Decision Support System ( DSS )
Definition of Decision Support System / Decision Support System ( DSS )Decision support system is an interactive information system yangmenyediakan information , modeling and manipulating the data . Itudigunakan
system to assist decision-making in situations yangsemiterstruktur and
unstructured situations , where tahusecara seoranpun not sure how
decisions should be made . [ 2 ] Decision support systems are usually constructed to support solusiatas a problem or to evaluate an opportunity . Pendukungkeputusan system called a decision support system applications penggambilan those used in the decision . Application
of data keputusanmenggunakan support system , providing an easy user
interface and dapatmenggabungkan thinking decision making . Keputusantidak
support system intended to automate the decision making ,
tetapimemberikan interactive tools that allow retrieval keputusanuntuk
perform a variety of analyzes using the model - a model that
tersedia.Ditinjau of the level of technology , decision support systems
dibagimenjadi 3 , namely [ KUS07 ] : 1 . SpesifikSPK specific DSS aims to help solve a particular problem dengankarakteristik . For example , DSS unit pricing of goods . 2 . Generating SPKSuatu dedicated software used to build and develop a DSS . DSS will facilitate the generation perancangdalam build SPK spesifik.3 . SPKBerupa
supplies software and hardware used and the specific DSS or
mendukungpembangunan SPK.Keputusan plants are taken to solve a problem
that can be seen dariketerstrukturannya divided into [ KUS07 ] : 1 . Structured Decision ( Structured Decision) is a structured decision -making is done repeatedly and routine .Decision-making
procedures is jelas.Keputusan was mainly done at the management level
bawah.Misalnya , ordering goods and decision -making hutang2 billing . Semistructured
decision ( Decision semistructured ) semistructured decision is a
decision that has two sifat.Sebagian decisions can be handled by
computers and other remains should be done by decision makers . The
procedures in the pengambilankeputusan outline already exists , but
there are some that still require POINTS of policy makers
keputusan.Biasanya , these kind of decisions taken by managers
menengahdalam levels of an organization . Examples of this type of decision is pengevaluasiankredit , production scheduling and control sediaan.3 . Unstructured
decisions ( Unstructured Decision) unstructured decision is a decision
that does not happen over rumitkarena handling - again or not always the
case . Keputusantersebut
requires both experience and a variety of sources that are
eksternal.Keputusan generally occurs at the level of atas.Contohnya
aalah management decisions for the development of new technologies ,
keputusanuntuk merged with another company , and executive recruitment .
sources :
10 Definition of Decision Support Systems ( DSS )
The concept of Decision Support Systems ( DSS ) / Decision Support Systems ( DSS ) was first proposed in the early 1970s by Michael S. Scott Morton with the term Management Decision Systems . The system is a computer -based system intended to help decision makers to utilize data and models to solve certain problems that are not terstruktur.Istilah DSS refers to a system that utilizes computer support in the decision-making process . To provide a deeper understanding , will describe 10 definitions of the Decision Support System / Decision Support System developed by some experts .
10 opinions on the definition of decision support systems :1 . Little ( 1970 )Decision support system is a set / set of model-based procedures for processing data and judgments to assist management in decision -making .
2 . Alter (1990 ) makes the definition of a decision support system memabandingkannya with a system of electronic data processing ( EDP ) / traditional Electronic Data Processing in 5 ways:
SPKUsage : ActiveUser ManagementObjective : EffectivenessTime horizon : Present and futurePros : Flexibility
PDEUsage : PassiveUser : Operator / EmployeeObjective : Mechanical EfficiencyTime horizon : The PastPros : Consistency
3 . Keen (1980 )Decision support systems are computer -based systems that are built through a process of adaptive learning , patterns of use and the evolution of the system .
4 . Bonczek ( 1980 )Decision support system as a computer -based system that consists of components include components of the language system ( language ) , system component knowledge (knowledge ) and component processing system problems ( processing ) which interact with each other .
5 . Hick (1993 )Decision support systems as an integrated set of computer tools that allow a decision maker to interact directly with a computer to create information that is useful in making decisions on semi-structured and unstructured decisions are not anticipated .
6 . Man and WatsonDecision support system is an interactive system , which helps decision-makers through the use of data and decision models to solve problems that are semi- structured or unstructured .
7 . Moore and ChangDecision support systems can be described as a system that is capable of supporting ad hoc analysis of data , and decision modeling , decision -oriented , future -oriented planning , and used in times of unusual .
8 . Bonczek (1980 )Decision support system as a computer -based system that consists of components include components of the language system ( language ) , system component knowledge (knowledge ) and component processing system problems .
