optimal program learning outcomes, each study program applies student-centered learning approachin its learning models, methods and strategies. This approach aims to encourage all students to have the ability to acquire knowledge for the future long-run, create new understandings, solve problems, do research, and communicate knowledge to others. Theapproaches, models, methods, and strategies have been agreed upon by all lecturers. Meanwhile, the head of the study program regularly controls the teaching and learning process through the Quality Control Task Force (GKM). The task of GKM is to monitor the teaching and learning process.

Teaching and learning strategies are applied through various methods and approaches. The use of the teaching and learning methods and approaches depends on the formulation of the Learning Outcome Program (PLO), course characteristics, as described in the module description, didactic and pedagogical views, learning methods, and the importance of teaching and learning activities. The learning methods linked to learning outcomes for study program of Computer Science is presented in table below:

 
Table Teaching Methodology to Achieve PLO of Computer Science Study Program
PLO Code
Teaching Methodology
Lecture Discussion Debate Symposium Brainstorming Laboratory’s work/Practice Demonstration Simulation Field Practice
PLO-1          
PLO-2  
PLO-3        
PLO-4    
PLO-5    
PLO-6      
PLO-7          
 

Other practicums that are held outside campus are Student Study Service Program (KKN) and Internship Program (PPLSP). For Student Study Service Program, students apply the knowledge and skills they have learned in their studies in the community, whileat the same time receive practical skills and new knowledge relevant to the theoretical knowledge they have learned . Student Study Service Program activities are done by students in groups consisting of students from different study program background to ensure theirdifferentknowledge can complement each other. Each group of Student Study Service Program is supervised by a lecturer in charge. An the end of the program, each group makes a report about the result of their Student Study Service Program and a scientific article that will be submitted to relevant journal to add to UPI scientific publications. Both are the basics things students need to do besides their individualand in group activities to receive their final score for Student Study Service Program.

In Internship Program (PPLSP), students have teachingpracticums in the school classrooms where they have their internshipprogram and supervised by a teacher in charge and a lecturer. Students who take Internship Programhavetheir practicums for approximately one semester or at least sixteen face-to-face meeting in the classroom. To ensure the effectiveness of the program, students who take Internship program are not allowed to take any other coursesfor the semester. At the end of the program, each student will have an exam for the Internship Program by teaching in front of students in the classroom. Internship Program report also need to be submitted by the students individually. Both exam and report are assessed by the teacher in charge and the lecturer. The final score of the Internship Programis determined by how actively involved the students are in the program andthe results of the examination and the grade of the report.

Field Practice Program (PPL) is a program for non-educationstudy program students to experience practical work in a public or private company for one semester. Studes who are taking Field Practice Program are not allowed to take any other coursesfor the semester. Students work ingroup or individuallyduring Field Practice Program in a company and supervised by two lecturers from the students’ study program and one supervisor from the company. At the end of Field Practice Program, students make individual report from the Field Practice Program activities and have an exam in the company by making a presentation in front of lecturers. The student’s active involvementand how well they do in his/her presentation presentation are the criteria to determine their final score for Field Practice Program.


8. Examination

Assessment is designed to measure the level of student’s achievement based on the learning process and the results against predetermined targets. An assessment is usually arranged in such a way to include all the expected learning achievement targets associated with one or a number of competencies covering the aspects of knowledge, skills, and/or attitudes.

The Computer Science study programs of FPMIPA UPI use the multi-component assessment concept in its assessment process to measure the successful course achievement implementation level and the students final results achievement. The knowledge aspect is measured using a written exam; aspects of skills are measured using project tasks, performance, and/or presentations; and the attitude aspect is measured using peer assessment which is carried out in the activities of project assignments, work performance, and/or presentations. Based on the 2020 UPI Education Implementation Guidelines, the assessment of the student learning process is conducted at least twice in one semester, i.e. Mid-Semester Examination (UTS) and the Final Semester Examination (UAS).

Based on UPI Education Implementation Guidelines of 2020, 1 semester consists of 16 sessions with 14 sessions used for lectures, 1 session for the Mid-Semester Examination (UTS) and 1 session for the Final-Semester Examination (UAS). In general, the Mid-Semester Examination (UTS) is administered on the 8th session and the Final-Semester Examination (UAS) on the 16th meeting. The students can take the Final-Semester Examination (UAS) if they have attended at least 80% of the sessions in a particular course. The administration of Mid-Semester Examination (UTS) is left to the lecturer of the course and the cource schedule. The administration of the Final-Semester Examination (UAS), remedial teaching, and entry of grades is regulated by the Rector through he Vice Rector for Education and Student Affairs.

