V. CONCLUSION MENDATIONS
: 1.
The spatial multi-criteria analysis method has been developed with the goal to assess vulnerability of settlement area from mud volcano hazard. According to
literature study of some previous researches, interviews and discussions with some experts, the method considers 4 physical evaluation criteria i.e.
subsidence, consists of three indicators which are methane gas, hydrogen sulfide gas and
carbon dioxide gas. The expert judgment is used to decide the preference of criteria on weight and rating presented as Pairwise Comparison Matrices.
2. The method assesses the vagueness of expert confidence that involved in
multi-criteria decision making by using Fuzzy AHP analysis. To simplify the complexity implementation of using fuzzy, alpha cut is applied to represent
interval performance of expert confidence about their judgment. The lambda function is applied to fit the attitude of expert between these intervals to obtain
crisp performance value of criterion. This research performed sensitivity analysis at three alpha values 0.4, 0.6 and 0.8 to assess the effect of expert
confidence to vulnerability area. While measuring the vagueness, lambda values 0, 0.5 and 1 are used to fit the
inimum, medium and maximum value of interval performance.
S AND RECOM
5.1 Conclusions
There are some important points related to this research
bubble gas, mud flooded and water quality. While bubble gas
attitude of expert at m
3. The method has been applied to generate mud volcano vulnerability for
lement area in Sidoarjo by using performance sett
resulted from applying
und fou
10.9 of the total
49.
app 4.
Com a prepared by BPLS, the map resulted from multi-
vul vul
prepared by BPLS. Therefore, this vulnerability area can be used to provide
inc 5.
The problem for implementing the method was criterion map availability and
risk pplied some international
5.2 Recommendations
Multi-criteria evaluation used in this research offers an alternative to perform mud volcano vulnerability analysis since the hazard in Sidoarjo involves
Fuzzy AHP and implementing spatial analysis. Based on vulnerability analysis er 100 confidence of expert on deciding upon their importance, it was
nd that the high hazardous area Z1 covers about settlement area, while 25 were considered as moderate hazardous area Z2,
6 as low hazardous area Z3 and 14.4 as not impacted area Z4. The future using of this method needs the adjustment of the criteria that is
ropriated with the analysis. pared to impacted are
criteria analysis at 100 confidence level of expert has different classes of nerability. However, the surface area of the merged class Z1 and Z2 from
nerability analysis covered area was almost same with impacted area
the government with information in making decision about the area to be luded in impacted areas in order to be grouped as high priority.
the standard to classify the criterion map. According to the discussion with management expert, this research has a
standards to classify each criterion.
85
some f be used to assess vagueness of expert knowledge since there is vagueness in
criterion. There are several points that should be done in the future, e.g.:
2. many experts from multi
ed to confirm the confidence level of expert
3. always change over time
actors that should be analyzed. Besides, the application of Fuzzy AHP can
expert confidence while making a decision on the priority to be given to each
1. The vulnerability area resulted from applying multi-criteria analysis and
Fuzzy AHP needs to be verified by the experts from BPLS who already know the real condition in the study area.
Further study and discussion that involve discipline are needed to include other criteria such as crack on land surface
and strength of embankment for assessing mud volcano vulnerability analysis in the future due to the dynamic change of impact of hazard in the
study area. There is also a ne and decision maker on deciding their preference as the basis of developing
vulnerability map as a consequence of vagueness in expert judgment. The data of each criterion used in the analysis
caused by dynamic change of impact in the study area. Therefore, the vulnerability map also has a limited usefulness as consequence of this
change. For the purpose of predicting the future data and updating vulnerability map, time series regression model or analysis based on
stochastic model is needed to deal with time sensitivity.
86
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APPENDICES
Appendix 1: Concentration of Bubble Gas
Bubb ive
Vol le
No Number
Date of Act CH4 LEL
H2S PPM CO2
1 ei 2006
7 23
1 29 M
2 Nov 2006
36 28
100 3
007 25
12 50
7 Jan 2 4
007 83
6.0 61
4 April 2 5
2007 65
15 Mei 3
6 66
27 7
68 29 Mei 2007
100 35
8 71
3 Sep 2007 2
9 72
8 Nov 2007 100
18 10 73
11 Nov
2007 100 3
7.4 11
74 26 N0v 2007
100 12
75 11 Jan 2008
5 13
76 n
12 Ja 2008 100
8.2 14
77 21 Jan 20
1 08
2 15
78 23 jan 200
1 8
00 7.0
16 79
28 jan 200 10
1 8
2.4 17
80 7 Feb 2008
6.5 18
81 Feb
1.5 8
2008 10
19 82
8 Feb 2 008
100 20 83
0.5 10
93
94
endix 2: Physical and Chemical Data of Water Criterion n
a i
Nove r 2007
sics Chemistry
App a.
Physical a d Chemical D ta Observation t me:
Phy
mbe
Turbidity olour TDS
Fe Mn Na NH4 Cl
SO4 NO2 NO3 C
pH CaCO3
No Point
ID Location
TCU mgl mgl mgl mgl mgl mgl mgl mgl mgl
NTU Standard Limit
Health Ministerial No. 907 15
100 6,5-
250 3 50 MENKESSKVII2002