Geotechnical Assessment for Truss Bridge using Fuzzy-based Soft

Computing: Case Study - Kedaung Bridge, Tangerang, Banten

Indonesia

Pringga Satria Panji and Tommy Ilyas

Deparment of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia

Keywords: Assessment, Kedaung bridge, Fuzzy, Hazard, Slope stability, soil investigation

Abstract: Kedaung Bridge is a truss bridge that connect two sub-districts in Tangerang. This bridge pass over Cisadane

River. Although the bridge is newly opened, any hazard may be occurred during operating periods.

Substructure of bridge itself is prone to hazards such as ground displacement, slope instability and seismic-

related hazard. Typical traffic data and soil investigation data will be used to analyze ground displacement

and slope instability where the bridge located. Local geological and seismic data will be used to assess

seismic-related hazard. A risk assessment for substructure shall be conducted. Fuzzy Analytical Hierarchy

Process (FAHP) will be used to analyses various geotechnical aspects. Hazard identification, risk rating, risk

analysis, and risk assessment are steps conducted in FAHP method. The ranking model can be used for quick

sensitivity assessment of the effect of various site condition. Classification and rating of risk can be done with

proposed method. Classification of risk will be based on soil type and geological condition. This assessment

can be a tool or recommendation for local government where the bridge located. Priority list will be created

using this method and enable decision makers to decide on either carrying out further detailed evaluation or

consider any other actions for the bridge.

1 INTRODUCTION

In a road network system, bridges play an important

role as a complementary road infrastructure. Bridges

can be the backbone of infrastructure that links one

region to another (Andric & Lu, 2015). Bridges can

connect road that is separated by rivers, lakes,

ravines, valleys, straits, highways and railways. In its

development, the bridge undergoes the evolution

from wooden and simple stone bridges to bridges

with more complex structural systems and advanced

materials. The advanced materials used in more

complex bridge structure (such as concrete, steel and

cables) that continue to develop will encourage the

construction of bridges with more complex

technology than ever before.

In Indonesia, Directorate General of Highways of

Ministry of Public Works and Housing (Dirjen Bina

Marga Kementerian PU-PERA) is responsible for

bridge management through archipelago. The

Directorate General of Highways uses the Bridge

Management System (BMS) for more systematic

monitoring and planning of the bridge. The BMS

developed and owned by the Directorate General of

Highways serves as a tool for the process of storing

bridge-related data; such as design work,

construction, rehabilitation and monitoring of bridge

condition. For the purposes of the bridge survey,

Indonesia’s Directorate General of Highways has a

Working Unit of Planning and Supervision of

National Roads and located in each province.

According to data collected from the Ministry of

Public Works and Housing Statistics Information

Book (Buku Informasi Statistik Kementerian

PUPERA) year 2015, the total number of bridges in

Indonesia recorded by the Ministry per year 2014 are

14710 bridges with various conditions. The details of

the bridge conditions recorded are 6609 bridges

(45%) in good condition, 3137 bridges (21.3%) with

medium condition, 3253 bridges (22.1%) at lighty-

damaged condition, 1360 bridges (9.2%) in heavily-

damaged condition, 314 bridges (2.1%) with critical

condition and 37 bridges (0.3%) already collapse /

break-up.

From the data above, the condition of the bridge

in Indonesia is composed of various conditions,

130

Satria Panji, P. and Ilyas, T.

Geotechnical Assessment for Truss Bridge using Fuzzy-based Soft Computing: Case Study - Kedaung Bridge, Tangerang, Banten Indonesia.

DOI: 10.5220/0009007401300139

In Proceedings of the 7th Engineering International Conference on Education, Concept and Application on Green Technology (EIC 2018), pages 130-139

ISBN: 978-989-758-411-4

ranging from good conditions until the condition of

collapsed or broke. The bridges listed above are

bridges that have been designed and built by the

Directorate General of Highways. Those bridges have

various shaping materials with varying length and

spans.

