Developing Knowledge Management dalam perusahaan Week 10 – Pert 19 & 20 (Off Class Session)

Agenda  Peran AI dalam mengembangkan Knowledge Management (lihat artikel pendukung tentang AI)  Membuat suatu sistem Knowledge Management sederhana untuk organisasi

Tujuan  Mahasiswa mampu menciptakan suatu sistem Knowledge Management sederhana untuk organisasi

To Do  Pelajari dan pamahi artikel tentang Artificial Intelligence  Pelajari slide-slide pendukung berikut tentang Artificial Intelligence

Tugas off Class  Ambil perusahaan sebagai sample untuk pembangunan Knowledge Management  Lakukan analisa untuk kebutuhan knowledge management yang perlu dibangun diperusahaan  Bangun aplikasi untuk Knowledge Management yang diperlukan

Tugas off Class  Aplikasi yang dibangun harus berisi:  Secara umum tentang perusahaan atau aplikasi KM  Workflow  Document Management  Communication system ( , messages or forum)  Info center / contact centre (seperlunya)

 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?

 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

The Artificial Intelligence Family ARTIFICIAL INTELLIGENCE

 Knowledge Base  Rule-based Expert System  Rule Base  Knowledge Frames Capturing Knowledge: Expert Systems ARTIFICIAL INTELLIGENCE

Rules in an AI Program ARTIFICIAL INTELLIGENCE

 AI shell  Inference Engine  Forward Chaining  Backward Chaining Capturing Knowledge: Expert Systems ARTIFICIAL INTELLIGENCE

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

 Galeria Kaufhof  Countrywide Funding Corp. ARTIFICIAL INTELLIGENCE Examples of Successful Expert Systems

Case-based Reasoning (CBR)  Captures and stores collective knowledge  Represents knowledge as database of cases and solutions Organizational Intelligence: Case-Based Reasoning ARTIFICIAL INTELLIGENCE

Case database NOYES Successful? System modifies the solution to better fit the problem System finds closest fit and retrieves solution System stores problem and successful solution in the database System asks user additional questions to narrow the search System searches database for similar cases User describes the problem

 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

Inference Engines in Expert Systems ARTIFICIAL INTELLIGENCE

Biological Neurons of a Leech OTHER INTELLIGENT TECHNIQUES

 Rule-based AI  Tolerates imprecision  Uses nonspecific terms called membership functions to solve problems Fuzzy Logic OTHER INTELLIGENT TECHNIQUES

Implementing Fuzzy Logic Rules in Hardware OTHER INTELLIGENT TECHNIQUES Figure 10-15

 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

The Components of a Genetic Algorithm OTHER INTELLIGENT TECHNIQUES

 Integration of multiple AI technologies into a single application  Takes advantage of best features of technologies Hybrid AI Systems OTHER INTELLIGENT TECHNIQUES

 Software programs  Use built-in or learned knowledge base to carry out specific, repetitive, and predictable tasks Intelligent Agents OTHER INTELLIGENT TECHNIQUES