9 . Turban & Aronson (1998 )Decision support systems as systems used to support and help the management make decisions in conditions of semi -structured and unstructured . Basically the concept of DSS was limited to activities help managers assess and replace the position and role of the manager .
10 . Raymond McLeod , Jr. . ( 1998)Decision support system is a system that provides the ability for problem solving and communication for issues that are semi - structured .
Kind of - kind of Decision Support Methods sisem1 . MetodeSistempakar2 . MetodeRegresi linear3 . Method B / C Ratio4 . AHP method5 . IRR method6 . NPV method7 . MetodeFMADM8 . SAW methodDefinition of AHP MethodAHP was developed by Thomas L. Saaty , a mathematician . This method is a framework for making decisions effectively over complex issues by simplifying and speeding up the decision making process to solve these problems into parts , arranging parts or variables in a hierarchical arrangement , members numerical value on the subjective judgment of the importance of each variable and synthesize the various considerations set a variable to which one has the highest priority and act to influence the outcome of the situation . The AHP method helps solve complex problems by structuring a hierarchy of criteria , interested parties , with interesting results and considerations for developing a weight or priority . This method also combines the strength of feeling and logic concerned on various issues , and synthesize diverse considerations into results that matched estimates as we intuitively presented on considerations that have been made . ( Saaty , 1993) .The process hierarchy is a model that provides an opportunity for individuals or groups to develop ideas and define problems in a way to make their own assumptions and obtain the desired solution darinya.Ada two main reasons for expressing action would be better than other measures . The first reason is the effects of such actions sometimes can not be compared because sutu size or different fields and second , stated that the effect of such actions sometimes clashed with each other , meaning that the effect of corrective actions which one can be achieved by other deterioration . The second reason would be difficult to make an equivalence between the effects necessitating a flexible scale called priorities .
Basic Principles and Axiom AHP
AHP is based on three basic principles , namely :1 . decompositionWith this principle structure of a complex problem is divided into sections hierarchically . The purpose of the public to be defined specifically . In its simplest form the structure will be compared to the goal , criteria and alternatives level . Each set of alternatives may be further divided into more detailed levels , includes many more other criteria . The top level of the hierarchy is an objective consisting of one element . The next level may contain multiple elements , where the elements to be compared , have similar interests and do not have too striking differences . If the difference is too large to insert a new level .
2 . Comparative assessment / consideration (comparative Judgments ) .With this principle will be constructed pairwise comparisons of all the elements are there for the purpose of scale relative importance of the elements . Assessment generate the numeric rating scale . Pairwise comparisons in the form of a matrix when combined will produce a priority .
3 . synthesis of PrioritiesPriority synthesis is done by multiplying the local priorities with the priorities of the relevant criteria in the level above it and add it to each element in the level that influenced the criteria . The result is combined with the known global priorities which are then used for weighing the local priorities of elements at the lowest level in accordance with the criteria .
AHP is based on three main axioms :
1 . axiom ReciprocalThis axiom states if the PC ( EA , EB ) is a pairwise comparison between the elements of A and B elements , taking into account the elements of C as a parent , shows how many times more properties owned by the elements of A to B , then the PC ( EB , EA ) = 1 / PC ( EA , EB ) . For example, if A is 5 times greater than B , then B = 1/5 A.
2 . Homogeneity axiomThis axiom states that the elements being compared do not differ too much . If the difference is too large , the results obtained containing a high error value . When the hierarchy is built , we must try to arrange the elements so that the elements did not produce results with low accuracy and high inconsistency .
3 . axiom AddictionThis axiom states that the priority elements in the hierarchy does not depend on the level below the element . This axiom allows us to apply the principle of hierarchical composition .
Advantages and Disadvantages of the Method of AHP
excess1 . As a hierarchical structure of criteria selected konskwensi until the sub - sub- criteria deepest .
2 . Into account up to the limit of tolerance inkonsentrasi validity as criteria and alternatives selected by the decision makers .
3 . Memperhitungkandayatahanatauketahanan analisissensitivitaspengambilankeputusan output .
Method of " pairwise comparison " AHP has the ability to solve multi- object problem under study and multi-criteria based on preference ratio of each element in the hierarchy . So this model is a comprehensive model . Decision -makers determine the choice of a pair of simple comparison , membengun all priorities for alternative sequences . " Pairwaise comparison" AHP mwenggunakan qualitative data that is based on perception , experience , intuition sehigga felt and observed , but no numerical data completeness to support the quantitative modeling .weakness
1 . AHP model dependence on the main input .The main input is a perception that an expert in this case involves the subjectivity of the experts but it is also the model becomes meaningless if the experts give a false assessment .
