MANAGEMENT INFORMATION SYSTEMS 8/E
Raymond McLeod, Jr. and George Schell
Chapter 13
Sistem Pendukung Keputusan
13-1
Copyright 2001 Prentice-Hall, Inc.
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
Simon’s Problem Solving Phases

Intelligence
–

Design
–

Menemukan, mengembangkan dan analisis alternatif
Choice
–

Amati lingkungan, cari kondisi yg perlu diperbaiki
Seleksi rangkaian tindakan dari beberapa alternatif yg
tersdia
Review
–
Menilai pilihan yang lalu
13-3
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
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
The Gorry and Scott Morton Grid
Management levels
Operational
control
Structured
Degree of
problem
structure
Semistructured
Unstructured
Management
control
Strategic
planning
Accounts
receivable
Budget analysis-engineered costs
Tanker fleet
mix
Order entry
Short-term
forecasting
Warehouse and
factory location
Inventory
control
Production
scheduling
Variance analysis-overall budget
Mergers and
acquisitions
Cash
management
Budget
preparation
New product
planning
PERT/COST
systems
Sales and
production
R&D planning
13-6
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
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
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
Alter’s DSS Types
Retrieve
information
elements
Little
Analyze
entire
files
Prepare
reports
from
multiple
files
Estimate
decision
consequences
Degree of
complexity of the
problem-solving
system
Propose
decisions
Make
decisions
Degree
of
problem
solving
support
Much
13-10
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
A DSS Model
Environment
Individual
problem
solvers
Report
writing
software
Other
group
members
GDSS
GDSS
software
software
Mathematical
Models
Database
Decision
support
system
Environment
Legend:
Data
Communication
Information
13-12
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
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
How GDSS Contributes
to Problem Solving
Meningkatkan komunikasi
 Memungkinkan diskusi
 Mengurangi waktu

13-15
User Interface

User entri :
– Instructions
– Information

}
Menus, commands, natural language, GUI
Sistem menyediakan:
– Solutions
– Explanations of
» Questions
» Problem solutions
13-16
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
A Rule Set That
Produces One Final
Conclusion
Conclusion
Conclusion
Evidence
Evidence
Conclusion
Evidence
Evidence
Evidence
Evidence
Evidence
Evidence
13-18
Rule Selection
Pemilihan aturan yang paling efisien untuk
memecahkan masalah yang paling sulit
 Bebrapa goal dapat dicapai dengan hanya
sejumlah aturan;

13-19
Inference Engine
Memakai knowledge based dengan suatu
urutan
 Dua pendekatan menggunakan rules

– 1. Forward reasoning (data driven)
– 2. Reverse reasoning (goal driven)
13-20
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
Rule 1
IF A
THEN B
Rule 2
T
Rule 7
F
IF B OR D
THEN K
IF C
THEN D
Rule 3
T
Rule 10
IF K AND
L THEN N
The Forward
Reasoning
Process
T
T
IF M
THEN E
Rule 8
Rule 12
T
IF N OR O
THEN P
IF E
THEN L
T
Rule 4
IF K
THEN F
T
Legend:
Rule 9
Rule 5
IF G
THEN H
T
IF (F AND H)
OR J
THEN M
T
First pass
Rule 11
IF M
THEN O
T
Second pass
Rule 6
IF I
THEN J
Third pass
F
13-22
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
Step 4
Rule 1
IF A THEN
B
T
Rule 2
Step 3
Rule 7
IF B OR D
THEN K
T
IF C
THEN D
The First Five Problems
Are Identified
Step 2
Rule 10
IF K AND L
THEN N
Step 5
Rule 3
IF N OR O
THEN P
Rule 8
IF M
THEN E
IF E
THEN L
Rule 11
Rule 9
13-24
Step 1
Rule 12
IF (F AND H)
OR J
THEN M
IF M
M
IF
THEN O
THEN
O
Legend:
Problems to
be solved
The Next Four Problems Are
Identified
Step 8
If N Or O
Then P T
Rule 4
If K
Then F
Rule 5
Rule 12
T
Step 7
Step 6
IF (F And H)
Or J
Then M T
If M
Then O
Step 9
If G
Then H
T
Rule 6
If I
Then J
Rule 9
T
Rule 11
Legend:
Problems to
be solved
13-25
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
Development Engine

Programming languages
– 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
Expert System Disadvantages
Can’t handle inconsistent knowledge
 Can’t apply judgment or intuition

13-28
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
The Human Brain

Neuron -- the information processor
– Input -- dendrites
– Processing -- soma
– Output -- axon

Neurons are connected by the synapse
13-30
Simple Biological Neurons
Soma
(processor)
Axonal Paths
(output)
Synapse
Axon
Dendrites
(input)
13-31