Mid-Semester Examination (UTS) and Final-Semester Examination (UAS) are organized according to the course categories, namely General Courses (MKU) and Core Expertise Competency Courses (MKIPS and MKPPS). This categorization is designed to help students take the exam in an orderly manner according to the specified time. The General Courses (MKU) exams are administered through a computer based test (CBT) by the General Courses (MKU) Study Program. The Core Expertise Competency Courses (MKIPS and MKPPS) examinations are conducted by the respective study programs. Examination schedules of the Core Competencey Courses are prepared by the study program and published offline or online on UPI Academics. The examination schedules are prepared by considering the time and student’s load. Only a maximum of two examinations are scheduled per day per class.

During the Covid-19 pandemic, tests are aministered online using the (http://spot.upi.edu), SPADA (http://spada.upi.edu) and other applications/platforms such as https://quizizz.com, https://safeexambrowser.org which can be accessed from anywhere without the students having to to come to campus.

Students who for some reason cannot take Mid-Semester Examination (UTS) and/or Final-Semester Examination (UAS) must inform the lecturer prior to the exam time and submit supporting documentary evidence for their absence. Students will only be given the opportunity to take a make up examination if their absence is caused by: (a) an illness (proven by a doctor's certificate); (b) performing a task of representing the university in intra-curricular or extra-curricular activities outside campus; or (c) other legitimate and permissible reasons. Make up examinations are administered and scheduled by the lecturer in agreement with the student.. Assessment is carried out objectively and transparently, and in accordance with the regulation and procedures, and the results are informed to the students. Results are announced to provide feedback to the students on what they have done and achieved and to enourage those who have not made optimal efforts to improve themselves and obtain the better results in the future.

Students who have not met the course passing criteria will receive a short-term treatment of remedial teaching and their have their semester learning plan (RPS) evaluated learning process improvement. Students who get an E (fail) in a course must sign up for the course again in the following semester. The grade to be assigned to the students is the final grade they will receive in the current semester. This is stated in the 2020 UPI Education Implementation Guidelines.

The Internship Program(PPL) is a field activity for non-education sciencestudents. It iscarried out in collaboration with public and private external institutions.Students of Mathematics Study Program who take part in the Internship Program(PPL)are guided by two lecturers from the Study Program and aperson from the company where thestudents have their Internship Program(PPL). Internship)in the Computer Science Study Programstudents taking the Internship Program (PPL)is supervisedby a lecturer from the Study Program and aperson from the company where the Internship Program(PPL) is attended.

Passingand final grade of the Internship Program (PPL)is determined based on the accumulated scoreobtained from the supervisor,from the institution/companywhere the student is apprenticing,and from the supervising lectureraccording to the formulastatedin the PPL guidebook.

In addition to the Internship Program (PPL), the students also learn about the wider community environment through the Student Community Service (KKN)whose implementation is coordinated by the UPI Research and Community Service Institute (LPPM). The students can download information related to the Student Community Service (KKN) on the http://kkn.lppm.upi.edu/ page.

In the Student Community Service (KKN) students groups from various disciplinary backgrounds stay for a certain period of time in a community and participate actively in the life of the community. The group is guided by a supervising lecturer who serves as a companion and assessor for the student field activities. Before the Student Community Service (KKN) activities began, the lecturers and students would respectively be given briefing by the UPI Research and Community Service Institute (LPPM). Briefing for the supervisors relates to monitoring activities and information about the Student Community Service (KKN) assessments. Briefing for the students relates to the technical implementation of the Student Community Service (KKN) on the ground and the best practices. The supervising lecturer is responsible for monitoring activities. The assessment of the Student Community Service (KKN) participants is conducted on two aspects, namely the individual aspect and the group aspect. The supervising lecturer reports the KKN students score to the UPI Research and Community Service Institute (LPPM) for further entry into the system. During the COVID-19 pandemic, UPI made some adjustment to the theme to allow participants (students) to continue to participate in activities risking their health health and safety.

There are two tracks for completion of undergraduate (S1) study, namely the thesis track and the non-thesis track. The non-thesis track is for students who have a GPA (IPK) of 2.00 - 2.50. They are required to take 6 credits (SKS) of courses and make a thesis substitute paper. The study program makes regulations andSOPs for completion of study without a thesis track. The hesis track can be taken by students who have passed the thesis prerequisite courses, obtaining a minimum 105 credits (SKS) and GPA (IPK) of at least 2.50, and have received recommendation from the academic supervisor lecturer.

