Rapor Tarihi: 13.04.2026 05:29
| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Enterprise Resource Planning I | YBS303 | Turkish | Compulsory | 5. Semester | 3 + 0 | 3.0 | 6.0 |
| Prerequisite Courses | |
| Course Level | Undergraduate |
| Mode of delivery | |
| Course Coordinator | Dr. Öğr. Üyesi Mustafa YANARTAŞ |
| Instructor(s) | |
| Goals | To understand the concept of algorithm analysis and to increase the ability of application development with example algorithms, to obtain information about different data structures. |
| Course Content |
| # | Öğrenme Kazanımı |
| 1 | Learning algorithm analysis methods. |
| 1 | Understands the functions of the business |
| 2 | Understands how integrated information systems can improve business processes and increase the welfare of an enterprise by providing fast, accurate data. |
| 2 | Mastering data structures. |
| 3 | Learning and use of tree data model structures of all types and especially common in the market. |
| 3 | Gains knowledge of corporate resource planning modules and their application and placement in the company. |
| 4 | Practical implementation of all subjects in C programming language |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | Business overview, introduction to ERP | Research |
| 1. Week | Basic Concepts | |
| 2. Week | Introduction to Algorithm Analysis Concept | |
| 2. Week | Basic concepts, risks and benefits of ERP, ERP technologies | Research |
| 3. Week | Functional Modules (HRM, Finance Management) | Research |
| 3. Week | Application with Algorithm Analysis and Programming Language | |
| 4. Week | Recursive Algorithms, Recursive Relations, Multidimensional / Triangle / Generation / Sparse Matrix Implementation | |
| 4. Week | Functional Modules (Product life-cycle management) | Research |
| 5. Week | Functional Modules (Purchasing and inventory management) | Research |
| 5. Week | Recursive Algorithms, Recursive Relations, Multidimensional / Triangle / Generation / Sparse Matrix Implementation with a program language | |
| 6. Week | Pre-cursor / Intermediate / Last Operator Expressions. Single / Double Coupled (Cycle) Lists | |
| 6. Week | Functional Modules (supplier relationship management, supply chain planning) | Research |
| 7. Week | Functional Modules (Warehouse and transportation management) | Research |
| 7. Week | Pre-cursor / Intermediate / Last Operator Expressions. Using Single / Double Concatenated (Cycle) Lists with a programming language | |
| 8. Week | MIDTERM EXAM | |
| 8. Week | Functional Modules (Accounting Management) | Research |
| 9. Week | Functional Modules (Production planning and control) | Research |
| 9. Week | Selection, Placement, Bubble, Counting, Quick, Associative, Batch, Step Ranking Algorithms and Analysis | |
| 10. Week | Coding of Selection, Placement, Bubble, Count, Quick, Associate, Batch, Step Sort Algorithms with a programming language | |
| 10. Week | Functional Modules (Maintenance planning and asset management) | Research |
| 11. Week | Stacks, Queues, and Applications | |
| 11. Week | Functional Modules (Quality management) | Research |
| 12. Week | Examples of series and structures | |
| 12. Week | Functional Modules (Sales and after-sales service management) | Research |
| 13. Week | Tree Data Structure | |
| 13. Week | Functional Modules (Customer relationship management) | Research |
| 14. Week | Binary Tree, Binary Search Tree, Recursive and Recursive Binary Tree Roots, Generalized Lists, Guided Binary Trees | |
| 14. Week | Installation and lifetime | Research |
| No | Program Requirements | Level of Contribution | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Graduates will have a holistic perspective on business functions | ✔ | |||||
| 2 | Graduates will have conceptual knowledge in the field of informatics in the sector average. | ✔ | |||||
| 3 | Graduates may integrate the business functions and IT infrastructure | ✔ | |||||
| 4 | Graduates will have awareness and knowledge about the processes of analyzing, designing, developing, and using information systems. | ✔ | |||||
| 5 | Students will have the ability to define the problem, collect data, analyze, interpret, evaluate, and develop a solution proposal for the solution of problems encountered in business. | ✔ | |||||
| 6 | Graduates may develop new strategic approaches for the efficiency of applications used in businesses. | ✔ | |||||
| 7 | Graduates may understand the logic of the algorithm and convert the designed algorithm into an up-to-date programming language. | ✔ | |||||
| 8 | Gradutes may have basic knowledge and understanding in the field of data science. | ✔ | |||||
| 9 | Graduates may have basic knowledge and understanding in the field of data science. | ✔ | |||||
| 10 | Graduates may base their vision on continuous learning and renewal. | ✔ | |||||
| 11 | Graduates may have an awareness of ethical and professional responsibility in business life. | ✔ | |||||
| 12 | Graduates may have an awareness of the individual and social effects of informatics applications and their legal consequences. gets the awareness of social responsibility. | ✔ | |||||
| 13 | Graduates may be able to use at least one foreign language in written and oral communication in the fields of information systems and business administration. | ✔ | |||||
| 14 | Graduates may take responsibility as an individual or team member in solving problems encountered in business life. | ✔ | |||||
| Program Requirements | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 | DK7 |
|---|---|---|---|---|---|---|---|
| PY1 | 0 | 5 | 5 | 0 | 0 | 5 | 0 |
| PY2 | 0 | 4 | 4 | 0 | 0 | 5 | 0 |
| PY3 | 0 | 5 | 5 | 0 | 0 | 5 | 0 |
| PY4 | 0 | 4 | 5 | 0 | 0 | 4 | 0 |
| PY5 | 0 | 5 | 5 | 0 | 0 | 5 | 0 |
| PY6 | 0 | 5 | 5 | 0 | 0 | 5 | 0 |
| PY7 | 0 | 4 | 3 | 0 | 0 | 4 | 0 |
| PY8 | 0 | 3 | 4 | 0 | 0 | 4 | 0 |
| PY9 | 0 | 5 | 5 | 0 | 0 | 5 | 0 |
| PY10 | 0 | 5 | 5 | 0 | 0 | 5 | 0 |
| PY11 | 0 | 4 | 4 | 0 | 0 | 4 | 0 |
| PY12 | 0 | 4 | 3 | 0 | 0 | 4 | 0 |
| PY13 | 0 | 1 | 1 | 0 | 0 | 1 | 0 |
| PY14 | 0 | 4 | 4 | 0 | 0 | 4 | 0 |
| Ders Kitabı veya Notu |
|
|---|---|
| Diğer Kaynaklar |
|
| ECTS credits and course workload | Quantity | Duration (Hour) | Total Workload (Hour) | |
|---|---|---|---|---|
|
Ders İçi |
Class Hours | 3 | 14 | 42 |
|
Ders Dışı |
Research | 3 | 14 | 42 |
|
Sınavlar |
Midterm | 1 | 20 | 20 |
| Homework | 1 | 9 | 9 | |
| Homework Preparation | 1 | 9 | 9 | |
| Final | 1 | 20 | 20 | |
| Classroom Activities | 1 | 11 | 11 | |
| Total Workload | 153 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 6.0 | ||
