Information Package

Master's of Industrial Engineering with Thesis

END536

DECISION SUPPORT SYSTEMS

Course Code
END536
Semester
-
Theory+Practice
3 + 0
ECTS
10
Course TypeElective Course
Course LevelMaster's Degree With Thesis
Year of Study-
Semester-
ECTS10
Name of Lecturer(s)
Learning Outcomes

At the end of this course, the students;

  1. Gain an ability to select and practice the appropriate methods and technologies on decision problems
  2. Gain an ability to design a decision support system and its components professionally to meet the requirements
  3. Determine, formulate and solve the semi structured decision problems systematically.
  4. Use the qualitative and quantitative methods within decision support systems
  5. Gain an ability to transform technologies into engineering solutions.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNone
Course Description
Course Contents
WEEK TOPICS
1st Week Introduction to DSS and business intelligence
2nd Week Intro to DSS development in Excel and VBA
3rd Week Excel object model and VBE
4th Week Macros and VBA
5th Week Range objects
6th Week Control logic and loops
7th Week Other Excel objects
8th Week Midterm
9th Week Arrays, variables and subroutines
10th Week User forms and error handling
11th Week Working with Files and folders
12th Week Importing data into Excel
13th Week Working with pivot tables
14th Week Menus and toolbars,Data mining in Excel
Recommended or Required Reading(1) Christian Albright. VBA for Modelers: Developing Decision Support Systems with Microsoft Office Excel 4'ncü baskı (2011).
(2) Turban and Aronson. Decision Support Systems and Business Intelligence Systems. Prentice-Hall Publishing Co. Eight Edition.
Planned Learning Activities and Teaching Methods
  • Practice
  • Lecture
  • Questions/Answers
  • Problem Solving
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Project 1 30
Total(%) 60
Contribution of In-term Studies to Overall Grade(%) 60
Contribution of Final Examination to Overall Grade(%) 40
Total(%) 100
ECTS Allocated Based on Student Workload
Activities Quantity Duration (Hour) Total Workload (Hour)
Midterm exam 1 2 2
Preparation for Quiz
Individual or group work 14 14 196
Preparation for Final exam 1 25 25
Course hours 14 3 42
Preparation for Midterm exam 1 25 25
Laboratory (including preparation)
Final exam 1 2 2
Homework 1 14 14
Total Work Load306
Total Work Load / 30 (h)10.2
ECTS Credit of the Course10
Language of InstructionTurkish
Work Placement(s)No
LO1 LO2 LO3 LO4 LO5
K1 X
K2 X X X X
K3 X X X
K4 X X X X
K5
K6
K7
K8
K9
K10
K11