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 Types of Decision Support System Decision Support System (DSS) Highly flexible &interactive IT system to support decision making for non-structured problems Group Decision Support System (GDSS) DSS that facilitates the formulation & the solutions to problems by a team Geographic Information System (GIS) DSS system specially designed to work with spatial information

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 Components of Decision Support System Data Management Performs storing function & information maintenance that DSS needs Model Management Model management component consists of both DSS models & DSS model management systems User Interface Management Is a component that enables user to communicate with DSS

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 Issue categorization & analysis Ranking & Voting 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 Components of Expert system Information types -Domain expertise -‘why’ information -Problem facts People -Domain expert -Knowledge engineer -Knowledge worker Components of Information Technology -Knowledge base -Knowledge acquisition -Inference engine -User interface -Explanation module

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.