11 • As few limitations as possible should be used in the symbol for any subclass.
One, rarely two, letters should normally suffice. The dominant symbol i.e. that which determines the class should be used alone if possible. If two
limitations are equally severe, both may be given. FAO, 1976
2.4 Simple Additive Weighting SAW for Marine Coastal Suitability
SAW stands for simple weight and probably the best known in many weighting and very widely used in multiple attribute decision making. Basic concept of this
method is to search for average weight in of all alternative attributes; the decision maker assigns determines the weights based on their importance of each attribute.
Another opinion when the decision maker can obtain a total score for each alternative by multiplying the scale rating for each attribute influenced by the
weights based on their importance then summing with all the attributes. Simple Additive Weighting method can be stated as follows:
A
i
= ∑
………………… ………..…… 1
Where x
ij
is the score of the i
th
alternative with respect to the j
th
attribute, w
j
is the normalized weight. The GIS-based SAW method involves the following steps
Malczewski, 1999: • Define the set of evaluation criteria map layer and the set of feasible
alternatives attributes • Standardize each criterion weight map layer
• Define the criterion weight; that is, a weight of “relative importance” is
directly assigned to each criterion map • Construct the weighted standardized map layer
• Generate the overall score for each alternatives • Rank the alternatives according to the overall performance score
Marine coastal suitability level can be divided in several classifications such as S1 class most suitable, S2 class suitable, S3 class less suitable, and N class not
suitable. The notation in numbers will be describe into S1 class with values in range of 80 – 100, S2 class with values in range of 60 – 80, S3 class with values
12 in range of 40 – 60, and N class where the values are less than 40, as describe in
table 2-3. Table 2-3. Range marine suitability class for SAW method
Wiradisastra, 2004
LSI Symbol Suitability
Class
100 – 80 S1
Most suitable 79,99 – 60
S2 Suitable
59,99 – 40 S3
Less suitable 40
N Not suitable
2.5 Fuzzy Method for Marine Coastal Suitability
The fuzzy logic in general is essentially a logic that allows values between 0 – 1 that will be assigned conventional evaluation, such as yes or no, right or wrong,
etc. which could be formulated mathematically. Fuzzy logic can be used to model and deal with the appropriate information, such as incorrect measurements or
expert knowledge available in the form of verbal description. The digital computing world is built on the structure of boolean logic 0 and 1
and applied to the value of discrete such as one or zero, yes or no, etc. But this is a big idea structure and need simplification in the real world, where many of the
problems that have a description as gray between black and white Baja, 2002. Fuzzy logic in multi-theory which the value of values as moderate, high,
low on the application in the real world is used as a yes or no, right or wrong is also used in the conventional theory crisp. In daily life, the allegation metric is use
clearly related to the concept or the numeric value. In generally, fuzzy method gives alternative way to handle situations and defined by membership degrees.
Such example for elements in x actually members of A and if A x = 1, x is not owned by A, and if A x = 0. Then the higher the value of membership, the
greater is element x belonging to a set A Malczewski, 1999. The value such as low, moderate, high, or so often used to determine the status of the variables.
Variables are usually referred to as fuzzy variables. Significantly from the fuzzy
13 variables are those that facilitate the gradual transition between the state and,
therefore, have a natural expression and the ability to deal with observation and measurement of fuzziness. Fuzzy logic is a superset of classical logic with the
introduction of degree of membership. These degrees of membership are possible to interpolate input between crisp set. The operator logic is quite similar,
except their interpretation differs. Model functions used to calculate membership function MF of marine coastal
attributes are depicted in Figure 2-2 adapted from Burrough and McDonnell, 1998. Model 1 in figure 2-2 is used to determine the membership grades of
marine coastal qualities with symmetric functions, where only one ideal point or central concept exists. Another type of symmetric function is shown in model 2 of
figure 2-2, where the central concept consists of a range of values from b1 to b2. Further more, there are also situations where only the lower and upper boundary
of a class has practical importance Burrough and McDonnell, 1998. In such circumstances, an asymmetric function needs to be applied models 3 and
4 of figure 2-2. An asymmetric left function is used for the lower boundary of a class, while an asymmetric right is employed for an upper boundary. If MFx
i
represents individual membership value for i
th
marine coastal property x, then in the computation process these model functions Models 1 to 4 take the following
form Burrough and McDonnell, 1998: MFx
i
=
…
………………………………..….… 2
For optimum range Model 2:
MFx
i
= 1,
….…. 3
14 For asymmetric left Model 3:
MFx
i
= 1,
.............................................. 4
For asymmetric right Model 4:
MFx
i
= 1,
…………………………….. 5
Where MFx
i
= membership function of marine coastal; d = transition zone;
b = lower and upper crossover points.
Figure 2-2. Fuzzy set models used for rating land attributes adapted from Burrough and McDonnell, 1998.
A land evaluation system developed in light of the FAO principles 1976 were used in the quantitative assessment of the biophysical potential of ecosystems in
the study area for the marine coastal use types of residence, reforestation-
15 recreation, and arable farming. The conditions of the marine coastal necessary for
successful and sustained implementation of the specified marine coastal type, namely marine coastal use requirements, were determined using related literature
information and available data. The land suitability index LSI of the marine coastal mapping unit for each marine coastal type was calculated using the
multiplicative combination of suitability rating index FAO, 1976, and LSI value is expressed on a discrete scale of suitability classification for a specific in table 2-
4.Kilic, et al., 2003 Table 2-4. Land suitability index use as fuzzy logic method
LSI Symbol Suitability
Class
1,00 – 0,90 S1
Most suitable 0,89 – 0,75
S2 Suitable
0,74 – 0,50 S3
Less suitable 0,49
N Not suitable
The class criterion for marine coastal suitability evaluation using fuzzy method is describe in table 2-4 such as S1 class, S2 class, S3 class, and N class. These
ordinal values are used in marine coastal suitability analysis, with scale of 0 to 1, therefore each class has a particular criteria to contribute to the goal.
2.6 Study Area