2 . AHP is a mathematical method only without any statistical testso there is no limit of the confidence of the true model of the form
Stages In AHP MethodAHP stepsStep - step and process Analysis Hierarchy Process ( AHP ) is as follows1 . Memdefinisikan problems and setting goals . If AHP is used to select an alternative or arrange alternative prioriras , at this stage of development alternatives .2 . Formulate the problem into a hierarchy so that complex problems can be seen from the detailed and measurable .3 . Priority setting for each element of the hierarchy problem . This process produces a weight or contribute to the achievement of objectives so that elements with the highest weight element has priority handling . Priority is generated from a matrix of pairwise perbandinagan between all elements at the same level of hierarchy .4 . Consistency of the comparison testing between didapatan elements at each level of the hierarchy.
While the steps " pairwise comparison " AHP is1 . Retrieval of data from the object under study .2 . Calculating the weight of the pairwise comparison of data from respondents with a" Pairwise comparison " based on AHP questionnaire results .3 . Calculating the average ratio of the consistency of each respondent .4 . Treatment with the method of " pairwise comparison " AHP .5 . After processing , it can be inferred the existence of consistency with , if the data are not consistent then repeated again with the retrieval of data as before , but if otherwise then classified the data that can then be searched weighted value of beta ( b ) .Case Example
Adi birthday 17th Both parents promise to buy motorcycle suit the desired Adi . Adi has choices of motorcycle Ninja , Tiger and Vixsion . Adi has a criteria in the selection of motorcycles will he buy that is: the bike has a good design , quality and economical in fuel .completion1 . The first stageDetermining botot of each - masig criteria .Design 2 times more important than the EfficientDesign is more important than the quality of 3 timesEfficient 1.5 times more important than the quality of the
Comparation Pair Matrix
Irit Design Quality Criteria Priority VectorDesign 1 2 3 0.5455Efficient 0.5 1 1.5 0.2727Quality 0.333 0.667 1 0.1818Total 1.833 3.667 5.5 1.0000Pricipal Eigen Value ( max ) 3.00Consistency Index ( CI ) 0Consistency Ratio ( CR ) 0.0 %
From the picture above , prioity Vector ( far right column ) shows the weight of each criterion , so in this case the design is the highest weight / Adi most important , followed by Irit and the latter is Quality .How to make a table like the one above1 . For comparison between each - each criterion is derived from the weight that has been given ADI first .2 . As for the line number , the result of each vertical penjumalahan - each criterion .3 . For Priority Vector obtained from the sum of all the cell just to the left ( on the same line ) after the first divided by the amount that is underneath , then the sum is divided by the number 3 .4 . To find Principal Eigen Value ( max )The formula is summing the multiplication of the cells in the row number and a column of cells on the Priority Vector5 . Calculating the Consistency Index ( CI ) with the formulaCI = ( max - n ) / ( n - 1 )6 . As for calculating the value of CR7 . Using rumuas CR = CI / RI , RI values obtained fromn 1 2 3 4 5 6 7 8 9 10RI 0 0 5.8 0.9 1.12 1.24 1.32 1.41 1.45 1.49
So for n = 3 , RI = 0:58 .If the results of the calculation of CR is less than or equal to 10 % , inconsistencies can still be accepted , otherwise if greater than 10 % , can not be accepted .2 . Second stageIncidentally ADI friend has a friend who has a motor that is in accordance with the choice of ADI . After his friend Adi adi trying motors provide an assessment ( referred to as pair - wire Comparation )Design 2 times more important than the EfficientDesign is more important than the quality of 3 timesEfficient 1.5 times more important than the quality of the
Ninja 4 times better than the tiger designNinja 3 times better than the design vixsiontiger half times the design is better than the Vixsion
Ninja 1/3 times more efficient than the tigerNinja 1/4 times more efficient than the vixsiontiger half times more efficient than the Vixsion
Based on the assessment , it can be made table ( called Pair - wire matrix Comparation )Design Ninja Tiger Vixsion Priority VectorNinja 1 4 3 0.6233Tiger 0.25 1 0.5 0.1373Vixsion 0.333 0.2394 2 1Total 1,583 7 4.5 1.0000Pricipal Eigen Value ( max ) 3,025Consistency Index ( CI ) 0.01Consistency Ratio ( CR ) 2.2 %
Irit Ninja Tiger Vixsion Priority VectorNinja 1 0.333 0.25 0.1226Tiger 3 1 0.5 0.3202Vixsion 4 2 1 0.5572Number 8 3.333 1.75 1.0000Pricipal Eigen Value ( max ) 3,023Consistency Index ( CI ) 0.01Consistency Ratio ( CR ) 2.0 %
Irit Ninja Tiger Vixsion Priority VectorNinja 1.00 0.010 0.10 0.0090Tiger 100.00 1.00 10.0 0.9009Vixsion 10.00 0.100 1.0 0.0901Total 111.00 1.11 11.10 1.0000Pricipal Eigen Value ( max ) 3Consistency Index ( CI ) 0Consistency Ratio ( CR ) 0.0 %
3 . The third stageAfter obtaining the weights for the three criteria and scores for each of the three criteria for the choice of motor , then the final step is to calculate the total score for all three of these motors . For the ADI will summarize all the results of the assessment in the form of overalls table called composite weight , as follows .
