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Soedito AdjisoedarmoFakultas Peternakan UnsoedPurwokerto
INTRODUCTION OF SYSTEMINTRODUCTION OF SYSTEM
THE SYSTEMS VIEWTHE SYSTEMS VIEW
The system view is a template for The system view is a template for describing, analysing, and designing all describing, analysing, and designing all aspects of any systemaspects of any system.
We will describe this view in We will describe this view in organisational terms here because this organisational terms here because this is the is the viewpoint of a business manager.viewpoint of a business manager.
Reporting structuresReporting structures, , sequences of sequences of work stepswork steps, , information and material information and material flows between work stepsflows between work steps, , and the and the organisation of dataorganisation of data are modelledare modelled using the systems viewusing the systems view.
What is a System?What is a System?
A system is a set of A system is a set of interrelated components that interrelated components that must work together to must work together to achieve some common achieve some common purpose. purpose.
Even when each component Even when each component is well-designed, efficient, is well-designed, efficient, and simple, the system will and simple, the system will malfunction if the malfunction if the components do not work components do not work togethertogether. .
Further, a change in one Further, a change in one component may affect other component may affect other components..components..
An example of An example of what happens what happens when sys-tem when sys-tem components do components do not work together not work together appears in Figure appears in Figure 1. This house has 1. This house has all the all the components ne-components ne-cessary for a cessary for a func-tioning func-tioning home, but the home, but the rooms, plumbing, rooms, plumbing, electrical wiring, electrical wiring, and other compo-and other compo-nents just do not nents just do not fit together. fit together.
The functional relationships among these The functional relationships among these components are simply not right. For components are simply not right. For example, front steps exist, but not where example, front steps exist, but not where needed.needed.
The process to develop a good The process to develop a good system is called systems analysis and system is called systems analysis and design ( SA & D).design ( SA & D). SA & D process are based on a systems approach to problem solving that is driven by several fundamental principles:
1) You must know what a system is to do before you can specify how a system is to operate.
2) Choosing an appropriate scope for the situation you will analyse greatly influences what you can and cannot do to solve a problem.
SYSTEMS, MANAGEMENT SYSTEMS, MANAGEMENT ANDAND
AGRICULTUREAGRICULTURE
Introduction of System (Analysis)An organizational framework for
systemsAgriculture and the System
ConceptModel and Planning Methods
SYSTEMS, MANAGEMENT SYSTEMS, MANAGEMENT ANDAND
AGRICULTUREAGRICULTURE
Introduction of System (Analysis)An organizational framework for
systemsAgriculture and the System
ConceptModel and Planning Methods
2) Choosing an appropriate scopescope for the situation you will
analyze greatly influences what you can and cannot do to solve a problem.
3) A problem (or system) is actually a set a set of problemsof problems; thus, an appropriate strategy is to recursively break a problem down into smaller and smaller problems, which are
more manageable than the whole problem.
4) The solution of a problem is not usually obvious to all interested parties, so alternative solutionsalternative solutions representing different perspectives should be generated and compared before
a final solution is selected.
5) The problem and your understanding of it continues to continues to
changechange while you are analyzing the problem, so
you should take a staged approach to problem-solving in which you reassess the problem
and your approach to solving it solving it at each stageat each stage; this allows an
incremental commitment to a particular solution, with a go go
or no go decisionor no go decision after each stage.
Function Before Form in Function Before Form in SystemsSystems
System are describe in various, System are describe in various, and necessarily separate ways.and necessarily separate ways.
These different ways concentrate on separate aspects of systemsaspects of systems
(for example, what the system does versus how it operates) or or represent systems in different represent systems in different levels of detail.levels of detail.
Consider a good example of system - a house.
As any architect knows, function precedes form with the design of a new house. Before the house is designed, we must determine how many people will live in it, how each room will be used, the lifestyle of the family, and so on.
These requirements comprise a functional, or functional, or logical, specification for the logical, specification for the house house .
It would be premature to choose the type of materials, color of plumbing fixtures, and other physical characteristics before we determine the purpose of these aspects.
We are often anxious to hurry into building (form) before we determine needs (functions) , but the penalty for violating the violating the functionfunction before form principle is increased costs–
the cost to fix a function specification error grows exponentially as you progress through the systems analysis and design process.
Thus, the requirements of the house (or systems) must be well must be well defined and clearly understooddefined and clearly understood.