Kedaung Bridge is considered as newly built

bridge by local government of Tangerang that

connect two sub-district in Tangerang. It crosses

Cisadane River. The bridge consists of two main lane

and can handle until mid-size truck. Local

government is the entity that hold responsibility for

Kedaung Bridge (under supervision of Indonesia

Directorate General of Highways of Ministry of

Public Works and Housing).

Assessment process of Kedaung Bridgge is to

determine the current state of the bridge can be done

by collecting various related data and then those data

can be analyzed and generate a value that will be able

to assist in the decision-making process. Related

research on the structure of the bridge (such as deck,

frame and bridge pier or pier) has relatively much

research on it. Research on the assessment of the sub-

structure of bridge is not as much as upper-structure

of bridges. Damage to upper and lower structures of

jembaatan will result in disruption of the service life

of the bridge.

2 EVALUATION AND ANALYSIS

To evaluate sub-structure condition of a bridges,

several methods can be conducted. Then, after

evaluation process, assessment process shall be done.

In this paper, assessment process is done by Fuzzy

Analytical Hierarchy Process (Fuzzy AHP). Fuzy

AHP is based on fuzzy set that is developed by Lotfi

Zadeh in 1965. The result of Fuzzy AHP is rating of

each criterion. Rating that is respected to value of

each criteria is the result of assessment process. Based

on the rating, decision making can be done with those

rating.

In this paper, evaluation criteria will be described

based on text book. Slope stability, seismic hazard

analysis, liquefaction study and Fuzzy AHP will be

described in the following subsection.

2.1 Soil Parameter Interpretation

According to Duncan and Wright (2005), the process

of slope stability evaluation needs to be done to

determine the safety factor of a slope. Clear and

comprehensive evaluation results should also be done

for the following reasons:

 Evaluation results should be checked by a few

engineers and experts from relevant

institutions. Multiple examinations are

intended to minimize errors that may occur

during the evaluation process and to gain a

different perspective on a problem.

 Evaluation results must be clear and

understandable by the client

 Responsibility for engineering evaluation

results is usually given to engineers at an

institution or company. The engineer must

understand the results of the evaluation and

understand the basis of the decisions taken in

the analysis and evaluation.

 Evaluation results should be well documented.

Good documentation will make it easier if the

data at any time required in the future.

It is inevitable that each slope location evaluated

has different characteristics from one another. In

Java, soil conditions in each province will be

different. Geological detail plays an important role in

slope stability, and for that, geological information of

a region is very important (Duncan & Wright, 2005).

Then, the next step in the evaluation of the stability of

the slope is the evolution of the soil property.

Evaluation of soil properties will be closely related to

geotechnical investigations. Geotechnical

investigation work will include field and laboratory

work. The properties obtained are quite diverse,

among others are: property of soil shear strength, soil

stiffness, soil physical characteristics and others. In

slope stability, shear strength parameters and soil

density are prioritized.

Soil investigation work has been conducted at

project site of Kedaung Bridge. Soil investigation

works consist of field work (boring) and laboratory

work. Boring work has been conducted in 2 points of

reference. One point is located in one side of

approach section and the other is located in another

side of approach section. Boring work is done until

30 meters depth. Boring log report and soil mechanic

summary report are shown in Figures 1 – 3.

Upper section of soil is dominated by clay until 25

to 26 meter depth and after that section, tuff /

cemented clay mixed with rock is dominated.

Borehole 1 and bor-hole 2 is done at minimum

required depth (30 meter).

At least one undisturbed sample (UDS) in each

borehole are taken for laboratory work. Several

testing have been conducted in laboratory work.

Atterberg limit test, consolidation test, soil density

test, grainsize distribution test, water content test and

triaxial test are testing item treated for each UDS.

