modeling and analysis pertemuan-4 mata kuliah: csm211, management support system tahun akademik:...
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MODELING AND ANALYSISPertemuan-4
Mata Kuliah : CSM211, Management Support SystemTahun Akademik : 2014/2015
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Sasaran Pembelajaran• Understand the basis concepts of MSS modeling• Describe how MSS models interact with data and the user• Understand of different model classes• Understand how the structure decision making of a few alternatives• Describe how spreadsheets can be used for MSS modeling and
solution• Explain what optimization, simulation, and heuristics are, and when
and how to use them• Describe how to structure a linear programming model• Become familiar with some capabilities of linear programming and
simulation packages• Understand how search methods are used to solve MSS models• Explain what is meant by sensitivity, automatic, what if analysis, and
goal seeking• Describe the key issues of model management
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Target Pembelajaran
The student can shows relationship between system models management (MBMS) to Decision Support System (DSS)
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MSS MODELING
• IDENTIFICATION OF THE PROBLEM AND ENVIRONMENTAL ANALYSIS
• VARIABLE IDENTIFICATION• FORECASTING• MULTIPLE MODELS• MODEL CATEGORIES• MODEL MANAGEMENT• KNOWLEDGE BASED MODELING• CURRENT TRENDS
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STATIC AND DYNAMIC MODELS
• Static AnalysisTake a single snapshot of a situation
• Dynamic Analysis– Time Dependent– Represent or generate trends and patterns
over time
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MODEL
1. Algorithm Based Model
Create model with algoritm formula to calculate on DSS model
Example : cost estimate formula
2. Statistic Based :
Creat models with statistic formula
Example : forecasting
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3. Linier Programming
Create models to determine ”the best” from others choice combination
4. Graphical Model, Quantitative Model, Qualitative Model, Simulation
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Influence Diagrams
A Graphical representation of a model used to assist in model design, development, and understanding.
CHARACTERICS :- Provide representation model graphic and visual
communication- Framework for expressing a modeler in focusing on
the models - Explain determining between variable- Show impact change of analisis what If 4-8
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Influence Diagrams
Decision Intermediate or uncontrollable
Variables:
Result or outcome (intermediate or final)
Certainty
Uncertainty
Arrows indicate type of relationship and direction of influence
Amount in CDs
Interest earned
Price
Sales
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Influence Diagrams
Random (risk)
Place tilde above variable’s name
~ Demand
Sales
Preference
(double line arrow)
Graduate University
Sleep all day
Ski all day
Get job
Arrows can be one-way or bidirectional, based upon the direction of influence 4-10
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An Influence Diagram for the profit model
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MSS Modeling with SPREADSHEETS
The most popular end user modeling tool Qucikly recognized as easy to use
implementation sofware Modeling tool orientation end user Provide linier programming and Regresi
analysis with fiture analysis what If, data management and macro
Consolidated from static and dinamic
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Excell spreadsheet Dynamic model example of a simple loan calculation of monthly payment and the
effects of pre payments
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Decision Table
Analysis decision making with multi criteria Provide fiture :
- Decision variable (choice alternative)- Uncontrolllable variable (independent)- Variable as Result
Provide principle of certainly, uncertainty and risk
Show relationship variable with graphics Multy Criteria Show relationship complixity Difficult analysis if there are many alternative
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Model Matematical Tools used to problem solving for the
managerial levels User have to provide resources about activity
competity Determine optimitation specific goals Linier Programming :
Decision variable, Objective function, and Coefisien, Uncontrol variable (constraint), capacibility and coefisien output
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Multiple Goal
Managerial can know how to the goals by simultance can interative
Determine one goals from achieve effectively that complexity issue
Handle by method :
- Utility Theory
- Program Goal
- Linier programming by goal and constraint
- System Point4-16
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SENSITIVITY ANALYSIS Makes prediction and assumptions regarding the input
data, many of which the assessment of uncertain futures
The impact of change in external (uncontrolable) variables and parameters on outcome variable
Impact of changes in decision variable on outcome variable
The efect of uncertainly in estimating external variable The effect of different dependent interactions among
variable The rebustness of decision under changing conditions Allows adaptation and flexibility to changing
conditions Trial and error simulation 4-17
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Sensitivity Analysis are used for Revising models to eliminate too large
sensitivities Adding details about sensitive varible or
scenario Obtaining better estimates of sensitive external
variable Altering the real word system to reduce actual
sensitivities Accepting and using the sensitive real world,
leading to continuous and close monitoring of actual results
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What If Analysis and Goal Seeking What If Analysis
Makes assessment result based on changing variable and the assumptionsAssuming the appropriate user interface, easy for manager to ask computer model
Goal SeekingCalculate the values of the inputs to achieve output (goal) Represent a backward solution approachExample : Break Event Point (BEP) Analysis 4-19
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PROBLEM SOLVING SEARCH METHODS
• Search approaches• Analytical Techniques• Algorithms• Blind Search• Heuristic Search
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SIMULATION Technique for conducting experiments (exp :
what if) with a computer on a model of a management system
Make the assumption result characterics from the actual
CHARACTERICS :- Making trial error s (assumption) from the reality- Provide experiement- Descriptive (not normative)- Complexity can increasing, need specific expert
- Handle unstructure problems- No garantive, result optimal
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METHODOLOGY OF SIMULATION• Problem definition• Construction of the simulation model• Testing and validating the model• Design of the experiment• Conduction the experiment• Evaluation the results• Implementation
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The Process of Simulation
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MODEL BASE MANAGEMENT SYSTEM (MBMS)
MBMS is a software package with capatibilites similar to those of a DBMS
Limited MBMS capabilities are provided by some spreadsheets and other model based DSS tools and languanges
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MODEL BASE MANAGEMENT SYSTEM (MBMS)
• Control• Flexibility• Feedback• Interface• Redundancy Reduction• Increased Consistency
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MODELING LANGUAGE
Relational MBMSProvide virtual file and virtual relation (executive, optimation, sensitivity analysis)
Object Oriented MBMSIndependent logical between based on model based and other DSS component (Data Management, User Interface & KMS)
Model Database and MISData dictionary, Entity Relationship Diagram (ERD) with Case 4-26
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=============== thanks 4 your attention ============
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