Architects use blueprints blueprints and other drawings to depict and communicate the design design specificationsspecifications for these requirements.
A blueprintA blueprint is an abstract an abstract representation of the houserepresentation of the house , which mask many detailed and physical feature of the house.
Scope of SystemsScope of Systems
Often the fatal flaw in conceiving and designing a system centers on choosing an inappropriate system scope, apparently the designer of the house outlined each component separately, keeping the boundaries narrow and manageable; he did not see all the necessary interrelationships among the components.
Turning to a business situation(animal breeding is a (animal breeding is a business)business) , when a sales person sells a cheaper version of a product to underbid a competitor, that sales person has defined defined the limitsthe limits of the system to be this one sale.
However, the cost of handling customer complaints about inadequacy of the product, repeated trips to install repeated trips to install upgradesupgrades, and other possible problems make make this narrow definition of this narrow definition of scope inadequate.scope inadequate.
The system boundary The system boundary indicate the system scope.indicate the system scope.
Defining the boundary is Defining the boundary is crucial to designing any crucial to designing any system or solving any system or solving any problemproblem.
Fore example,Fore example,
we could install more efficient computer equipment that can process recording much faster,
but if the staffs (recorders)(recorders) of the recording center are confused by the equipment or if the human if the human factors of using the factors of using the equipmentequipment
are not also considered as are not also considered as part of the system, any part of the system, any benefit from the new benefit from the new equipment may be lost.equipment may be lost.
Therefore, Therefore, recorders and their recorders and their capabilitiescapabilities should be included should be included within the boundaries of the within the boundaries of the system being considered.system being considered.
Too narrowToo narrow a scope may cause a scope may cause you to miss a really good you to miss a really good solution to a problem. solution to a problem.
To wideTo wide a scope may be too a scope may be too complex to handle. complex to handle.
Choosing an appropriate Choosing an appropriate scope is difficult but crucial scope is difficult but crucial in viewing an organization in viewing an organization as a system.as a system.
AN ORGANIZATIONAL AN ORGANIZATIONAL FRAMEWORKFRAMEWORK FOR SYSTEMSFOR SYSTEMS
Several useful frameworks exist to view how a system fit into the whole organization, and one such framework is illustrated in Figure 3.1
People
OrganizationStructure Technology
Task/Procedure
Figure 31. Fundamental Component of an Figure 31. Fundamental Component of an OrganisationOrganisation
AN ORGANIZATIONAL AN ORGANIZATIONAL FRAMEWORKFRAMEWORK FOR SYSTEMSFOR SYSTEMS
This figure indicates This figure indicates four four general key componentsgeneral key components of of the organization that must the organization that must work in concert of the whole work in concert of the whole organization to be effectiveorganization to be effective,,people, technology, task/ people, technology, task/ procedure, and procedure, and organization structureorganization structure..
The important point is that each time was change characteristics of one or more of these four components, we must consider we must consider compensating changes in the compensating changes in the other. other.
Fore example,Fore example,
when technology - such computer hardware and soft ware- changes, people may have to be trained,
method of works may have to be redesigned, and old reporting relationships may have to be modified.
These change must be considered together, or we or we may find that the may find that the compenseting changes are compenseting changes are infeasibleinfeasible or enacting them enacting them will take too long. will take too long.
The framework raises as interesting question
concerning making changes making changes to organizationsto organizations.
In which of the four In which of the four components to start ?components to start ?
There is no universal answer to this. Issues of organizational
politics can play a role in answering this question.
When technology changes, we must consider compensating
changes in the other components, we can use the we can use the technology change to make technology change to make possible other innovation possible other innovation
in organization.in organization.
Environment Output
Interface
Input Component
Component Storage
Boundary
Figure 3.2 Characteristics of systems1. Boundary2. Environment3. Inputs4. Outputs5. Component6. Interface7. Storage
Storage
component
component
component
Figure 3.2 Characteristics of systems
1. Boundary 4. Outputs2. Environment 5. Component3. Inputs 6. Interface 7. Storage
Figure 3.2 Characteristics of systems
1. Boundary 4. Outputs2. Environment 5. Component3. Inputs 6. Interface 7. Storage
CHARACTERISTICS OF CHARACTERISTICS OF SYSTEMSSYSTEMS
There are seven general system elements.
Boundary Boundary ; the delineation of which elements (such as components and storages) are within the system being studied and which are outside; it is assumed that elements elements within the boundary are more within the boundary are more easily changed and controlled easily changed and controlled than those outsidethan those outside.