Overall weight weight composite Ninja Tiger VixsionDesign 0.5455 0.6233 0.1373 0.2394Irit 0.2727 0.1226 0.3202 0.5572Quality 0.1818 0.0090 0.9009 0.0901Composite Weight 0.3751 0.3260 0.2989
How to create Composite Overall weight is• Column Weight taken from the Priority column vector in the matrix criteria .• The three other columns ( Ninja , Tiger and Vixsion ) are taken from the third column matrix Priority Vector Design , Efficient and Quality .• Line Composite Weight obtained from the result of multiplying the number of cells with a weight on top .Based on the table above , it can take the conclusion that the highest scores are the Ninja is 0.3751 , while the tiger followed with a score of 0.3260 and the latter is Vixsion with a score of 0.2989 . Adi finally going to buy a motor Ninja
Decision Support Systems ( DSS ) August 1, 2007Posted by haniif in My Thesis .Tags : Decision Support System , DSS , Research , Decision Support Systems , DSS , theist , Review of LiteraturetrackbackThe concept of Decision Support Systems ( DSS ) / Decision Support Systems ( DSS ) was first proposed in the early 1970s by Michael S. Scott Morton with the term Management Decision Systems . The system is a computer -based system intended to help decision makers to utilize data and models to solve specific problems of unstructured [ 10 ] .SPK The term refers to a system that utilizes computer support in the decision-making process . To provide a deeper understanding , will describe some of the definitions of the DSS which was developed by several experts, including by Man and Watson which provides the following definition , DSS is an interactive system , which helps decision-makers through the use of data and models for decision solve a problem that is semi- structured and unstructured . [ 10 ]Characteristics and Value ToCharacteristics of a decision support system is [ 10 ] :1 . Decision Support System designed to assist decision makers in solving problems that are semi- structured or unstructured by adding human wisdom and computerized information .2 . In the process of processing , decision support system combines the use of analytical models with conventional techniques and data entry functions of search / interrogation information .3 . Decision Support System , is designed so that it can be used / operated easily .4 . Decision Support System is designed with emphasis on flexibility and high adaptability .With a variety of special characters above , DSS can provide a variety of benefits and advantages . The benefits can be taken from the DSS are [ 10 ] :1 . DSS expands the capabilities of decision makers in the process of data / information to the wearer .2 . DSS help decision makers to solve the problems especially the problems are very complex and unstructured .3 . DSS can produce solutions more quickly and produces reliable results .4 . Although an SPK , may not be able to solve the problems faced by decision makers , but it can be a stimulant for decision makers in understanding the problem , because it is able to present a variety of alternative solutions.In addition to the various advantages and benefits as stated above , DSS also has some limitations , such as [ 10 ] :1 . There are several management capabilities and human talent that can not be modeled , so the existing models in the system do not all reflect the real issue .2 . The ability of a DSS limited to the treasury of their knowledge ( knowledge base as well as the basic model ) .3 . The processes do SPK usually also depends on the software used .4 . DSS does not have the ability like those of human intuition . The system is designed only to assist decision makers in carrying out their duties .So it can be said that the DSS can provide benefits for decision makers in improving the effectiveness and efficiency , especially in the decision-making process .Components of Decision Support SystemsDecision support system consists of three main components , namely [ 10 ] :1 . Subsystem data management ( databases ) .2 . Management subsystem models ( modelbase ) .3 . Dialogue management subsystem ( userinterface ) .The relationship between these three components can be seen in the figure below .