The procedures for thesis writing are as follows: thesis coordinator assigns supervisors I and II to the students; the students are guided in writing a thesis proposal; students take the thesis proposal examination. If the proposal approved by the examiners, students can continue the guidance process with the two supervisors, such as conducting activities to develop the instruments and collect data; proceed with writing the report of the data collection results, discussion, and conclusion. If the thesis writing results are considered appropriate by the supervisors, the student can take the thesis defense.

The proposal writing and examination,exam follows the SOP; the procedure for the thesis defense follows the SOP. The final score of the thesis includes the assessment of thesis writing and thesis defense examination. A student is said to have passed the thesis examination if his final-thesis score is at least 2.0 (on the scale of 4). The thesis research is carried out independently under the guidance of the two thesis supervisors. In general, the procedure for final completion of the study through the thesis track is presented in the following flowchart below.

Figure The flowchart of study completion procedures through thesis track in Computer Science Education Department

The assessment system in four study programs includes student learning processes and outcomes. This system includesformative and summativeassessments.Formative assessment aims to obtain information that can be used to improve the learning process (program delivery), while summative assessment is used to assess the achievement of student learning outcomes (learning outcomes). The assessment guidelines generally follow the UPI Education Implementation Guidelines which can be accessed at https://dit-akademik.upi.edu/.

Principle of Benchmarking Assessment (PAP) is used to assess student’s performance in a course. With PAP student achievement of a goal/competency is assessed against predetermined criteria . The final grade of a course is the cumulative result of the components of the assignment, mid-semester exams, final-semester exams, and other assessment components. In practice, each course has its own assessment procedures and techniques appropriate to its characteristics as long as it is not in conflict with the provisions of UPI Education Implementation Guidelines. This practical assessment guideline is contained in the course syllabus/RPS developed by a lecturer.

In general, each subject uses integrative assessment techniques, namely between the process and the results, and between other assessment components: attendance, quizzes, mid-semester exams (UTS), final-semester exams (UAS), assignments, practicum (if any), participation, and presentation (if any). The percentage of the assessment components include the element of attendance (5%); participation/quizzes/assignments/presentations (15%); practicum (10%); mid-semester exam (35%); and final-semester exams (35%). Table below is the illustrates guidelines for determining grades for each course.

 
Table Guidelines for Determining Course Values
Category
Level of Ability
Description
Grade Value Degree of Quality
A 4,0 Excellent
92-100
 
A- 3,7 Almost Excellent
86-91
 
B+ 3,4 Very Good
81-85
 
B 3,0 Good
76-80
 
B- 2,7 Fairly Good
71-75
 
C+ 2,4 Very Satisfactory
66-70
 
C 2,0 Satisfactory
60-65
 
D 1,0 Poor
55-59
Minimum requirement for graduation
E <1,0 Fail
below 55
course should be retaken
 

In compulsory courses, the minimum passing grade is C, while for elective courses the minimum passing grade is D. Students who get an E (fail), should retake the class in the following year in order to get the appropriate grade with pass criteria.

Students cannot cancel the grades of courses that they have passed, unless the they transfer to a different department/study program, where they have to cancel the expertise courses of the previous study program, or in the case where a student sign up for more than the maximum study load specified in the curriculum structure.

The achievement of the course learning outcome (CLO) can be seen from the student learning outcomes in these courses which are measured using summative test instruments. Each test instrument consists of a number of questions, each of which measures the CLO in that course. Each question that will be used for the exam is validated first by the head of the KBK where the subject is located. Parallel course (the same course taught in different classes) must use the same questions and assessment criteria. The final course outcomes are then evaluated by the GKM team to ensure the achievement of PLOs related to these courses. The results of the assessment in the form of the final grade must be inputted by the lecturer of the course into the lecturer score input system through the website https://siak.upi.edu/sinndo. If the lecturer is late in inputting the grades, the lecturer in question will receive a warning and consequences.

Students can view the final grade information for the courses they contact through the website https://student.upi.edu. Lecturers are obliged to design, manage, provide assignments/exams, provide feedback, and maintain student academic documents in an orderly manner. Relevant tothis obligation, students have the right to obtain clear and transparent information about their study results in the form of test scores, quizzes, assignments or projects, practicum, and/or presentations.

Students who have questions about their grades can directly contact the lecturer to discuss the problem. If there is an error in the process of inputting the grades, the lecturer can correct the grade to match the facts as long as it is still within the period of grade entry. If input error is detected after the grade entry period is over, the lecturer can submit a request letter to the UPI Academic Directorate to correct the grade.

The relationship between the learning outcome, the learning strategy, and the assessment used to measure the learning outcome in Computer Science study program will be presented below.