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Environment Environment ; everything outside the system; the environment provide assumption, constrain, and inputs to the system.
Inputs Inputs ; the resources (data, data, materials, supplies, energymaterials, supplies, energy) from the environment that are consumed and manipulated within the system.
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Outputs Outputs ; the resources or products (information, reports, documents, information, reports, documents, screen displays, materials) screen displays, materials) ~ provided to the environment by the activities within the system.
Components Components : the activities activities or processesprocesses within the system that transform inputstransform inputs into intermediate forms or that generate system outputs, recursively, components may be considered as the system themselves, in which case they are called subsystems.
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Interface Interface : the place where two components or the system and its environment meet or interact; system need special sub-components at interface to filtered, translate, store, and filtered, translate, store, and correct whatever flow correct whatever flow through the interface.through the interface.
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Storage Storage : holding areas used for the temporary and permanent temporary and permanent storagestorage of information, energy, materials, and so on; storage provides a buffer between system components to allow them to work at different rates or at different times and to allow different to allow different components to share the same components to share the same data.data.
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REVIEWREVIEWQuestionsQuestions ??
Environment Output
Interface
Input Component
Component Storage
Boundary
Figure 3.2 Characteristics of systems1. Boundary2. Environment3. Inputs4. Outputs5. Component6. Interface7. Storage
Storage
component
component
component
Figure 3.2 Characteristics of systems
1. Boundary 4. Outputs2. Environment 5. Component3. Inputs 6. Interface 7. Storage
Figure 3.2 Characteristics of systems
1. Boundary 4. Outputs2. Environment 5. Component3. Inputs 6. Interface 7. Storage
WHAT IS A SYSTEM ?
WHAT IS A SYSTEM ?
FUNCTION BEFORE FORM IN SYSTEMSFUNCTION BEFORE FORM IN SYSTEMSSCOPE OF SYSTEMSCOPE OF SYSTEM
PeoplPeoplee
OrganizationOrganizationStructureStructure TechnologyTechnology
Task/Task/ProcedureProcedure
Fundamental Component of an Organisation
?
WHERE TO GO ?
THAT’S ALLthank youthank you
HERD IMPROVEMENT*
OBJECTIVES OBJECTIVES (REQUIREMENTS FOR IMPROVEMENT )
Regardless of whether goals in specific breeds or seed-stock strains are for all-round merit or for specialised trait combinations, the general requisites for genetic improvement continue to be the same. First we must assess what we have genetically in our present animals.
OBJECTIVES OBJECTIVES (REQUIREMENTS FOR IMPROVEMENT )
This requires accurate records of performance on a large number of animals of known ancestry.
Second, within seed-stock herds we must discover how we can increase the number of offspring form those individuals which have the desirable genes at the expense of the individuals with the less desirable genes.
OBJECTIVES OBJECTIVES (REQUIREMENTS FOR IMPROVEMENT )
This requires accurate records of performance on a large number of animals of known ancestry.
Second, within seed-stock herds we must discover how we can increase the number of offspring form those individuals which have the desirable genes at the expense of the individuals with the less desirable genes.
OBJECTIVES OBJECTIVES (REQUIREMENTS FOR IMPROVEMENT )
Third we must optimise combinations of heriditary material from seed-stock herds for commercial production.
OBJECTIVES OBJECTIVES (REQUIREMENTS FOR IMPROVEMENT )
Third we must optimise combinations of heriditary material from seed-stock herds for commercial production.
the general requisites for genetic improvement continue to be the same
in specific breeds
seed-stock strains are
for specialised trait combinations,
the general requisites for genetic improvement continue to be the
same
for specialised
trait combinations,
assess what we have genetically in our present animals
increase the number of offspringoptimise combinations of heriditary material
future goals
future goals
potential requirement of the consuming public.
consumer needs
per capita incomes
strong demand for animal protein.
annually 50 to 60 kg of beef, 27 to 32 kg of pork, and the equivalent of 270 kg of milk per capita,
additional meat needs from beef and swine
increased numbers of animals.
Efficiency in production per head
increasing the production per animal.
Milk
OBJECTIVES(REQUIREMENTS FOR IMPROVEMENT )
In developing future goals, animal breeder must continue to seek out the potential requirement of the consuming public.
Insensitivity to consumer needs will be tolerated less and less as competition from substitute for animal products becomes keener and keener.