Figure : The relationship between the three components of decision support systemsSub data management system ( database )Sub data management system ( database ) is a useful component of DSS as a data provider for the system . The data is stored and organized in a database that is organized by a system called the database management system ( Database Management System ) .Management sub- system model ( base model )The uniqueness of the DSS is the ability to integrate data with decision models . The model is an imitation of the real world . Obstacles often encountered in designing a model is that the model is designed not able to reflect the real nature of all variables , so the decision is not in accordance with the requirements therefore , in storing various models must be considered and must be maintained flexibility . Another thing to note is stored on each model should be added details a comprehensive description and explanation of the model created .Management subsystem dialog ( user interface )Another uniqueness of the DSS is the facility that is capable of integrating systems installed by the user interactively , known as dialogue subsystem . Through dialogue subsystem , the system is implemented so that users can communicate with the system are made .Facilities owned by the subsystem dialog is divided into three components [ 10 ] :1 . Language action ( action language) , which is a software that can be used by the user to communicate with the system , which is done through a variety of media options such as keyboards , joysticks and other keyfunction .2 . Language display ( display and presentation language) , which is a device that serves as a means to show something . Equipment used for realizing this view include printers , graphics monitors , plotters , and others .3 . Knowledge base of ( knowladge base ) , which is an indispensable part unknown to the user so that the system is designed to function interactively .
sources :
10 Definition of Decision Support Systems ( DSS )
The concept of Decision Support Systems ( DSS ) / Decision Support Systems ( DSS ) was first proposed in the early 1970s by Michael S. Scott Morton with the term Management Decision Systems . The system is a computer -based system intended to help decision makers to utilize data and models to solve certain problems that are not terstruktur.Istilah DSS refers to a system that utilizes computer support in the decision-making process . To provide a deeper understanding , will describe 10 definitions of the Decision Support System / Decision Support System developed by some experts .
10 opinions on the definition of decision support systems :1 . Little ( 1970 )Decision support system is a set / set of model-based procedures for processing data and judgments to assist management in decision -making .
2 . Alter (1990 ) makes the definition of a decision support system memabandingkannya with a system of electronic data processing ( EDP ) / traditional Electronic Data Processing in 5 ways:
SPKUsage : ActiveUser ManagementObjective : EffectivenessTime horizon : Present and futurePros : Flexibility
PDEUsage : PassiveUser : Operator / EmployeeObjective : Mechanical EfficiencyTime horizon : The PastPros : Consistency
3 . Keen (1980 )Decision support systems are computer -based systems that are built through a process of adaptive learning , patterns of use and the evolution of the system .
4 . Bonczek ( 1980 )Decision support system as a computer -based system that consists of components include components of the language system ( language ) , system component knowledge (knowledge ) and component processing system problems ( processing ) which interact with each other .
5 . Hick (1993 )Decision support systems as an integrated set of computer tools that allow a decision maker to interact directly with a computer to create information that is useful in making decisions on semi-structured and unstructured decisions are not anticipated .
6 . Man and WatsonDecision support system is an interactive system , which helps decision-makers through the use of data and decision models to solve problems that are semi- structured or unstructured .
7 . Moore and ChangDecision support systems can be described as a system that is capable of supporting ad hoc analysis of data , and decision modeling , decision -oriented , future -oriented planning , and used in times of unusual .
8 . Bonczek (1980 )Decision support system as a computer -based system that consists of components include components of the language system ( language ) , system component knowledge (knowledge ) and component processing system problems .
9 . Turban & Aronson (1998 )Decision support systems as systems used to support and help the management make decisions in conditions of semi -structured and unstructured . Basically the concept of DSS was limited to activities help managers assess and replace the position and role of the manager .
10 . Raymond McLeod , Jr. . ( 1998)Decision support system is a system that provides the ability for problem solving and communication for issues that are semi - structured .
Kind of - kind of Decision Support Methods sisem1 . MetodeSistempakar2 . MetodeRegresi linear3 . Method B / C Ratio4 . AHP method5 . IRR method6 . NPV method7 . MetodeFMADM8 . SAW methodDefinition of AHP MethodAHP was developed by Thomas L. Saaty , a mathematician . This method is a framework for making decisions effectively over complex issues by simplifying and speeding up the decision making process to solve these problems into parts , arranging parts or variables in a hierarchical arrangement , members numerical value on the subjective judgment of the importance of each variable and synthesize the various considerations set a variable to which one has the highest priority and act to influence the outcome of the situation . The AHP method helps solve complex problems by structuring a hierarchy of criteria , interested parties , with interesting results and considerations for developing a weight or priority . This method also combines the strength of feeling and logic concerned on various issues , and synthesize diverse considerations into results that matched estimates as we intuitively presented on considerations that have been made . ( Saaty , 1993) .The process hierarchy is a model that provides an opportunity for individuals or groups to develop ideas and define problems in a way to make their own assumptions and obtain the desired solution darinya.Ada two main reasons for expressing action would be better than other measures . The first reason is the effects of such actions sometimes can not be compared because sutu size or different fields and second , stated that the effect of such actions sometimes clashed with each other , meaning that the effect of corrective actions which one can be achieved by other deterioration . The second reason would be difficult to make an equivalence between the effects necessitating a flexible scale called priorities .
