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Chapter 13 Sistem Pendukung Keputusan

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1 Chapter 13 Sistem Pendukung Keputusan
MANAGEMENT INFORMATION SYSTEMS 8/E Raymond McLeod, Jr. and George Schell Chapter 13 Sistem Pendukung Keputusan 13-1 Copyright 2001 Prentice-Hall, Inc. 1

2 Jenis Keputusan (Simon’s)
Keputusan terprogram repetitive and routine Aturan/procedure terdefinisi Keputusan tak terprogram Uraian dan tak terstruktur Tak ada metode langsung menanganinya Berada pada ujung suatu kesatuan 13-2

3 Simon’s Problem Solving Phases
Intelligence Amati lingkungan, cari kondisi yg perlu diperbaiki Design Menemukan, mengembangkan dan analisis alternatif Choice Seleksi rangkaian tindakan dari beberapa alternatif yg tersdia Review Menilai pilihan yang lalu 13-3 3

4 Definitions of a Decision Support System (DSS)
General definition - a system providing both problem-solving and communications capabilities for semistructured problems Specific definition - a system that supports a single manager or a relatively small group of managers working as a problem-solving team in the solution of a semistructured problem by providing information or making suggestions concerning specific decisions. 13-4 2

5 The DSS Concept Gorry and Scott Morton memakai istilah ‘DSS’ pada 1971, 10 tahun setelah MIS dipopulerkan Dasarnya adalah struktur masalah Masalah terstruktur adalah yang dapat ditangani dengan algorithms and decision rules Masalah tidak terstruktur sama sekali tidak memiliki struktur 3 tahap Simon Semistructured mengandung terstruktur dan tidak terstruktur 13-5

6 The Gorry and Scott Morton Grid
Management levels Operational control Management control Strategic planning Structured Accounts receivable Order entry Inventory control Budget analysis-- engineered costs Short-term forecasting Tanker fleet mix Warehouse and factory location Degree of problem structure Semistructured Production scheduling Cash management PERT/COST systems Variance analysis-- overall budget Budget preparation Sales and production Mergers and acquisitions New product planning R&D planning Unstructured 13-6 5

7 Alter’s DSS Types Kerangka DSS Steven Alter(1976)
Taksonomi 6 jenis DSS Berdasarkan survai pada 56 DSS Pengklasifikasian DSS berdasar “tingkat dukungan terhadap pengambilan keputusan” 13-7

8 Levels of Alter’s DSSs Level of problem-solving support from lowest to highest Mengambil elemen-2 informasi Menganalisa emua file Menyiapkan report dari berbagai file Memperkirakan akibat keputusan Mengusulkan keputusan Membuat keputusan 13-8

9 Importance of Alter’s Study
Didukung oleh konsep mengembangkan sistem utk menangani keputusan tertentu Menjelaskan bahwa DSS tidak terbatas pada pendekatan yang lebih eksotik daripada query database. 13-9

10 Alter’s DSS Types Little Much Degree of problem solving support
Retrieve information elements Analyze entire files Prepare reports from multiple files Estimate decision consequen-ces Propose decisions Make decisions Degree of complexity of the problem-solving system Little Much 13-10 8

11 Based on studies of Keen and Scott-Morton
Three DSS Objectives 1. Membantu manajer membuat keputusan untuk masalah semiterstruktur 2. Mendukung penilaian oleh manajer bukan mengganti tugas mereka 3. Meningkatkan efektifitas keputusan Based on studies of Keen and Scott-Morton 13-11 10

12 A DSS Model support system problem solvers group members Report
Environment Individual problem solvers Other group members Report writing software Mathematical Models GDSS software GDSS software Database Decision support system Environment Data Communication Information Legend: 13-12 11

13 Database Contents Memakai tiga jenis software S/W report writer
Special reports Periodic reports DBMS Model matematika Simulasi Bahasa pemodelan khusus Groupware atau GDSS 13-13 12

14 Group Decision Support Systems
Sistem berbasis komputer mendukung kelompokdalam tugas-2 nya dan membantu menghubungkan dengan lingkungannya. Dipakai dalam problem solving Bidang-2 yang berhubungan : Electronic meeting system (EMS) Computer-supported cooperative work (CSCW) Group support system (GSS) Groupware 13-14 13

