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Kuliah Sistem Pakar Pertemuan V “Representasi Pengetahuan”

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Presentasi berjudul: "Kuliah Sistem Pakar Pertemuan V “Representasi Pengetahuan”"— Transcript presentasi:

1 Kuliah Sistem Pakar Pertemuan V “Representasi Pengetahuan”

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

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

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

5 Penjelasan ……… Deep knowledge atau pengetahuan formal, pengetahuan bersifat umum yang terdapat dalam sumber pengetahuan tertentu (buku, jurnal, buletin ilmiah dsb) dan dapat diterapkan dalam tugas maupun kondisi berbeda. Deep knowledge atau pengetahuan formal, pengetahuan bersifat umum yang terdapat 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. 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 Pengetahuan Heuristik Pengetahuan Heuristik Pengetahuan Prosedural Pengetahuan Prosedural Pengetahuan Deklaratif Pengetahuan Deklaratif Tipe-tipe Pengetahuan berdasar Cara Merepresentasikan

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

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

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

10 Symbols represent propositions, premises or conclusions 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 Propositional logic: limited in representing real-world knowledge

11 Propositional Logic A proposition is a statement that is either true or false 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 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 Rules are used to determine the truth (T) or falsity (F) of the new proposition

12 Propotional Logic Logic dapat digunakan untuk melakukan penalaran : Logic dapat digunakan untuk melakukan penalaran : Contoh : 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 Proses Logik Input Premise atau Fakta-Fakta Output Inferensi atau Konklusi

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

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

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

16 2) MERCEDES BENZ JERMAN PERAK MOBIL SAM GOLF OLAH- RAGA WAKIL PRESDIR ACME AJAX KAY LAKI- LAKI MANUSIA MAKANAN PEREM- PUAN ANAK LAKI- LAKI JOESEKOLAH pergi ke adala h perlu adalah mempunya i anak kawin dengan punyajabatan bekerja di anak perusahaa n bermain adalah merk buatan berwarna adalah

17 Script, List, Table, dan Tree

18 Scripts SCRIPT, skema representasi pengetahuan yang menggambarkan urutan dari kejadian. Elemen-elemen script terdiri dari : Elements include Elements include Entry Conditions Entry Conditions Props Props Roles Roles Tracks Tracks Scenes 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 Umumnya digunakan untuk merepresentasikan hirarki pengetahuan dimana suatu obyek dikelompokan, dikategorikan sesuai dengan Rank or Rank or Relationship 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. 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. List

20 DECISION TABLE, pengetahuan yang diatur dalam format lembar kerja atau spreadsheet, menggunakan kolom dan baris. 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 :… ? Contoh :… ? Decision Tabel

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

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

23 Object Attribute Values Object Attribute Values Rumah Kamar tidur 2,3,4, dsb. RumahWarna Hijau, Putih, Coklat dsb. Diterima di Universitas Nilai Ujian masuk A, B, C atau D Pengendalian persedian Level persediaan 15, 20, 25, 35, dsb. Kamar tidur Ukuran 3x4, 5x6, 4x5, dsb.

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. 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 Condition-Action Pairs IF this condition (or premise or antecedent) occurs, IF this condition (or premise or antecedent) occurs, THEN some action (or result, or conclusion, or consequence) will (or should) occur 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 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 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 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 can be viewed as a simulation of the cognitive behavior of human experts Rules represent a model of actual human behavior Rules represent a model of actual human behavior

27 Contoh : Production Rules RULE 1 : JIKA konflik internasional mulai RULE 1 : JIKA konflik internasional mulai MAKA harga emas naik MAKA harga emas naik RULE 2 : JIKA laju inflasi berkurang RULE 2 : JIKA laju inflasi berkurang MAKA harga emas turun RULE 3 : JIKA konflik internasional berlangsung lebih dari tujuh hari dan 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 Condition-Action Pairs IF this condition (or premise or antecedent) occurs, IF this condition (or premise or antecedent) occurs, THEN some action (or result, or conclusion, or consequence) will (or should) occur 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 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 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 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 can be viewed as a simulation of the cognitive behavior of human experts Rules represent a model of actual human behavior Rules represent a model of actual human behavior

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

31 Inclusion of ELSE 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 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 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.” 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" 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. 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) dan facet. Setiap frame mendefinisikan satu objek, dan terdiri dari dua elemen : slot (menggambarkan rincian dan karakteristik obyek) dan facet.

33 Frames Frame: Data structure that includes all the knowledge about a particular object Frame: Data structure that includes all the knowledge about a particular object Knowledge organized in a hierarchy for diagnosis of knowledge independence Knowledge organized in a hierarchy for diagnosis of knowledge independence Form of object-oriented programming for AI and ES. Form of object-oriented programming for AI and ES. Each Frame Describes One Object Each Frame Describes One Object Special Terminology 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 : 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 Car Frame Boat Frame Train Frame Airplane Frame Submarine Frame Passenger Car Frame Truck Frame Bus Frame Compact Car Frame Midsize Car Frame Toyota Corolla Frame Jan’s Car Frame Mary’s Car Frame Mitsubishi Lancer Frame

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