Basic Principles and Axiom AHP
AHP is based on three basic principles , namely :1 . decompositionWith this principle structure of a complex problem is divided into sections hierarchically . The purpose of the public to be defined specifically . In its simplest form the structure will be compared to the goal , criteria and alternatives level . Each set of alternatives may be further divided into more detailed levels , includes many more other criteria . The top level of the hierarchy is an objective consisting of one element . The next level may contain multiple elements , where the elements to be compared , have similar interests and do not have too striking differences . If the difference is too large to insert a new level .
2 . Comparative assessment / consideration (comparative Judgments ) .With this principle will be constructed pairwise comparisons of all the elements are there for the purpose of scale relative importance of the elements . Assessment generate the numeric rating scale . Pairwise comparisons in the form of a matrix when combined will produce a priority .
3 . synthesis of PrioritiesPriority synthesis is done by multiplying the local priorities with the priorities of the relevant criteria in the level above it and add it to each element in the level that influenced the criteria . The result is combined with the known global priorities which are then used for weighing the local priorities of elements at the lowest level in accordance with the criteria .
AHP is based on three main axioms :
1 . axiom ReciprocalThis axiom states if the PC ( EA , EB ) is a pairwise comparison between the elements of A and B elements , taking into account the elements of C as a parent , shows how many times more properties owned by the elements of A to B , then the PC ( EB , EA ) = 1 / PC ( EA , EB ) . For example, if A is 5 times greater than B , then B = 1/5 A.
2 . Homogeneity axiomThis axiom states that the elements being compared do not differ too much . If the difference is too large , the results obtained containing a high error value . When the hierarchy is built , we must try to arrange the elements so that the elements did not produce results with low accuracy and high inconsistency .
3 . axiom AddictionThis axiom states that the priority elements in the hierarchy does not depend on the level below the element . This axiom allows us to apply the principle of hierarchical composition .
Advantages and Disadvantages of the Method of AHP
excess1 . As a hierarchical structure of criteria selected konskwensi until the sub - sub- criteria deepest .
2 . Into account up to the limit of tolerance inkonsentrasi validity as criteria and alternatives selected by the decision makers .
3 . Memperhitungkandayatahanatauketahanan analisissensitivitaspengambilankeputusan output .
Method of " pairwise comparison " AHP has the ability to solve multi- object problem under study and multi-criteria based on preference ratio of each element in the hierarchy . So this model is a comprehensive model . Decision -makers determine the choice of a pair of simple comparison , membengun all priorities for alternative sequences . " Pairwaise comparison" AHP mwenggunakan qualitative data that is based on perception , experience , intuition sehigga felt and observed , but no numerical data completeness to support the quantitative modeling .weakness
1 . AHP model dependence on the main input .The main input is a perception that an expert in this case involves the subjectivity of the experts but it is also the model becomes meaningless if the experts give a false assessment .
2 . AHP is a mathematical method only without any statistical testso there is no limit of the confidence of the true model of the form
Stages In AHP MethodAHP stepsStep - step and process Analysis Hierarchy Process ( AHP ) is as follows1 . Memdefinisikan problems and setting goals . If AHP is used to select an alternative or arrange alternative prioriras , at this stage of development alternatives .2 . Formulate the problem into a hierarchy so that complex problems can be seen from the detailed and measurable .3 . Priority setting for each element of the hierarchy problem . This process produces a weight or contribute to the achievement of objectives so that elements with the highest weight element has priority handling . Priority is generated from a matrix of pairwise perbandinagan between all elements at the same level of hierarchy .4 . Consistency of the comparison testing between didapatan elements at each level of the hierarchy.
