The document provides an introduction to decision support systems (DSS). It defines DSS as an interactive computer-based system intended to help decision-makers use communications technologies, data, documents, knowledge and/or models to identify and solve problems, complete decision process tasks, and make decisions. DSS are designed to enhance a person or group's ability to make decisions by making the decision-making process more productive, agile, innovative and reputable. The document also discusses why DSS are important for handling increasing decision complexity, the availability of technology and information, as well as the pace of change. It emphasizes that a key goal of the course is for students to develop a final DSS project.

1. Introduction to Decision Support System Soetam Rizky

2. What is dss ?

3. DSS ? an interactive computer-based system or subsystem intended to help decision makers use communications technologies, data, documents, knowledge and/or models to identify and solve problems, complete decision process tasks, and make decision interactive computer-based system

4. DSS ? general term for any computer application that enhances a person or group’s ability to make decisions. enhances a person or group’s ability to make decisions.

5. DSS ? a computer-based system that represents and processes knowledge in ways that allow decision making to be more productive, agile, innovative, and/or reputable productive, agile, innovative, and/or reputable

6. DSS ? academic field of research that involves designing and studying Decision Support Systems in their context of use.

7. Before we continue…. DSS should be : interactive computer-based system enhances a person or group’s ability to make decisions More productive, agile, innovative, and/or reputable

8. DSS ?

9. Why we learn dss ?

10. DSS for IS Increasing complexity of decisions Technology Information: “Data, data everywhere, and not the time to think!” Number and complexity of options Pace of change Increasing availability of computerized support Inexpensive high-powered computing Better software More efficient software development process Increasing usability of computers

11. Let’s get realistic…. For your final project ? Fearness : Is it all about algorithm ? Is it hard to do ? Am I capable to do this ? Confusion : I don’t have the problem I am very weak at math Programming must be difficult

12. Let’s get realistic…. IS + DSS = Value added IS IS + DSS = easy to do IS + DSS = should be easy to represent IS + DSS = should be fast if you already have the IS IS + DSS = should be easier because you have focus in it

13. Before we continue… This course : should not teach many algorithms Should just teach the concept and introductory Should be resulting good project for your final project proposal Should become the door to open your mind before you graduate

14. Decision

15. Decision ? Decision: a reasoned choice among alternatives Examples: Where to advertise a new product What stock to buy What movie to see Where to go for dinner Decision Making: a process of choosing among alternative courses of action for the purpose of attaining a goal or goals

18. The problem is identified and defined

19. Representative model is constructed

20. The model is validated and evaluation criteria are set

21. Includes a proposed solution to the model

23. Before we continue….. So, is MIS course has already being forgotten ? Do you really think management science is non-sense ? Do you already think that expert system and artificial intelligence is nothing ? Have you already have final project proposal ?

24. 19 Information Characteristics

25. Before we continue…. Still remember these terms ? Data Information

26. Let’s take a break

27. What you will need…. Have you passed : Management Science Linear Algebra Expert System Artificial Intelligence Human Computer Interaction Management Information System

28. What you will need… Find a lot of : Problems domains Solutions feasibility Algorithms alternative Be creative for : Your final project Your future solution

29. What you will get… Introduction to DSS DSS architecture DSS modeling DSS implementation Simulation and solution Final project as final term

30. Quizzes Small quiz : Assignments Proposal Big quiz = presentation

31. Final project No group allowed Submit the proposal Present your proposal Implement your proposal If feasible, go on to your final project

32. Final project Proposal : week 2 Revision and finalization : week 3 -5 First presentation : week 6 – 7 Second presentation : 9 – 10 Final demo : 14 - 16

33. Proposal’s content Background Purposes Boundaries Submit it next week

34. Before we continue….. Please keep in mind, that the course is not about teaching algorithm It’s should be your final mandatory course in class So, it’s the aggregation of all your knowledge…..

35. taxonomies

36. Types of DSS uses storage and processing technologies to document retrieval and analysis. It manages, retrieves and manipulates unstructured information in a variety of electronic formats provides specialized problem solving expertise stored as facts, rules, procedures, or in similar structures. It suggest or recommend actions to managers. emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data intensive use network and communication technologies to facilitate collaboartion on decision making. It supports more than one person working on a shared task emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.

37. IS to support decisions

38. Before we continue…. Still thinking of common MIS ?

39. summary

40. What we already learn… DSS should be interactive, have ability to make decisions, become more productive, agile and innovative DSS is the aggregate of your knowledge

41. What we already learn… Decision making process from intelligence to implementation DSS includes analytical, ad hoc, adaptable and modeling before we implement them

42. Questions / Comments ?