The expanding United State population, with prediction of 250 millions by 2000, suggests an increase in the demand for food products.
OBJECTIVES(REQUIREMENTS FOR IMPROVEMENT )
In developing future goals, animal breeder must continue to seek out the potential requirement of the consuming public.
Insensitivity to consumer needs will be tolerated less and less as competition from substitute for animal products becomes keener and keener.
The expanding United State population, with prediction of 250 millions by 2000, suggests an increase in the demand for food products.
increased numbers of animals.
increasing the production per animal.
Milk
heavy concentrate feeding is continued
future competition of animals with human for cereal grains and other concentrated foods may be anticipated.
future competition of animals with human for cereal grains and other concentrated
foods may be anticipated.
selecting animals under conditions where the
nutritional regimes have included liberal feeding of
concentrates
surplus of cereal
Secondary increase would come from the increasing animal numbers.
Present milk production levels per cow cannot be maintained unless heavy concentrate feeding is continued.
Hence, future competition of animals with human for cereal grains and other concentrated foods may be anticipated.
Secondary increase would come from the increasing animal numbers.
Present milk production levels per cow cannot be maintained unless heavy concentrate feeding is continued.
Hence, future competition of animals with human for cereal grains and other concentrated foods may be anticipated.
future competition of animals with human for cereal grains and other
concentrated foods may be anticipated.
selecting animals under conditions where the
nutritional regimes have included liberal feeding of
concentrates
surplus of cereal
do best on high roughage
best genotype for utilising rations
dairy cattle and beef cattle
livestock industry
market
quality products
recompense the producer for the
extra quality
special effort in breeding and production costs
AGRICULTURE AND THE SYSTEM AGRICULTURE AND THE SYSTEM
CONCEPTCONCEPT
Agricultural Production and Agricultural Production and The System ConceptThe System Concept
Many books are essentially about man's search for efficiencyefficiency inin the the
control of agricultural control of agricultural productionproduction.
Most of the world's food and fibre is produced on farms ( under under
farming systemsfarming systems)
FARMS(farming systems)
FARMS(farming systems)
worl
d's
food
and
fib
re
worl
d's
food
and
fib
re overall supply of food to the human population
overall supply of food to the human population
level of the individual farm or individualregion.
level of the individual farm or individualregion.
FAR
MS
(farm
ing s
yst
em
s)FA
RM
S(f
arm
ing s
yst
em
s)
large ecological framework
large ecological framework
exploited the naturalEnviron-ment.
exploited the naturalEnviron-ment.
specialised farming systemsspecialised farming systems
FAR
MS
(farm
ing s
yst
em
s)FA
RM
S(f
arm
ing s
yst
em
s)bio-economic complex
bio-economic complex
controlled by man to achieve his
economic objectives
controlled by man to achieve his
economic objectives
FAR
MS
(farm
ing
syst
em
s)FA
RM
S(f
arm
ing
syst
em
s)bio-economic complex
bio-economic complex
controlled by man to achieve his economic
objectives
controlled by man to achieve his economic
objectives
increasing world population
increasing world population
FAR
MS
(farm
ing
syst
em
s)FA
RM
S(f
arm
ing
syst
em
s)bio-economic complex
bio-economic complex
controlled by man to achieve his economic
objectives
controlled by man to achieve his economic
objectives
increasing world population
increasing world population
more specialised and consequently more biologically unstable
FARMS(farming systems)
FARMS(farming systems)
FAR
MS
(farm
ing
syst
em
s)FA
RM
S(f
arm
ing
syst
em
s)
increasing world
population
increasing world
population
more specialised and consequently more biologically unstable
more specialised and consequently more biologically unstable
FARMS(farming systems)
FARMS(farming systems)
industrial products.
severe biological problems
severe biological problems
severe biological problems
severe biological problems
Many chemical inputs are not easily not easily destroyeddestroyed and
accumulate in food accumulate in food chainschains affecting species
which were no their original targets.
Many chemical inputs are not easily not easily destroyeddestroyed and
accumulate in food accumulate in food chainschains affecting species
which were no their original targets.
more specialised and consequently more biologically unstable
more specialised and consequently more biologically unstable
industrial products.
in the techno-logically
advanced countries
in the techno-logically
advanced countries
in the developping countries -----------
in the developping countries -----------
Disparities in the availability of food and
fibre
On the individual farm, production
processes
On the individual farm, production
processes
systems standpoint.systems standpoint.
complexbiological nature
and their influence is essentially
dynamic
Economic
Seasonalpattern
demanddemand
supplysupply
Seasonalpattern
demanddemand
supplysupply
liquid milk
management decisions taken to
breed cows
natural pasture growth cycles
Economic
Pri
ces
+ p
rod
uct
ion
Pri
ces
+ p
rod
uct
ion
For all stages-Selecting the systemOf feeding, housing, genotype, health care system operates
When and How ?Sell or keep ?