Geotechnical Assessment for Truss Bridge using Fuzzy-based Soft Computing: Case Study - Kedaung Bridge, Tangerang, Banten Indonesia

131

(a)

(b)

Figure 1: (a) Upper section of boring log B1 report, (b) Lower section of boring log B1 report.

(a)

(b)

Figure 2: (a) Upper section of boring log B2 report, (b) Lower section of boring log B2 report.

Figure 3: Summary of soil mechanic laboratory test for whole bor-hole.

2.2 Slope Stability Evaluation

Basically, calculation or analysis of slope stability

can be done manually or using geotechnical software.

Manual computations are calculated using several

methods such as Bishop, Taylor, Spencer, Fellenius,

Morganstern and other methods. The whole method

of manual calculation is based on the concept of

equilibrium limit. Then, if using the software, the

geotechnical software widely used and will be used in

this research is Plaxis and Geoslope. The concept of

calculation on Plaxis is based on the finite element

method (FEM), while the concept of calculation on

Geoslope is based on the concept of equilibrium limit.

In this case, soil stability is conducted using

Geoslope software. Input data for Geoslope are

consist of geometry of slope analyzed, soil property

data. loading data at the top of slope (bridge self

weight and traffic load) and environmental data (such

as seismic load).

Three main analysis in Geoslope for this case are

long-term, short-term and seismic condition. Long-

term condition is conducted and deal with daily load

such as traffic load in normal condition. Short-term

EIC 2018 - The 7th Engineering International Conference (EIC), Engineering International Conference on Education, Concept and

Application on Green Technology

132

Figure 4: Geoslope output for long-term condition in bor-

hole 1 location, critical SF = 2.058.

Figure 5: Geoslope output for short-term condition in bor-

hole 1 location, critical SF = 1.808.

Figure 6: Geoslope output for seismic condition in bor-hole

1 location, critical SF = 1.183.

Figure 7: Geoslope output for long-term condition in bor-

hole 2 location, critical SF = 2.092.

Figure 8: Geoslope output for short-term condition in bor-

hole 2 location, critical SF = 1.951.

Figure 9: Geoslope output for seismic condition in bor-hole

1 location, critical SF = 1.200

condition is deal with short and considerably quick

load when traffic jam and big vehicle get jammed and

stroked for one time at both lane along the bridge.

While, seismic condition is deal with seismic load. In

the lifetime of bridge, the bridge itself can be faced

with earthquake, thus, the slope under abutment of

bridge has to be analyzed in seismic condition as well.

Geotechnical Assessment for Truss Bridge using Fuzzy-based Soft Computing: Case Study - Kedaung Bridge, Tangerang, Banten Indonesia

133

Figure 10: GoogleEarth™ imaginary with red circle in 500 km radius.

Figure 11: Maximum magnitude from subduction or megathrust seismic source (Study Report Summary of Indonesia’s

Seismic Map Revision Team, 2010).

Figure 12: Maximum magnitudo and slip rate from fault seismic source (Study Report Summary of Indonesia’s Seismic

Map Revision Team, 2010).

EIC 2018 - The 7th Engineering International Conference (EIC), Engineering International Conference on Education, Concept and

Application on Green Technology

134

The output for slope stability analysis in Geoslope

is safety factor (SF) value. Safety factor value is

reflected the condition of the slope. Based on SNI

8460-2017 (Geotechnical Design Guidelines),

several value of safety factor has been considered for

every uncertainty. Conservative design of slope is one

main focus in SNI 8460-2017. After all required data

has been input in Geoslope, the software will analyse

the data and safety factor value will be clearly visible

for several condition. The geoslope outputs are shown

in Figures 4 – 9.

2.3 Seismic Hazard Identification

Tangerang is located in Java Island and this area is

surrounded by several active and unstable tectonic

plates. The southern plates is part of ring of fire.

Radius taken for seismic hazard identification is 500

km. Seismic source can be located and identified

inside the circle.

