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

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

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

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

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

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

=============== thanks 4 your attention ============

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