Sell or Keep ?
When and How to mate ?
When and How to mate ?When to cull ?
How to market output ?
FARMS(farming systems)
FARMS(farming systems)
Productionprocess
ProductionprocessProduction
processProduction
process
Productionprocess
Productionprocess
In the management of farming systems it can be expected that an understanding of
the links between the various components the production process will be at least as important as a knowledge
of the separate components themselves.
MODEL AND PLANNING METHODS
The agriculture scientist has employed a variety of mathematical models to explain the operation and organisation of farming processes and to enable predictions to be made about their behaviour. Many such models have been developed and here it is only necessary to record some important illustrative examples.
FARMS(farming systems)
FARMS(farming systems)
Productionprocess
ProductionprocessProduction
processProduction
process
Productionprocess
Productionprocess
Mathematical modelMathematical modelExplanation
pred
ictio
n
The model of Crowther and Yates (19..) was of very simple nature and yet had a useful impact on agricultural policy in UK during World War II. The model took form:
Y=Y0 +d(1-1O-kx)
It purpose was to predict the yield (Y) of a crop for different levels of fertiliser application (x), assuming Y0 is the yield with no fertiliser and d is the respond limit.
Y=Y0 +d(1-1O-kx)
A second simple model, which has had a wide influence on agricultural practice, was
developed by Kleiber (19..) to estimate the maintenance
energy requirement (E) of an animal in relation to its live
weight (W) and constant (S):
E= SW E= SW 0.750.75
Mathematical modelMathematical model
had important roles in the
development of agricultural
practice
had important roles in the
development of agricultural
practice
their simplicity can be
somewhat misleading
their simplicity can be
somewhat misleading
Y=YY=Y0 0 +d(1-1O+d(1-1O-kx-kx))...... .......... ....
E= SW E= SW 0.750.75
..... ........... ......
Mathematical modelMathematical model
had important roles in the
development of agricultural
practice
had important roles in the
development of agricultural
practice
policy determination
and in production
theory
policy determination
and in production
theory
Mathematical modelMathematical model
had important roles in the
development of agricultural
practice
had important roles in the
development of agricultural
practice
policy determination
and in production
theory
policy determination
and in production
theory
progress in planning farming
systems
progress in planning farming
systems
Mathematical modelMathematical model
biological and economic detailbiological and economic detail
the programming techniquethe programming technique p
recis
e a
pp
roach
to
decis
ion
makin
gp
recis
e a
pp
roach
to
decis
ion
makin
g
defi
ned
pro
ble
md
efi
ned
pro
ble
m
Mathematical model
Mathematical model
biological and economic detailbiological and
economic detail
the programming technique
the programming techniqueM
anag
emen
t p
rob
lem
Man
agem
ent
pro
ble
m
tim
e-d
epen
den
tti
me-
dep
end
ent
un
cert
ain
re
lati
on
ship
su
nce
rtai
n
rela
tio
nsh
ips
op
tim
al s
olu
tio
no
pti
mal
so
luti
on
Mathema-tical modelMathema-tical model
biological and economic detailbiological and economic detail
the programming technique
the programming technique
syste
ms a
naly
sis
syste
ms a
naly
sis
the model can be as complex as realistic
the model can be as complex as realistic
Mathema-tical modelMathema-tical model
biological and economic detailbiological and economic detail
the programming technique
the programming technique
syste
ms a
naly
sis
syste
ms a
naly
sis
the model can be as complex as realistic
the model can be as complex as realistic
purely
biologicalpurely
biological
bio-economic
bio-economic
Math
em
a-
tica
l m
odel
Math
em
a-
tica
l m
odel
the model can be as
complex as realistic
the model can be as
complex as realistic
purely
biologicalpurely
biological
bio-economic
bio-economic
descri
pti
ve,
an
aly
tical or
con
str
ucti
ve
descri
pti
ve,
an
aly
tical or
con
str
ucti
ve
System researchSystem research
In this terms, the model may be either purely biological or bio-economic in character and the objective of systems research may be descriptive, analytical or constructive.