Detailed area information are as follow, it was

located at Tangerang, Banten, Indonesia with the

coordinate of E. 678 541.88 (use UTM coordinates

system), N. 9 322 379.92, Zone: 48 M with radius of

500 km. The detailed location are shown in Figures

10 – 12.

From seismic source map as shown in Figures 10

– 12 (megathrust and fault), there are several seismic

source inside red circle where Kedaung Bridge

located. The summary of potential seismic source

inside red circle can be seen in Tables 1 and 2.

Table 1: Potential megathrust seismic zone.

No Subduction Zone Max Rec’d Mag.

1 Megathrust Jawa M = 8.2

2 Megathrust Sumatra M = 8.1

Table 2: Potential fault zone.

Fault Max Rec’d

Mag.

ID Name

14 Ketaun M = 7.3

15 Musi M = 7.2

16 Manna M = 7.3

17 Kumering M = 7.6

18 Semangko M = 7.2

19 Sunda M = 7.6

31 Opak (Jogja) M = 7.8

32 Lembang M = 7.6

33 Pati M = 7.8

34 Lasem M = 7.5

Maximum magnitude from data as shown in

Tables 1 and 2 is Mw = 8.2 SR. This value is historical

seismic ever recorded in the zone. This magnitude

value can trigger liquefaction event in the area with

high sand content.

2.4 Liquefaction Evaluation

Liquefaction of soil can be happened due to loss of

strength in saturated and cohesion less soil. In this

phenomena, pore water pressure will be increasing

significantly, hence, effective stress of affected soil

will be reduced. Rapid dynamic loading is main

suspect of liquefaction phenomena. Earthquake and

other rapid dynamic loading can trigger the increment

of pore water pressure. In Indonesia, several

liquefaction phenomena has been recorded. Most of

them happened after earthquake event.

Method of liquefaction evaluation used is SPT

(soil penetration test) based evaluation that is

developed by United States’ NCEER (National

Center for Earthquake Engineering Research) in

December 1997. T.L.Youd and I.M. Idriss are editors

of NCEER. This method is using CRR (cyclic

resistance ratio). Minimum magnitude of earthquake

to trigger liquefaction based on this method is 7.5 SR

(scale of Richer). In the other hand, this method has

limitation. This method is applicable for (N1)60 < 30;

for (N1)60 ≥ 30, fine sand content is too dense to

liquefied and this type of soil is classified as non-

liquefiable soil (Ikhsan, 2011).

Researcher has analysed liquefaction in spreadsheet

program and has considered limitation above. For

(N1)60 ≥ 30, Researcher input maximum allowable

value of 30. For instance, if (N1)60 = 45, Researcher

only input maximum allowable value. In spreadsheet,

the value becomes 30. This limitation has shown logic

value of FS (factor of safety). Researcher only plot

result of depth vs. FS for each borehole. The

evaluation results are shown in Figures 13 – 16.

Red box in Figure 14 and Figure 16 indicate soil

layer that has FS < 1. This value indicate potential

liquefaction in those layer. To classify the risk, the

next chapter will explain and classify how above FS

value has potential liquefaction. Any risk considered

in above parameter will be explained below using

Fuzzy based method.

3 NATIONAL INDONESIA

CODE/STANDARD (SNI) AS

INFERENCE SYSTEM

Indonesia has released standard code for geotechnical

design called SNI 8460:2017 Persyaratan

Perancangan Geoteknik (Geotechnical Design

Geotechnical Assessment for Truss Bridge using Fuzzy-based Soft Computing: Case Study - Kedaung Bridge, Tangerang, Banten Indonesia

135

Figure 13: Depth vs NSPT for B1 soil profile. Figure 14: Depth vs FS for B1 soil profile.

Figure 15: Depth vs NSPT for B2 soil profile. Figure 16: Depth vs FS for B2 soil profile.

Guidelines). This code will be used as inference

system for risk analysis using Fuzzy-based method.

