Industrial Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Industrial Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Industrial Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 15251516 | Decision Support Systems | 2025 | Autumn | 7 | 3+0+0 | 0 | 5 |
| Course Type | Elective |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | Prof. Murat DARÇIN |
| Instructor(s) | - |
| Instructor Assistant(s) | - |
Course Content
Location-related decision-making problems; Multi-criteria decision-making methods; Defining and normalizing criteria; Determining weights, implementation in a GIS environment; Interpreting and classifying results
Objectives of the Course
The aim of the course is to develop ways and methods to be used in decision making related to position, to create alternatives and to apply them in GIS environment.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | X |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P5 | The ability to use research methods, including literature review, experimental design, experiment execution, data collection, analysis, and interpretation of results, to investigate complex industrial engineering problems. | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Explain managerial decision-making, computer-supported decision-making, and the fundamentals of business intelligence. | P.5.15 | 1 |
| O2 | Explain the fundamentals, definitions, and capabilities of decision support systems. | P.5.16 | 1 |
| O3 | Develop a decision support system for solving a specific problem as part of a team. | P.5.17 | 1 |
| O4 | Develop Excel-based decision support system applications to solve different problems. | P.5.18 | 1 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Login. Gravity, potential area determination problems |
| 2 | Multi-criteria decision making problems, homework presentation |
| 3 | Methods of solution of multi-criteria decision making problems |
| 4 | Methods of solution of multi-criteria decision making problems |
| 5 | Methods of normalization of criteria |
| 6 | CBS ortamında normalleştirme çalışması-Vektör |
| 7 | Normalization work in GIS environment-Vector |
| 8 | Ara Sınav |
| 9 | GIS analysis, visualization tools |
| 10 | Methods for determining weights |
| 11 | Weight calculation study |
| 12 | Classification, interpretation, visualization of results |
| 13 | Problem solving in GIS environment, mid-term exam |
| 14 | CBS ortamında problem çözüm çalışması |
| 15 | Final Sınavına Hazırlık |
Textbook or Material
| Resources | Karar Teorisi, Zerrin Aladağ, 2011 Umuttepe Yayınevi ISBN:9786055936464 |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Field Study | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Seminar | - | - |
| Quiz | - | - |
| Listening | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 30 | 30 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 36 | 36 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 150 | ||
| Total Work Load / 30 | 5 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P5 |
|---|---|---|
| O1 | Explain managerial decision-making, computer-supported decision-making, and the fundamentals of business intelligence. | 5 |
| O2 | Explain the fundamentals, definitions, and capabilities of decision support systems. | 5 |
| O3 | Develop a decision support system for solving a specific problem as part of a team. | 5 |
| O4 | Develop Excel-based decision support system applications to solve different problems. | 5 |