Table below, illustrates the relationship between PLO, learning strategies and assessment in Computer Science Study Program.

 
Table Linkage of PLO and Assessment of the Computer Science Study Program
PLO Code Teaching Method Assessment
PLO-1 Lectures, discussions, debates and brainstorms Multiple choice
PLO-2 Lectures, discussions, symposiums, brainstorming, laboratory/practicum, demonstrations, simulations, field experiences Presentations, Student project/projects, essay exams, oral exams, multiple choice exams, short answer exams
PLO-3 Lectures, discussions, laboratory/practicum, demonstrations, and simulations Essay exams, verbal exams, multiple choice exams, and short answer exams
PLO-4 Lectures, discussions, brainstorming, laboratory/practicum, demonstrations, simulations, and field experiences Student project/projects and practicum
PLO-5 Lectures, discussions, debates, symposiums, brainstorming, laboratory/practicum, and field experiences Scientific articles
PLO-6 Lectures, discussions, laboratory/practicum, demonstrations, simulations, and field experiences Scientific articles
PLO-7 Lectures, debates, symposiums and field experiences Scientific articles and presentations

9. Mapping PLO versus Qualification Profile

The following table describes the mapping between Study Program Learning Outcomes (PLO) and the expected Graduate Qualifications:

PLO Code
Qualification Profile
Academics
Research Assistance
Consultant
Professional Practitioner
Entrepreneur
PLO-1
PLO-2      
PLO-3
PLO-4    
PLO-5      
PLO-6    
PLO-7

10. Mapping PLO versus Courses

The following table describes the mapping between Study Program Learning Outcomes (PLO) and existing Study Program Courses:

A. General Course (MKU)

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 KU100 Islamic Education
2
           
2 KU101 Protestant Education
2
           
3 KU102 Catholic Education
2
           
4 KU103 Hindu Education
2
           
5 KU104 Buddhist Education
2
           
6 KU109 Khonghucu Education
2
           
7 KU110 Pancasila
2
         
8 KU105 Civic Education
2
         
9 KU106 Indonesian Language
2
           
10 KU108 Physical Education*
2
         
11 KU119 Art Education*
2
         
12 KU300 Seminar for Islamic Education
2
           
13 KU301 Seminar for Protestan Education
2
           
14 KU302 Seminar for Catholic Education
2
           
15 KU303 Seminar for Hindu Education
2
           
16 KU304 Seminar for Buddhist Education
2
           
17 KU309 Seminar for Khonghucu Education
2
           
18 KU400 Community Service Program /Student Study Service
2
         
Total Credit
36
 
 
 
 
 
 
 
 

B. University Specificity Courses (MKKU)

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 HU300 Introduction of Education
2
         
Total Credit
2
 
 
 
 
 
 
 
 

C. Faculty Skill Courses (MKKF)

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 MA100 Mathematics, Science, Technology and Engineering
3
           
2 MA101 Applied Mathematics, Science, Technology and Engineering
3
           
Total Credit
6
 
 
 
 
 
 
 

D. Core Expertise Courses of Study Program (MKKIPS)

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK100 Algorithm and Programming 1
3
     
2 IK110 Calculus
3
         
3 IK120 Programming Paradigm
2
       
4 IK130 Informatics Logic
3
         
5 IK140 English
2
         
6 IK150 Statistics
2
         
7 IK160 Algorithm and Programming 2
3
     
8 IK170 Database System
3
 
9 IK180 Linier Algebra and Metrics
2
         
10 IK190 Professional Ethics of Information and Communication Technology
2
         
11 IK200 Architecture and Organization Computer
3
         
12 IK210 Numerical Method
2
 
13 IK220 Control System
3
         
14 IK230 Design and Web Programming
3
 
15 IK240 Data Structure
3
         
16 IK250 Operating System
3
 
17 IK260 Automata Theory and Languages
3
       
18 IK270 Software Engineering
3
         
19 IK280 Artificial Intelligence
3
       
20 IK290 Design and Object-Oriented Programming
3
       
21 IK207 Computer Network
3
       
22 IK217 Information System
3
 
23 IK227 Techniques of Operations Research
2
       
24 IK237 Design and Analysis of Algorithms
3
       
25 IK300 Visual Programming and Mobile Device
3
       
26 IK310 Cryptography
2
 
27 IK320 Computer Graphics and Multimedia
3
       
28 IK330 Software Project Management
3
 
29 IK340 Intelligent system
2
       
30 IK350 Computer and Human Interaction
3
 
31 IK360 Capita Selecta
2
 
32 IK370 Simulation and Modeling Techniques
2
         
33 IK380 Non-Relational Databases
2
 
34 IK400 Research Methodology
3
 
35 IK410 Computer Science Entrepreneurship
2
       
36 IK420 Seminar
2
       
37 IK430 E-Business
2
 
38 IK598 Undergraduate Thesis
6
39 IK599 Thesis Defense
0
       
Total Credit
102
 
 
 