This code is used as inference system because it

contains expert overview about geotechnical aspects

or parameter being described above.

This code is published by Badan Standarisasi

Nasional (National Standarization Agency) of

Indonesia. A group of geotechnical expert in

Indonesia is then form a team to set this standard /

code. The team consist of Indonesia Government

(represented by experts from Ministry of General

Works and Housing), civil engineering society

(represented by Himpunan Ahli Teknik Tanah

Indonesia / Indonesian Society for Geotechnical

Engineering and Himpunan Pengenmbangan Jalan

Indonesia / Indonesian Raod Develompent

Association), university (represented by Tama

Jagakarsa University, National Technological

Institute) and private sector (represented by PT

Belaputera Intiland and PT MBT).

3.1 Slope Stability Design Guidelines

(Chapter 7 of SNI 8460:2017)

This code, generally, covers common technical

requirement for artificial slope. And for natural slope,

this require the engineer to check the natural slope

stabilization where there will be development in any

part of slope. The goal of slope stability checking is

to design and review the safest and most economical

slope design. Embankment is well covered by this

code. In this code, several different analysis type shall

be done to have board result of embankment

condition. This code require at least short-term

analyses (when embankment works finished), long-

term analyses (for operational needs), sudden-draw

down analyses (when embankment has high water

table) and seismic analyses. The safety factor for soil

slope and the criteria for seismic design as suggested

by SNI 8460-2017 are shown in Tables 3 and 4

respectively.

EIC 2018 - The 7th Engineering International Conference (EIC), Engineering International Conference on Education, Concept and

Application on Green Technology

136

Table 3: Safety Factor value for soil slope (SNI 8460-2017).

Costs and Consequences from failed slope

Level of uncertainty in the condition analysis

Low

High

Repair cost are equal to additional cost to

design a more conservative slope

1.25 1.5

Repair cost are greater to additional cost to

design a more conservative slope

2.5 2.0 or more

The level of uncertainty in the analysis condition is categorized as low, if geological conditions can

be understood, soil conditions are uniform, soil investigations are consistent, complete and logical to

the conditions in the field.

The level of uncertainty in the analysis condition is categorized as high, if geological conditions are

very complex, soil conditions are vary, soil investigations are inconsistent and unreliable.

Tabel 4: Criteria for seismic design based on infrastructure designation (SNI 8460:2017).

Allotment Design age

(Years)

Probability

Exceeded (%)

Return

Period

(Years)

Safety Criterions Reference

Building and

Non Building

50 2 2500 - SNI 1726:2012

Conventional

bridge

75 7 1000 - SNI 2833:201X

Earth retaining

wall, bridge

abutment

75 7 1000 SF > 1.5 (against sliding when

experiencing static load)

WSDOT,

FHWA-NJ-2005-

002

SF > 2 (against overturning

when experiencing static load)

SF > 1.1 (against pseudo static)

Approach

bridge’s

abutment

- - - SF > 1.1 -

Dam 100 1 10000

Safety

Evaluation

Earthquake

(SEE)

Uncontrolled water flow does

not occurs

ICOLD

No. 148-2016

Deformation does not exceed

0.5 of height

Deformation of filters does not

exceed 0.5 from filter thickness

Spillway shall still functional

after earthquake event

100 50 145

Operating

Basis

Earthquake

(OBE)

Minor damage occurs after

earthquake

Dam

Supplementary

Building

50 2 2500 - -

Tunnel 100 10 1000 - -

3.2 Seismic Hazard Design Guidelines

(Chapter 12 of SNI 8460: 2017)

Bridge is no different than any other civil structure or

building. It is prone to earthquake event. In SNI

8460:2017, earth retaining wall and bridge abutment

shall resist earthquake force with several minimum

SF value. The criteria for seismic design is shown in

Table 4.