In this terms, the model may be either purely biological or bio-economic in character and the objective of systems research may be descriptive, analytical or constructive.
Systems analysis
Systems synthesis
structure and functioning of a system
the design and control of the new system
SystemApproach/Research
Systems analysisSystems analysis
Systems synthesisSystems
synthesis
depending on observation
of the system
depending on observation
of the system
involving the use of
established relationships to construct a
system and examine its behaviour
involving the use of
established relationships to construct a
system and examine its behaviour
SystemApproach/Research
SystemApproach/Research
Systems analysisSystems analysis
Systems synthesisSystems
synthesis
Both, however, are dependent upon the development of an adequate model.
Both, however, are dependent upon the development of an adequate model.
SystemApproach/Research
SystemApproach/Research
Systems analysis
Systems synthesis
upon the Development of
an adequate model.
SystemApproach/Research
dictated by dictated by the the purpose of purpose of the investi the investi gation and gation and the kind of the kind of problems problems to be to be solvedsolved
The justification for model
building must be that
experimentation with the
model is more feasible and
efficient than
experimentation with and
observation of the real
situation.
The justification for model
building must be that
experimentation with the
model is more feasible and
efficient than
experimentation with and
observation of the real
situation.
ANIMALBREEDING
Hig
h q
uality
worl
d's
food
other forms of natural variation
observed over some considerable length of time
in different localities if
being subject to climatic
In many cases the real
system may prove too
complex to permit
suitable analysis from
direct observation.
In many cases the real
system may prove too
complex to permit
suitable analysis from
direct observation.
REALSYSTEM
OBSERVATION
OBSERVATION
SUITABLEANALYSIS
TOO
COMPLEX
TOO
COMPLEX
REALSYSTEM
OBSERVATION
So many factors
may act in union
and interact
So many factors
may act in union
and interact
cause
som
e
disturb
ance
of the n
atura
l
order
Anim
al p
rote
in w
orl
d's
food
monitored and interfered by man
FARMS(farming systems)
BREEDINGANIMAL
no monitoring is taking place.
FARMS(farming systems)ANIMAL
BREEDING Management
Experimentation with a computer model
model building
Anim
al p
rote
in w
orl
d's
food
Experimentation with a computer model
model building
the availability of computer time and the skill of the model building
take place in a homogeneous or, perfectly controlled environment.
Vp=Vg+Ve
OBSERVATION
Experimentation
modelling cannot exist without some information based on experimentation and observation of real life situations
REALSYSTEMREAL
SYSTEM
modelling cannot exist without some information based on
experimentation and observation of real life
situations
improved efficiency imparted to subsequent
real-life experimentation.
Areas of interest can be pin-point, and relevant
treatment ranges
established.
modelling cannot exist without some information based on experimentation and observation of real life situations
cannot be restricted to any single presently-defined discipline
improved efficiency imparted to subsequent real-life experimentation.
modelling cannot exist without some information based on experimentation and observation of real life situations
a corporate effort by a team of specialists in separate discipline
cannot be restricted to any single presently-defined discipline
modelling cannot exist without some information based on experimentation and observation of real life situations
a corporate effort by a team of specialists in separate disciplinean engineer and a
computer programmer all working under the direction of a group leader.
PROBLEMS IN SIMULATING FARM SYSTEMS
It will clear by now that the essence of the systems concept is to describe a situation with many interacting elements where, to be understood, any individual element in the system must be viewed in the context of the whole.
PROBLEMS IN SIMULATING FARM SYSTEMS
It will clear by now that the essence of the systems concept is to describe a situation with many interacting elements where, to be understood, any individual element in the system must be viewed in the context of the whole.
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(9 th)
(9 th)
(9 th)
(10 th)
80 cempe
1993
I
II
III
IV
V
VI
Disisihkan/afkir
Disisihkan/afkir
Disisihkan/afkir
Bibit unggul belum teruji
DirJenBinProd
Luar Negeri
PabrikSemenBeku
BPT &HMTBaturraden
Pemasok
Universitas Peternak
Dinas Peternakan
permintaan
Materi genetikkebijakan
Pejantan muda
Data produksi
Bibit betina
laporan
order
konsentrat
Data prod.
