Chapter 4

1. Chapter 4 Decision Support System & Artificial Intelligence

2. Definition of decision • Decision making process is one of the most important activity. • 4 types of decision; • Structured – information processing using forms to get the most accurate & correct answer • Non-structured – information processing where there is few correct answers, no forms/rules. • Recurring – decision that happen repeatedly & often periodically. • Non-Recurring – decision made infrequently & have different criteria to use each time.

3. Decision making process • 4 phases; INTELLIGENCE Find what to fix DESIGN Find solution CHOICE Choose a solution IMPLEMENTATION Apply the solution

4. Decision making process • Intelligence (find what to fix) • Find & recognize a problem/need/opportunity (also called diagnostic phase of decision making) • Design (find solution) • Possible ways of solving problem & develop all the possible solutions you can • Choice (pick a solution) • Analyzing every possible solution, the effect & choosing the best depending on cost, implementation & employees demand. • Implementation (apply the solution) • Implementing the solution, evaluating the outcome & make necessary changes.

5. Types of decision support system

6. Decision Support System • Allows you to locate & use information effectively to help decision making in non-structured problem. • An alliance between decision maker & specialized support provided by IT • Advantages; • Improves productivity • Improves understanding • Improves work speed • Reduces complex problem • Reduces cost

7. Components of decision support system

8. Data management in DSS • Contains DSS information & DSS database management system. • 3 main sources of information; • Organizational information – any information obtained from the organization. Ex. Sales data • External information – information obtained from another organization. Ex. From internet • Personal information – information obtained from own insights & experience.

9. Model management in DSS • Model represents event, facts or situation that occurs. • DSS models may include; what-if model, optimization model, goal-seeking model & statistical model allowing you to analyze in many different ways. • Model management system stores & maintains the DSS models. Its function of managing model is similar to that of database management system.

10. User interface management • Consists of user interface & user interface management system. • It allows user to key in information, instruction and model to the system

11. Group Decision Support System (GDSS) • Facilitates the formulation & the solutions to problems by a team. • GDD facilitates GDSS process by integrating a group with; • Groupware • DSS capabilities • Telecommunication

12. Phase of Decision Making in GDSS Brainstorming – group members will come up with ideas to solve problem Issue categorization & analysis – group members will sort the ideas based on the classification & the idea will be evaluated. Ranking & voting – every group member will chose the suitable ideas in solving the problem. Highest voted idea will be selected.

13. Main components in GDSS • Main components; • Individual in GDSS • Information Technology Hardware in GDSS • Individual • 2 functions of individual in GDSS • Group members solve the problem – every member needs to cooperate & exchange ideas. • Facilitator who helps group to achieve goals – technical & non-technical role

14. Main components in GDSS • Information Technology Hardware in GDSS • Contains groupware, DSS & telecommunication • Groupware GDSS – any kind of software that allows a team to communicate & share documents. Able to support 3 phases of decision making. • Obtain idea (brainstorming) • Analyze idea (issue categorization) • Perform vote (ranking & voting)

15. Group Decision Support System (GDSS) • DSS capabilities • Depends to the type of decision made. The method of analysis such as what-if analysis, statistical analysis etc need to be used by information to present decision. • Telecommunication network • The hardware & software that connects computers.

16. Geographical Information System (GIS) • Specially designed to work with spatial information. • Spatial information – any information that can be shown in map form such as electrical line & roads. • GIS assists business from viewpoint of; • Determine which area is suitable to open a branch based on the area’s population • Determine the possibility of total client in specific area. • Hold the promotion & advertisement based by sale that is made. • Determine the optimal location of a new distribution outlet.

17. Geographical Information System (GIS) • Business geography – when business combines textual information & spatial information. • GIS is a combination of graphic technology & database. • GIS manipulates the spatial information & produce graphical result.

18. Types of Artificial Intelligence System • The techniques & software that enables computers to mimic human behavior in various ways. • 4 types of AI; • Expert System – reasons thru problems & advice in a form of conclusion/ recommendations • Neural Networks – can be programmed to recognize patterns • Genetic Algorithms – imitates evolution characteristics, implement the process of suitability to produce better decision. • Intelligent Agents – move around computer/networks to perform repetitive process on its own & adapt to your preferences.

19. Expert system • Components of Expert System

20. Expert system • Information types • Domain expertise – set of problem solving steps • ‘why’ information – information to inform about something • Problem facts – symptoms of & assertions about your problem. • People • Domain expert role – provides problem solving strategies • Knowledge engineer role – IT specialist who formulates the domain expertise into expert system • Knowledge worker role – a person who uses expert system.

21. Expert system • Information Technology components; • Knowledge base – stores the rules made by knowledge engineer. • Knowledge acquisition – used to enter the rules • Inference engine – takes your problems facts & searches the knowledge base for rules that fit. • User interface – interface of a system that you use to run the consultation. • Explanation module – keeping the ‘why’ information

22. Neural Networks • Imitates a person’s capability to classify certain things. • Suitable for identifying, classifying & forecasting based on collected information • Ex; DNA patterns, asimo..

23. Genetic Algorithms • Suitable to decide on a decision that has various possibilities of settlement. • Uses 3 evaluation concepts, that are; • Selection – process to select best solution • Crossover – process of combining few solutions • Mutation – process to change a solution randomly. • Ex ; criminal face sketch.

24. Intelligent Agent • Built from one or more modern technology software including expert system, genetic algorithms & object oriented programming. • 4 types of intelligent agent; • Find-and-retrieve agents • User agents • Monitor & surveillance agent • Data-mining agents

25. Intelligent Agent • Components of Intelligent agents; • Autonomy – act without you telling every step • Adaptivity – discovering, learning & taking action independently. • Sociability – able to confer with other agents.