3.3 Liquefaction Design Guideline

In this research, liquefaction analysis is conducted

using Youd-Idriss Method. This method has final

value, the SF value. Like the other parameter, this

Geotechnical Assessment for Truss Bridge using Fuzzy-based Soft Computing: Case Study - Kedaung Bridge, Tangerang, Banten Indonesia

137

value has safe limitation. SF value for liquefaction

analysis is at least 1 for the first 20 meter depth of

granular soil layer with high water table. Triggering

parameter for liquefaction is earthquake with

minimum magnitude of SR (Scale of Richer) = 7.0.

Kedaung Bridge is located in vulnerable tectonic

plate with megathrust and fault seismic sources that

have qualified to trigger liquefaction.

4 RISK ANALYSIS USING FUZZY

–BASED METHOD

Whole parameter and evaluation works above have

conducted, the next step is to weighting the risk based

on Indonesian Standard Codes (SNI / Standar

Nasional Indonesia).

4.1 Fuzzy Logic

Fuzzy logic is a logic to describe imprecision, to

approximate reasoning and to explain uncertainty of

something. Fuzzy logic can be viewed as an attempt

at formalization / mechanization of two remarkable

human capabilities; First, the capability to converse,

to make reason, and to make rational decision in an

environment of imprecision, uncertainty,

incompleteness of information, conflicting

information, partiality of truth and partiality of

possibility; Second, the capability to perform a wide

variety of physical and mental task without any

measurement and any computations (Zadeh, 2008).

Fuzzy logic can describe normal human

languange. This method use neutral way of how

human thinking and reasoning. Fuzzy logic use input

data and process it with some reasoning (we may call

itu as “blackbox”). This blackbox contains a sort of

reasoning. And after the input has been processed, the

output can be obtained.

5 CONCLUSION

This research is still in progress. Especially in the risk

analyses using Fuzzy-based method in civil

engineering world. We still in progress to clarify that

Fuzzy-based methods can be used in Civil

Engineering. In this research, we take advantages of

Fuzzy logic in civil engineering. Kedaung Bridge

abutments have affordable SF value in long-term,

short-term and seismic condition. SF value vary from

1.183 to 2.092.

Tangerang is located in earthquake vurnerable

zone. Maximum historical earthquake magnitude

value in SR is 8.2. It comes from Java Magathrust.

Liquefaction around B1 and B2 location is considered

safe. Liquefaction (with earthquake triggering value,

SR = 8.2) may happen in depth 4 ~ 10 meter of soil

layer.

ACKNOWLEDGEMENTS

This researh is fully supported by PITTA Programs

from University of Indonesia. PITTA is Paduan

Hibah Publikasi Internasional Terindeks untuk Tugas

Akhir Mahasiswa UI (Grants of Indexed International

Publication for Final Project of University of

Indonesia Students).

REFERENCES

An, M., Chen, Y. & Baker, C. J., 2011. “A Fuzzy Reasoning

anf Fuzzy-Analytical Hierarchy Process Based

Approach to the Process of Railway Risk Information:

A Railway Risk Management System”, Information

Sciences, Vol. 181, pp. 3946-3966.

Attaway, S., 2009. MATLAB: A Practical Introduction to

Programming and Problem Solving, Oxford - UK:

Bitterworth – Heinermann - Elsevier Inc.

Andric, J. M. & Lu, D. G., “Risk Assessment of Bridges

Under Multiple Hazards in Operation Period”, Journal

of Safety Science, Vol. 83, pp. 80-92.

Carbonari, S., Morici, M., Dezi, F., Gara, F. & Leoni, G.,

2017. “Soil-Structure Interaction Effect in Single

Bridge Piers Founded on Inclined Pile Groups”, Soil

Dynamics and Earquake Engineering, Vol. 92, pp. 52-

67.

Cook, W., Barr, P. J. & Halling, M. W., 2015. “Bridge

Failure Rate”, Journal of Performance of Constructed

Facility, Vol. 29, pp. 1-8.

