1 Pertemuan 19 & 20 Managing Knowledge for the Digital Firm Matakuliah: J0454 / Sistem Informasi Manajemen Tahun: 2006 Versi: 1 / 1.
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Pertemuan 19 & 20Managing Knowledge for the Digital Firm
Matakuliah : J0454 / Sistem Informasi Manajemen
Tahun : 2006
Versi : 1 / 1
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Learning Outcomes
Pada akhir pertemuan ini, diharapkan mahasiswa
akan mampu :
• Mahasiswa akan dapat menunjukkan strategi penerapan Manajemen Pengetahuan C3
3
Outline Materi
• Concept of Knowledge Management
• Knowledge Management in the Organization
• Organization Learning and KM
• Artificial Intelligence
• Expert Systems
• Case-Based Reasoning
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Organizational learningOrganizational learning
• Creation of new standard operating Creation of new standard operating procedures and business processes procedures and business processes reflecting experience reflecting experience
Knowledge managementKnowledge management
• Set of processes Set of processes
• Creates, gathers, stores, maintains, and Creates, gathers, stores, maintains, and disseminates knowledgedisseminates knowledge
KNOWLEDGE MANAGEMENT IN THE ORGANIZATION
Organizational Learning and Knowledge Management
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Knowledge AssetsKnowledge Assets• Organizational knowledge enabling Organizational knowledge enabling
the business to create valuethe business to create value
Chief Knowledge Officer (CKO)Chief Knowledge Officer (CKO)
• Senior executive in charge of Senior executive in charge of organization’s knowledge management organization’s knowledge management programprogram
KNOWLEDGE MANAGEMENT IN THE ORGANIZATION
Organizational Learning and Knowledge Management
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Tacit KnowledgeTacit Knowledge
• Expertise and experience not formally Expertise and experience not formally documenteddocumented
Best PracticesBest Practices
• Successful solutions or problem-solving Successful solutions or problem-solving methods developed by specific methods developed by specific organization or industryorganization or industry
KNOWLEDGE MANAGEMENT IN THE ORGANIZATION
Systems and Infrastructure for Knowledge Management
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Organizational MemoryOrganizational Memory
• Stored learning from organization’s Stored learning from organization’s history history
• Used for decision making and other Used for decision making and other purposespurposes
KNOWLEDGE MANAGEMENT IN THE ORGANIZATION
Systems and Infrastructure for Knowledge Management
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• Consists of creating or processing Consists of creating or processing informationinformation
• Divided into knowledge workers and data Divided into knowledge workers and data workersworkers
INFORMATION AND KNOWLEDGE WORK SYSTEMS
Information Work
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Office systemsOffice systems
• Manage and coordinate work of data and Manage and coordinate work of data and knowledge workersknowledge workers
• Connect work of local information workers Connect work of local information workers with all levels and functions of organizationwith all levels and functions of organization
• Connect organization to external worldConnect organization to external world
• Example: Word processing, voice mail, and Example: Word processing, voice mail, and imagingimaging
INFORMATION AND KNOWLEDGE WORK SYSTEMS
Distributing Knowledge: Office and Document Management Systems
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Document imaging systems
• Convert documents and images into digital form
• Can be stored and accessed by the computer
Knowledge repository• Documented knowledge in a single
location
Typical Office Systems
INFORMATION AND KNOWLEDGE WORK SYSTEMS
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Knowledge Work Systems (KWS)• Aid knowledge workers in creation and
integration of new knowledge
• Specialized tools for specific types of knowledge work
• User-friendly interface
Creating Knowledge: Knowledge Work Systems
INFORMATION AND KNOWLEDGE WORK SYSTEMS
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Changes in the Construction Project Management Process
INFORMATION AND KNOWLEDGE WORK SYSTEMS
Figure 10-5
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• Computer-aided design (CAD)
• Virtual reality systems
• Virtual Reality Modeling Language (VRML)
• Investment workstations
Examples of Knowledge Work Systems
INFORMATION AND KNOWLEDGE WORK SYSTEMS
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• Groupware
• Intranets and Enterprise Knowledge Environments
• Enterprise information portals
• Teamware
Sharing Knowledge: Group Collaboration Systems and Enterprise Knowledge Environments
INFORMATION AND KNOWLEDGE WORK SYSTEMS
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• Effort to develop computer-based systems that behave as humans
• Includes natural language, robotics, perceptive systems, expert systems, and intelligent machines
ARTIFICIAL INTELLIGENCE
What is Artificial Intelligence?
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• Artificial Intelligence:
– Stores information in active form
– Creates mechanism not subjected to human feelings
– Eliminates routine and unsatisfying jobs
– Enhances organization’s knowledge base
– Generates solution to specific problems
Why Business is Interested in Artificial Intelligence
ARTIFICIAL INTELLIGENCE
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• Knowledge Base
• Rule-based Expert System
• Rule Base
• Knowledge Frames
Capturing Knowledge: Expert Systems
ARTIFICIAL INTELLIGENCE
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• AI shell
• Inference Engine
• Forward Chaining
• Backward Chaining
Capturing Knowledge: Expert Systems
ARTIFICIAL INTELLIGENCE
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Knowledge engineer
• Specialist eliciting information and expertise from other professionals
• Translates information into set of rules for an expert system
ARTIFICIAL INTELLIGENCE
Building an Expert System
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Case-based Reasoning (CBR)
• Captures and stores collective knowledge
• Represents knowledge as database of cases and solutions
Organizational Intelligence: Case-Based Reasoning
ARTIFICIAL INTELLIGENCE
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ARTIFICIAL INTELLIGENCE
Figure 10-11
Casedatabase
1.
2.
3.
4.
5. 6.
NO YES
Successful?
System modifies thesolution to better fit
the problem
System finds closestfit and retrieves
solution
System storesproblem and
successful solutionin the database
System asks useradditional questions to
narrow the search
System searchesdatabase for similar
cases
User describes theproblem
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• Hardware or software emulating processing patterns of biological brain
• Put intelligence into hardware in form of a generalized capability to learn
Neural Networks
OTHER INTELLIGENT TECHNIQUES
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Inference Engines in Expert Systems
ARTIFICIAL INTELLIGENCE
Figure 10-12
Synapse
Dendrite
Axon
Soma
Neuron
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• Rule-based AI
• Tolerates imprecision
• Uses nonspecific terms called membership functions to solve problems
Fuzzy Logic
OTHER INTELLIGENT TECHNIQUES
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• Problem-solving methods
• Promote evolution of solutions to specified problems
• Use a model of living organisms adapting to their environment
Genetic Algorithms
OTHER INTELLIGENT TECHNIQUES
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• Integration of multiple AI technologies into a single application
• Takes advantage of best features of technologies
Hybrid AI Systems
OTHER INTELLIGENT TECHNIQUES
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• Software programs
• Use built-in or learned knowledge base to carry out specific, repetitive, and predictable tasks
Intelligent Agents
OTHER INTELLIGENT TECHNIQUES
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