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Kuliah Sistem Pakar Pertemuan V “Representasi Pengetahuan”

Kuliah Sistem Pakar Pertemuan V “Representasi Pengetahuan”. Proses Rekayasa Pengetahuan ( Knowledge Engineering Process). Sumber Pengetahuan. Validasi Pengetahuan. Akuisisi Pengetahuan. Basis Pengetahuan. Representasi Pengetahuan. Pengkodean. Justifikasi Penjelasan. Inferensi.

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Kuliah Sistem Pakar Pertemuan V “Representasi Pengetahuan”

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  1. Kuliah Sistem Pakar Pertemuan V“Representasi Pengetahuan”

  2. Proses Rekayasa Pengetahuan(Knowledge Engineering Process) Sumber Pengetahuan Validasi Pengetahuan Akuisisi Pengetahuan Basis Pengetahuan Representasi Pengetahuan Pengkodean Justifikasi Penjelasan Inferensi

  3. Knowledge Representation • Knowledge Representation is concerned with storing large bodies of useful information in a symbolic format. • Most commercial ES are rule-based systems where the information is stored as rules. • Frames may also be used to complement rule-based systems.

  4. Tipe-tipe Pengetahuan berdasar Sumber • Deep Knowledge (formal knowledge) • Shallow /Surface Knowledge (non formal knowledge)

  5. Penjelasan ……… • Deep knowledge atau pengetahuan formal, pengetahuan bersifat umum yangterdapat dalam sumber pengetahuan tertentu (buku, jurnal, buletin ilmiah dsb) dan dapat diterapkan dalam tugas maupun kondisi berbeda. • Shallow knowledge atau pengetahuan non formal,pengetahuan-pengetahuan praktis dalam bidang tertentu yang diperoleh seorang pakar pengalamannya pada bidang dalam jangka waktu cukup lama.

  6. Tipe-tipe Pengetahuan berdasar Cara Merepresentasikan • Pengetahuan Heuristik • Pengetahuan Prosedural • Pengetahuan Deklaratif

  7. Representasi Pengetahuan • Propotional Logic(logika proposional) • Semantic Network(jaringan semantik) • Script, List, Table, dan Tree • Object, Attribute, dan Values • Production Rule (kaidah produksi) • Frame

  8. Representation in Logic andOther Schemas • General form of any logical process • Inputs (Premises) • Premises used by the logical process to create the output, consisting of conclusions (inferences) • Facts known true can be used to derive new facts that also must be true

  9. Two Basic Forms of Computational Logic • Propositional logic (or propositional calculus) • Predicate logic (or predicate calculus)

  10. Symbols represent propositions, premises or conclusions Statement: A = The mail carrier comes Monday through Friday. Statement: B = Today is Sunday. Conclusion: C = The mail carrier will not come today. • Propositional logic: limited in representing real-world knowledge

  11. Propositional Logic • A proposition is a statement that is either true or false • Once known, it becomes a premise that can be used to derive new propositions or inferences • Rules are used to determine the truth (T) or falsity (F) of the new proposition

  12. Propotional Logic • Logic dapat digunakan untuk melakukan penalaran : Contoh : Pernyataan A = Pak Pos datang hari Senin sampai Sabtu Pernyataan B = Hari ini hari Minggu Kesimpulan C = Pak Pos tidak akan datang hari ini Input Premise atau Fakta-Fakta Output Inferensi atau Konklusi Proses Logik

  13. Predicate Calculus • Predicate logic breaks a statement down into component parts, an object, object characteristic or some object assertion • Predicate calculus uses variables and functions of variables in a symbolic logic statement • Predicate calculus is the basis for Prolog (PROgramming in LOGic) • Prolog Statement Examples • comes_on(mail_carrier, monday). • likes(jay, chocolate). (Note - the period “.” is part of the statement)

  14. Jaringan Semantik • Merupakan gambaran pengetahuan berbentuk grafis dan menunjukkan hubungan antar berbagai obyek. • Obyek, berupa benda atau peristiwa • Nodes Obyek • Arc (Link) Keterhubungan (Relationships) * is a * has a

  15. Contoh : 1) Human Being Is a Boy Is a Is a Needs Goes to Woman Joe School Is a Food Has a child Kay

  16. 2) ANAK LAKI- LAKI MANUSIA adalah adalah PEREM- PUAN SEKOLAH pergi ke JOE adalah perlu adalah KAY MAKANAN LAKI- LAKI mempunyai anak kawin dengan adalah MOBIL punya SAM jabatan WAKIL PRESDIR bekerja di ACME merk anak perusahaan bermain berwarna MERCEDES BENZ GOLF AJAX buatan adalah PERAK OLAH- RAGA JERMAN

  17. Script, List, Table, dan Tree

  18. Scripts SCRIPT,skema representasi pengetahuan yang menggambarkan urutan dari kejadian. Elemen-elemen script terdiri dari : • Elements include • Entry Conditions • Props • Roles • Tracks • Scenes • Contoh : Script “Ujian Akhir Semester”

  19. List • LIST, daftar tertulis dari item-item yang saling berhubungan. • Umumnya digunakan untuk merepresentasikan hirarki pengetahuan dimana suatu obyek dikelompokan, dikategorikan sesuai dengan • Rank or • Relationship • Contoh : berupa daftar orang yang anda kenal, benda-benda yang harus dibeli di pasar swalayan, hal-hal yang harus dilakukan minggu ini, atau produk-produk dalam suatu katalog.