Corotis, R. B., 2015. “An Overview of Uncertainty

Concepts Related to Mechanical and Civil

Engineering”, Journal of Risk and Uncertainty in

Engineering System, Vol. 1, pp. 1-12.

Craig, R. F., 2004. Soil Mechanics, 7

edition, New York –

USA: Spon Press.

Duncan, J. M. & Stephen, G. W., 2005. Soil Strength and

Slope Stability, New Jersey – USA: John Wiley & Sons

Inc.

Fagundes, D. F., Almeida, M. S. S., Thorel, L. & Blanc, M.,

2017. “Load Transfer Mechanism and Deformation of

Reinforced Piled Embankment”, Geotextiles and

Geomembranes, Vol. 45, pp. 1-10.

Kusumadewi, S., Hartati, S., Harjoko, A. & Wardoyo, R.,

2006, Fuzzy Multi-Attribute Decision Making (Fuzzy

MADM), Yogyakarta – Indonesia: Penerbit Graha Ilmu.

EIC 2018 - The 7th Engineering International Conference (EIC), Engineering International Conference on Education, Concept and

Application on Green Technology

138

Kusumadewi, S., 2002. Analisis & Desain Sistem Fuzzy

Menggunakan Toolbox Matlab, Yogyakarta –

Indonesia: Penerbit Graha Ilmu.

Kusumadewi, S. & Purnomo, H., 2010., Aplikasi Logika

Fuzzy Untuk Pendukung Keputusan, 2

edition,

Yogyakarta – Indonesia: Penerbit Graha Ilmu.

Lee, S., 2015. “Determination of Priority Weight Under

Multi-Attribute Decision-Making Situation: AHP

versus Fuzzy AHP”, Journal of Construction

Engineering and Management, Vol. 141, pp. 1-9.

Marwoto, S., 2014. “Pemodelan Sistem Pendukung

Keputusan Untuk Pemeliharaan Jembatan Beton”,

Jurnal Teknik Sipil, Vol. 2, No. 1, pp. 1-5.

Maula, B. H. & Zhang, L., 2011. “Assessment of

Embankment Factor of Safety Using Two

Commercially Available Programs in Slope Stability

Analysis”, Procedia Engineering, Vol. 14, pp. 559-566.

Nezarat, H., Sereshki, F. & Ataei, M., 2015. “Ranking of

Geological Risks in Mechanized Tunneling by Using

Fuzzy Analytical Hierarchy Process (FAHP)”,

Tunneling and Underground Space Technology, Vol.

50, pp. 358-364.

Ossama Y & Barakat, W., 2013. “Application of Fuzzy

Logic for Risk Assessment using Risk Matrix”,

International Journal of Emerging Technology and

Advanced Engineering, Vol. 3, pp. 49-54.

Patel, D. A., Kikani, K. D. & Jha, K. N., 2016. “Hazard

Assessment Using Consistent Fuzzy Preference

Relation Approach”, Journal of Construction

Engineering and Management, Vol. 142, pp. 1-10.

Senouci, A., El-Abbasy, M. S. & Zayed, T., 2014. “Fuzzy-

Based Model for Predicting Failure of Oil Pipelines”,

Journal of Infrastructure System, Vol. 20, pp. 1-11.

Zadeh, L. A., 2008. “Is There a Need for Fuzzy Logic”,

Journal of Information Sciences, Vol. 178, pp. 2751-

2779.

Zatar, W. A., Harik, I. E., Sutterer, K.G. & Dodds, A. 2008.

“Bridge Embankment. I: Seismic Risk Assessment and

Rating”, Journal of Performance of Constructed

Facility, Vol. 22, pp. 171-180.

Geotechnical Assessment for Truss Bridge using Fuzzy-based Soft Computing: Case Study - Kedaung Bridge, Tangerang, Banten Indonesia

139