While the steps " pairwise comparison " AHP is1 . Retrieval of data from the object under study .2 . Calculating the weight of the pairwise comparison of data from respondents with a" Pairwise comparison " based on AHP questionnaire results .3 . Calculating the average ratio of the consistency of each respondent .4 . Treatment with the method of " pairwise comparison " AHP .5 . After processing , it can be inferred the existence of consistency with , if the data are not consistent then repeated again with the retrieval of data as before , but if otherwise then classified the data that can then be searched weighted value of beta ( b ) .Case Example
Adi birthday 17th Both parents promise to buy motorcycle suit the desired Adi . Adi has choices of motorcycle Ninja , Tiger and Vixsion . Adi has a criteria in the selection of motorcycles will he buy that is: the bike has a good design , quality and economical in fuel .completion1 . The first stageDetermining botot of each - masig criteria .Design 2 times more important than the EfficientDesign is more important than the quality of 3 timesEfficient 1.5 times more important than the quality of the
Comparation Pair Matrix
Irit Design Quality Criteria Priority VectorDesign 1 2 3 0.5455Efficient 0.5 1 1.5 0.2727Quality 0.333 0.667 1 0.1818Total 1.833 3.667 5.5 1.0000Pricipal Eigen Value ( max ) 3.00Consistency Index ( CI ) 0Consistency Ratio ( CR ) 0.0 %
From the picture above , prioity Vector ( far right column ) shows the weight of each criterion , so in this case the design is the highest weight / Adi most important , followed by Irit and the latter is Quality .How to make a table like the one above1 . For comparison between each - each criterion is derived from the weight that has been given ADI first .2 . As for the line number , the result of each vertical penjumalahan - each criterion .3 . For Priority Vector obtained from the sum of all the cell just to the left ( on the same line ) after the first divided by the amount that is underneath , then the sum is divided by the number 3 .4 . To find Principal Eigen Value ( max )The formula is summing the multiplication of the cells in the row number and a column of cells on the Priority Vector5 . Calculating the Consistency Index ( CI ) with the formulaCI = ( max - n ) / ( n - 1 )6 . As for calculating the value of CR7 . Using rumuas CR = CI / RI , RI values obtained fromn 1 2 3 4 5 6 7 8 9 10RI 0 0 5.8 0.9 1.12 1.24 1.32 1.41 1.45 1.49
So for n = 3 , RI = 0:58 .If the results of the calculation of CR is less than or equal to 10 % , inconsistencies can still be accepted , otherwise if greater than 10 % , can not be accepted .2 . Second stageIncidentally ADI friend has a friend who has a motor that is in accordance with the choice of ADI . After his friend Adi adi trying motors provide an assessment ( referred to as pair - wire Comparation )Design 2 times more important than the EfficientDesign is more important than the quality of 3 timesEfficient 1.5 times more important than the quality of the
Ninja 4 times better than the tiger designNinja 3 times better than the design vixsiontiger half times the design is better than the Vixsion
Ninja 1/3 times more efficient than the tigerNinja 1/4 times more efficient than the vixsiontiger half times more efficient than the Vixsion
Based on the assessment , it can be made table ( called Pair - wire matrix Comparation )Design Ninja Tiger Vixsion Priority VectorNinja 1 4 3 0.6233Tiger 0.25 1 0.5 0.1373Vixsion 0.333 0.2394 2 1Total 1,583 7 4.5 1.0000Pricipal Eigen Value ( max ) 3,025Consistency Index ( CI ) 0.01Consistency Ratio ( CR ) 2.2 %
Irit Ninja Tiger Vixsion Priority VectorNinja 1 0.333 0.25 0.1226Tiger 3 1 0.5 0.3202Vixsion 4 2 1 0.5572Number 8 3.333 1.75 1.0000Pricipal Eigen Value ( max ) 3,023Consistency Index ( CI ) 0.01Consistency Ratio ( CR ) 2.0 %
Irit Ninja Tiger Vixsion Priority VectorNinja 1.00 0.010 0.10 0.0090Tiger 100.00 1.00 10.0 0.9009Vixsion 10.00 0.100 1.0 0.0901Total 111.00 1.11 11.10 1.0000Pricipal Eigen Value ( max ) 3Consistency Index ( CI ) 0Consistency Ratio ( CR ) 0.0 %
3 . The third stageAfter obtaining the weights for the three criteria and scores for each of the three criteria for the choice of motor , then the final step is to calculate the total score for all three of these motors . For the ADI will summarize all the results of the assessment in the form of overalls table called composite weight , as follows .
