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Introduction to DSS


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Slide materi introduction to DSS

Slide materi introduction to DSS

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  • 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
    “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
    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
  • 16. Decision-Making Process
    • Solution to the original problem
    • 17. Failure: Return to the modeling process
    • Reality is examined
    • 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
    • 22. If reasonable, move on to the implementation
  • Type of Decision
  • 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 ?
  • 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 :
    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
    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 ?