15 How GDSS Contributes to Problem Solving
Meningkatkan komunikasi Memungkinkan diskusi Mengurangi waktu 13-15

16 } User Interface User entri : Sistem menyediakan: Instructions
Information Sistem menyediakan: Solutions Explanations of Questions Problem solutions } Menus, commands, natural language, GUI 13-16 8

17 Knowledge Base Description of problem domain Rules
Knowledge representation technique ‘IF:THEN’ logic Networks of rules Lowest levels provide evidence Top levels produce 1 or more conclusions Conclusion is called a Goal variable. 13-17 9

18 A Rule Set That Produces One Final Conclusion Conclusion Conclusion
Evidence Evidence Evidence Evidence Evidence Evidence Evidence Evidence 13-18 10

19 Rule Selection Pemilihan aturan yang paling efisien untuk memecahkan masalah yang paling sulit Bebrapa goal dapat dicapai dengan hanya sejumlah aturan; 13-19 12

20 Inference Engine Memakai knowledge based dengan suatu urutan
Dua pendekatan menggunakan rules 1. Forward reasoning (data driven) 2. Reverse reasoning (goal driven) 13-20 13

21 Forward Reasoning (Forward Chaining)
Rule is evaluated as: (1) true, (2) false, (3) unknown Rule evaluation is an iterative process When no more rules can fire, the reasoning process stops even if a goal has not been reached Start with inputs and work to solution 13-21 14

22 The Forward Reasoning Process Rule 1 T F T T Rule 8 T T T T Rule 5
IF A THEN B Rule 7 IF B OR D THEN K Rule 10 Rule 2 F IF K AND L THEN N IF C THEN D T T Rule 3 Rule 8 Rule 12 T T IF N OR O THEN P IF M THEN E IF E THEN L T Rule 4 T IF K THEN F Legend: First pass Rule 9 Rule 5 Rule 11 T T IF (F AND H) OR J THEN M IF G THEN H IF M THEN O Second pass T Rule 6 F Third pass IF I THEN J 13-22 15

23 Reverse Reasoning Steps (Backward Chaining)
Divide problem into subproblems Try to solve one subproblem Then try another Start with solution and work back to inputs 13-23 16

24 The First Five Problems
Step 4 The First Five Problems Are Identified Rule 1 Step 3 IF A THEN B Rule 7 Step 2 T IF B OR D THEN K Rule 10 Step 1 Rule 2 T IF K AND L THEN N Rule 12 IF C THEN D IF N OR O THEN P Step 5 Rule 3 Rule 8 IF M THEN E IF E THEN L Rule 11 Legend: Problems to be solved IF (F AND H) OR J THEN M IF M THEN O IF M THEN O Rule 9 13-24

25 The Next Four Problems Are
Identified Rule 12 Step 8 If N Or O Then P Rule 4 If K Then F T T Step 7 Step 6 Step 9 Rule 5 If G Then H If M Then O IF (F And H) Or J Then M T T T Rule 9 Rule 11 Legend: Problems to be solved Rule 6 If I Then J 13-25

26 Forward Versus Reverse Reasoning
Reverse reasoning lebih cepat Reverse reasoning lebih cocok untuk beberapa kondisi Jika variabel sasarannya banyak Jika banyak rules Semua rules tidak memerlukan penjelasan prosesnya dalam mencapai sebuah solusi 13-26 21

27 Development Engine Programming languages Expert system shells
Lisp Prolog Expert system shells Ready made processor that can be tailored to a particular problem domain Case-based reasoning (CBR) Decision tree 13-27 23

28 Expert System Disadvantages
Can’t handle inconsistent knowledge Can’t apply judgment or intuition 13-28 31

29 Keys to Successful ES Development
Coordinate ES development with strategic planning Clearly define problem to be solved and understand problem domain Pay particular attention to ethical and legal feasibility of proposed system Understand users’ concerns and expectations concerning system Employ management techniques designed to retain developers 13-29

30 The Human Brain Neuron -- the information processor
Input -- dendrites Processing -- soma Output -- axon Neurons are connected by the synapse 13-30 33

31 Simple Biological Neurons
Soma (processor) Axonal Paths (output) Synapse Axon Dendrites (input) 13-31


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