 
 
 
 
 

E. Expertise Elective Of Study Programs Courses (MKKPS)

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK500 Machine Learning
3
   
2 IK510 Parallel and Distributed Computing
3
   
3 IK520 Project Expertise
3
         
4 IK530 Mobile Application Development
3
         
Total Credit
12
 
 
 
 
 
 
 
 

E.1. Package 1: Software Engineering KBK

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK501 Testing and Software Management
2
   
2 IK511 Applied Marine Engineering
2
     
3 IK521 Service Computing Engineering
2
       
4 IK531 Game Application Development
2
     
5 IK541 Interfacing Technique
3
       
6 IK551 Software Quality Management
3
   
7 IK561 Business Application Engineering
2
       
8 IK571 Information Engineering
3
       
9 IK581 Software Quality Assurance
2
   
10 IK591 Compilation Techniques
3
       
Total Credit
24
 
 
 
 
 
 
 
Total
138
 
 
 
 
 
 
 
 

E.2. Robotics, Artificial Intelligence, and Internet Of Thing (IoT) KBK

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK502 Digital Image Processing
2
 
2 IK512 Intelligent Games
2
 
3 IK522 Natural Language Processing
2
 
4 IK532 Deep Learning
3
 
5 IK542 Computer Vision
2
 
6 IK552 Internet of Things
2
 
7 IK562 Control and Robotics
3
 
8 IK572 Expert System
3
 
9 IK582 Speech Recognition and Synthesis
3
 
Total Credit
22
 
 
 
 
 
 
 
Total
138
 
 
 
 
 
 
 
 

E.3. Package 3: Multimedia and Design KBK

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK503 Audio and Video Techniques
2
     
2 IK513 Game Programming
2
     
3 IK523 Visual Communication Design
2
 
4 IK533 Audio and Video Manipulation
2
     
5 IK543 Multimedia Production
3
     
6 IK553 Social and Media Innovation
2
 
7 IK563 Animation Techniques
3
     
8 IK573 Open Distance Learning
3
 
Total Credit
19
 
 
 
 
 
 
 
Total
138
 
 
 
 
 
 
 
 

E.4. Package 4: Computer Engineering and Network Systems KBK

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK504 Mobile Networking
2
     
2 IK514 Cloud Technology
2
     
3 IK524 Network Administration
2
 
4 IK534 Wireless Technology
3
     
5 IK544 Computer Forensics
2
 
6 IK554 Telecommunications Network Design
2
 
7 IK564 Information System Security
3
 
8 IK574 Advanced Computer Network
3
 
Total Credit
19
 
 
 
 
 
 
 
Total
138
 
 
 
 
 
 
 
 

E.5. Package 5: Big Data Analysis KBK

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK505 Data Mining and Warehouse
3
     
2 IK515 Computational Statistics
2
         
3 IK525 Decision Support System
3
         
4 IK535 Data Visualization
2
       
5 IK545 Big Data Platforms
2
     
6 IK555 Data Analysis
2
       
7 IK565 Time Series Data Analysis
2
 
8 IK575 Data Management
2
     
9 IK585 Financial Technology
3
       
Total Credit
21
 
 
 
 
 
 
 
Total
138
 
 
 
 
 
 
 
 

E.6. Package 6: Information System KBK

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK506 Information Technology Strategic Planning
3
   
2 IK516 Architecture and Integration Enterprise Application
2
   
3 IK526 Information System for Accounting
2
 
4 IK536 Information System for Education
3
 
5 IK546 Information System Audit
2
 
6 IK556 IT Infrastructure and Emerging Trends
2
 
7 IK566 Business Intelligence
2
   
8 IK576 Application Systems for Business Functions
2
   
9 IK586 Geographic Information System
3
   
Total Credit
21
 
 
 
 
 
 
 
Total
138
 
 
 
 
 
 
 
 

F. Field Experience Program Courses (MKPPL)

NO COURSE CODE
COURSE
CREDITS
PROGRAM LEARNING OUTCOMES
PLO-1 PLO-2 PLO-3 PLO-4 PLO-5 PLO-6 PLO-7
1 IK590 Internship
4
     
Total Credit
4