Overall weight weight composite Ninja Tiger VixsionDesign 0.5455 0.6233 0.1373 0.2394Irit 0.2727 0.1226 0.3202 0.5572Quality 0.1818 0.0090 0.9009 0.0901Composite Weight 0.3751 0.3260 0.2989
How to create Composite Overall weight is• Column Weight taken from the Priority column vector in the matrix criteria .• The three other columns ( Ninja , Tiger and Vixsion ) are taken from the third column matrix Priority Vector Design , Efficient and Quality .• Line Composite Weight obtained from the result of multiplying the number of cells with a weight on top .Based on the table above , it can take the conclusion that the highest scores are the Ninja is 0.3751 , while the tiger followed with a score of 0.3260 and the latter is Vixsion with a score of 0.2989 . Adi finally going to buy a motor Ninja
Decision Support Systems ( DSS ) August 1, 2007Posted by haniif in My Thesis .Tags : Decision Support System , DSS , Research , Decision Support Systems , DSS , theist , Review of LiteraturetrackbackThe concept of Decision Support Systems ( DSS ) / Decision Support Systems ( DSS ) was first proposed in the early 1970s by Michael S. Scott Morton with the term Management Decision Systems . The system is a computer -based system intended to help decision makers to utilize data and models to solve specific problems of unstructured [ 10 ] .SPK The term refers to a system that utilizes computer support in the decision-making process . To provide a deeper understanding , will describe some of the definitions of the DSS which was developed by several experts, including by Man and Watson which provides the following definition , DSS is an interactive system , which helps decision-makers through the use of data and models for decision solve a problem that is semi- structured and unstructured . [ 10 ]Characteristics and Value ToCharacteristics of a decision support system is [ 10 ] :1 . Decision Support System designed to assist decision makers in solving problems that are semi- structured or unstructured by adding human wisdom and computerized information .2 . In the process of processing , decision support system combines the use of analytical models with conventional techniques and data entry functions of search / interrogation information .3 . Decision Support System , is designed so that it can be used / operated easily .4 . Decision Support System is designed with emphasis on flexibility and high adaptability .With a variety of special characters above , DSS can provide a variety of benefits and advantages . The benefits can be taken from the DSS are [ 10 ] :1 . DSS expands the capabilities of decision makers in the process of data / information to the wearer .2 . DSS help decision makers to solve the problems especially the problems are very complex and unstructured .3 . DSS can produce solutions more quickly and produces reliable results .4 . Although an SPK , may not be able to solve the problems faced by decision makers , but it can be a stimulant for decision makers in understanding the problem , because it is able to present a variety of alternative solutions.In addition to the various advantages and benefits as stated above , DSS also has some limitations , such as [ 10 ] :1 . There are several management capabilities and human talent that can not be modeled , so the existing models in the system do not all reflect the real issue .2 . The ability of a DSS limited to the treasury of their knowledge ( knowledge base as well as the basic model ) .3 . The processes do SPK usually also depends on the software used .4 . DSS does not have the ability like those of human intuition . The system is designed only to assist decision makers in carrying out their duties .So it can be said that the DSS can provide benefits for decision makers in improving the effectiveness and efficiency , especially in the decision-making process .Components of Decision Support SystemsDecision support system consists of three main components , namely [ 10 ] :1 . Subsystem data management ( databases ) .2 . Management subsystem models ( modelbase ) .3 . Dialogue management subsystem ( userinterface ) .The relationship between these three components can be seen in the figure below .
Figure : The relationship between the three components of decision support systemsSub data management system ( database )Sub data management system ( database ) is a useful component of DSS as a data provider for the system . The data is stored and organized in a database that is organized by a system called the database management system ( Database Management System ) .Management sub- system model ( base model )The uniqueness of the DSS is the ability to integrate data with decision models . The model is an imitation of the real world . Obstacles often encountered in designing a model is that the model is designed not able to reflect the real nature of all variables , so the decision is not in accordance with the requirements therefore , in storing various models must be considered and must be maintained flexibility . Another thing to note is stored on each model should be added details a comprehensive description and explanation of the model created .Management subsystem dialog ( user interface )Another uniqueness of the DSS is the facility that is capable of integrating systems installed by the user interactively , known as dialogue subsystem . Through dialogue subsystem , the system is implemented so that users can communicate with the system are made .Facilities owned by the subsystem dialog is divided into three components [ 10 ] :1 . Language action ( action language) , which is a software that can be used by the user to communicate with the system , which is done through a variety of media options such as keyboards , joysticks and other keyfunction .2 . Language display ( display and presentation language) , which is a device that serves as a means to show something . Equipment used for realizing this view include printers , graphics monitors , plotters , and others .3 . Knowledge base of ( knowladge base ) , which is an indispensable part unknown to the user so that the system is designed to function interactively .
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