  20. Decision Tabel • DECISION TABLE,pengetahuan yang diatur dalam format lembar kerja atau spreadsheet, menggunakan kolom dan baris. Attribute List Conclusion List Different attribute configurations are matched against the conclusion • Contoh :… ?

  21. Decision Trees • DECISION TREE,tree yang berhubungan dengan decision table namun sering digunakan dalam analisis sistem komputer (bukan sistem AI). • Contoh :… ? • Related to tables • Similar to decision trees in decision theory • Can simplify the knowledge acquisition process • Knowledge diagramming is frequently more natural to experts than formal representation methods

  22. Object, Attribute, Values OBJECT : • OBJECT dapat berupa fisik atau konsepsi. ATTRIBUTE : • ATTRIBUTE adalah karakteristik dari object. VALUES : • VALUES adalah ukuran spesifik dari attribute dalam situasi tertentu

  23. Object Attribute Values

  24. Production Rules PRODUCTION RULES: • Production system dikembangkan oleh Newell dan Simon sebagai model dari kognisi manusia. Ide dasar dari sistem ini adalah pengetahuan digambarkan sebagai production rules dalam bentuk pasangan kondisi-aksi.

  25. Production Rules • Condition-Action Pairs • IF this condition (or premise or antecedent) occurs, • THEN some action (or result, or conclusion, or consequence) will (or should) occur • IF the stop light is red AND you have stopped, THEN a right turn is OK

  26. Each production rule in a knowledge base represents an autonomous chunk of expertise • When combined and fed to the inference engine, the set of rules behaves synergistically • Rules can be viewed as a simulation of the cognitive behavior of human experts • Rules represent a model of actual human behavior

  27. Contoh : Production Rules • RULE 1 : JIKA konflik internasional mulai MAKA harga emas naik • RULE 2 : JIKA laju inflasi berkurang MAKA harga emas turun • RULE 3 : JIKA konflik internasional berlangsung lebih dari tujuh hari dan JIKA konflik terjadi di Timur Tengah MAKA beli emas

  28. Production Rules • Condition-Action Pairs • IF this condition (or premise or antecedent) occurs, • THEN some action (or result, or conclusion, or consequence) will (or should) occur • IF the stop light is red AND you have stopped, THEN a right turn is OK

  29. Each production rule in a knowledge base represents an autonomous chunk of expertise • When combined and fed to the inference engine, the set of rules behaves synergistically • Rules can be viewed as a simulation of the cognitive behavior of human experts • Rules represent a model of actual human behavior

  30. Forms of Rules • IF premise, THEN conclusion • IF your income is high, • THEN your chance of being audited by the IRS is high • Conclusion, IF premise • Your chance of being audited is high, IF your income is high

  31. Inclusion of ELSE • IF your income is high, OR your deductions are unusual, THEN your chance of being audited by the IRS is high, OR ELSE your chance of being audited is low • More Complex Rules • IF credit rating is high AND salary is more than $30,000, OR assets are more than $75,000, AND pay history is not "poor," THEN approve a loan up to $10,000, and list the loan in category "B.” • Action part may have more information: THEN "approve the loan" and "refer to an agent"

  32. Frame • FRAME adalah struktur data yang berisi semua pengetahuan tentang obyek tertentu. Pengetahuan ini diatur dalam suatu struktur hirarkis khusus yang memperbolehkan diagnosis terhadap independensi pengetahuan. Frame pada dasarnya adalah aplikasi dari pemrograman berorientasi objek untuk AI dan ES. • Setiap frame mendefinisikan satu objek, dan terdiri dari dua elemen : slot (menggambarkan rincian dan karakteristik obyek) danfacet.

  33. Frames • Frame: Data structure that includes all the knowledge about a particular object • Knowledge organized in a hierarchy for diagnosis of knowledge independence • Form of object-oriented programming for AI and ES. • Each Frame Describes One Object • Special Terminology

  34. Contoh Frame Automobile Frame Class of : Transportation Name of Manufacturer : Audi Origin of Manufacturer : Germany Model : 5000 turbo Type of Car : Sedan Weight : 3000 lbs. Wheelbase : 105.8 inches Number of doors : 4 (default) Transmission : 3-speed (automatic) Number of wheels : 4 (default) Gas mileage : 22 mpg average (procedural attachment) Engine Frame Cylinder bore : 3.19 inches Cylinder stroke : 3.4 inches Compression ratio : 7.8 to 1 Fuel system : Injection with turbocharger Horsepower : 140 hp Torque : 160 ft/Lbs

  35. Hirarki Frame (exp : Vehicle) Vehicle Frame Train Frame Boat Frame Car Frame Airplane Frame Submarine Frame Passenger Car Frame Truck Frame Bus Frame Compact Car Frame Midsize Car Frame Toyota Corolla Frame Mitsubishi Lancer Frame Mary’s Car Frame Jan’s Car Frame

  36. Sampai Jumpa di Pertemuan VISelamat Belajar

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