Hasil penelitian
Semen bekuBibit btn
PermintaanbibIt
Contex diagram
SistemGlobal
Flowchart pencatatan dan pelaporan produksi susu
Sumbang saran pemikiran ekspor ternak hidup(Contex diagram)
Pengusaha
Pedagangantar pulau
eksportirternak hidup
pasarMalaysia
pasarBrunei
pasarTimur Tengah
dollar
Dirjenak
Puslitbangnak
PerguruanTinggi
dBase (Simnak dll)
petani
tran
saks
i
Ranch(pembesaran,
bakalan)
Rranch(pembibitan)
Disnak
kebijakan pembibitan
kebijakan perdagangan ternak
kebijakan
perm
inta
an b
antu
an
sapi
dolla
r
sapi
dolla
rPasardalamnegeri
laporan
data/informasi
data/informasi
data/informasi
data/informasi
data/informasi
penawaran
penawaranpermintaan
permintaan
Sumberbibit
pela
yana
n
perm
inta
an
PIR
/Non
-PIR
perbantuanpermintaan
budi
daya
budidaya
hasil
hasi
l
sapi
dollar
kerjasamakerjasama
perm
inta
an
pena
war
an
sapi
sapi
sapi
dolla
r
dolla
r
HAL-HAL YANG PERLU MENDAPAT PERHATIANPopulasi ternak saat ini. Kemampuan produksi untuk jangka pendek dan panjang dalam mencukupi permintaan dalam negeri. Masalah yang berkaitan dengan pelestarian plasmanutfah ternak asli Indonesia Issue pemotongan hewan besar betina yang bertandukPeningkatan pendapatan peternak dan devisa yang akan diperoleh
1
syste
ms c
on
cep
tdescribe a situation with many interacting elements
important implications for model construction
FARMS(farming systems)
FARMS(farming systems)
Productionprocess
Productionprocess
Productionprocess
modelExplanation
pred
ictio
n
OUTPUT
A subsystem whose functioning greatly influences the output criteria from the model should usually relative finer detail than one whose functioning has little effect on model output.
A subsystem whose functioning greatly influences the output criteria from the model should usually relative finer detail than one whose functioning has little effect on model output.
In this situation, the provision of data for model building is likely to prove a major problem.
Generally the model will represent a marked degree of simplification and the relationships required in its construction will not always correspond either with the true relationships or with those directly available from research.
In this situation, the provision of data for model building is likely to prove a major problem.
Generally the model will represent a marked degree of simplification and the relationships required in its construction will not always correspond either with the true relationships or with those directly available from research.
Some modification of research result will often be required. Even worse, few or no data may be available for some components of the model.
In this situation is occasionally possible to generate the infor mation using the rest of the model structure.
CONTROL BY MANAGEMENT
Broadly, farming systems may be classified into two types related to the degree of control that can be exercised over the production environment.
CONTROL BY MANAGEMENT
Broadly, farming systems may be classified into two types related to the degree of control that can be exercised over the production environment.
First, there are those systems where little direct control is possible.
Generally the would be considered to be the more extensive type of farm organisation, characterised by low capital investment per unit of land.
First, there are those systems where little direct control is possible.
Generally the would be considered to be the more extensive type of farm organisation, characterised by low capital investment per unit of land.
CONTROL BY MANAGEMENT
In such systems, control is mainly through a restricted range of management strategies such as adjusting the stocking rates, selling or buying stock, or perhaps modifying the soil environment by fertiliser application or crop rotation. By these means, the performance of the crop or of livestock can be controlled to some extent.
CONTROL BY MANAGEMENT
In such systems, control is mainly through a restricted range of management strategies such as adjusting the stocking rates, selling or buying stock, or perhaps modifying the soil environment by fertiliser application or crop rotation. By these means, the performance of the crop or of livestock can be controlled to some extent.
The second type of farming system is represented by production methods that attempt to reduce environment uncertainty by providing relatively large capital inputs.
The second type of farming system is represented by production methods that attempt to reduce environment uncertainty by providing relatively large capital inputs.
CONCLUSION
The few studies included in these covers can in no sense indicate the full scope for applying systems analysis to solving problems in agricultural management.
Rather, it is hoped that what presented will be suggestive of the wide and so far un-exploited scope.
CONCLUSIONCONCLUSION
It is fairly safe prediction that during the 1970s a great deal of attention will be turned towards analysis of agricultural systems as systems. It is anticipated that the present collection may help to light the way to an early and profitable attack on a wide front of the pressing problems in modern agricultural management.
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