Intelligent Information Management, 2012, 4, 277-283
http://dx.doi.org/10.4236/iim.2012.425039 Published Online October 2012 (http://www.SciRP.org/journal/iim)
Assessing Safety of Ferry Routes by Ship Handling
Model through AHP and Fuzzy Appr oach
Antoni Arif Priadi1, Tri Tjahjono2, Abdellatif Benabdelhafid1
1Laboratoire de Mathématiques Appliquées, University of Le Havre, Le Havre, France
2Departement of Civil Engineering, University of Indonesia, Jakarta, Indonesia
Received August 30, 2012; revised October 2, 2012; accepted October 13, 2012
ABSTRACT
Ferry accidents often occur the result of ship handling difficulty which interfacing human, machine and environment.
Therefore, a decision tool model as a comprehensive information system, b ased on the sh ip handling d ifficulty, need s to
be developed through the combination of Analytic Hierarchy Process (AHP) and Fuzzy Logic System. The Fuzzy Logic
System part consists of ship condition, ship handling facility conditio n, navigation condition and weather condition. The
output of decision tool is the ship handling difficulty level in linguistic form. The simulation of model is conducted at
several straits in Indonesia water. The decision tool model could be used as management information system by port
authority to monitor the ferry/ship movement in real time regarding the ship handling difficulty. Further, it would be
used to take some useful safety operation strategies and safety policies to improve ferry transportation safety at port
water and strait water.
Keywords: Ro-Ro Ferry; AHP; Fuzzy; Ship Handling
1. Introduction
The maritime transportation affects most of goods and
passengers movement among islands in an archipelago
country, Indonesia. As the result, the reliability of mari-
time transportation to link among islands will impact to
the development of country especially in the frame of
economic sector. The maritime transportation could be
divided into two categories which are sea transportation
and crossing transportation. The crossing transportation
bridges among places as the continuation of road or rail-
way by crossing the straits. The most type of transporta-
tion means for this category use Ro-Ro ferries. A Ro-Ro
ferry is a type of ship where generally able to carry both
passengers and vehicles on same time. The vehicles could
be private cars or commercial vehicles such as truck, bus,
lorry etc.
Ferry routes are divided by three categories such as,
commercial route, pioneer route subsidized by govern-
ment and pioneer route non-subsidized by government.
The numbers of routes in operation have increased from
99 routes in 2006 and 155 routes in 2010 [1]. The detail
number of route is presented in Figure 1.
Figure 2 shows the type of crossing transportation
means condition during 2006 and 2010 in Indonesia [1].
It clarifies that Ro-Ro ferries during 2006-2010 have
played very principal roles for serving ferry transporta-
tion means. Meanwhile, it also showed that the number
of Ro-Ro ferry has risen in number.
Nevertheless, the significance role of Ro-Ro ferry is
not free from the consequences of ship handling. In Fig-
ure 3, it is shown that there were 24 ferries/Ro-Ro acci-
dents during 2003 and 2009 which compose of 25% of
sinking, 25% of fire and 29% of grounding [2].
The cause of the ship accident at Indonesia during
2007-2009 may be categorized by several causal factors
such as weather factor constitute of 34% followed by
27% of human factor and followed by 18% of technical
factor [2].
The ship operation system contains of complex inter-
relation among technical factor, environment factor as
well as human factor that control the ship handling pro c-
ess. One idea of the event of ship accident is the idea of
ship handling process. The ship handling is defined as
the practice of guiding a ship which controls ship move-
ment through ship controllability means, visual monitor-
ing means and instrumental monitoring. Therefore, ship
navigation operation and ship maneuvering are the inte-
grated part of the ship handling. The successful of ship
handling will bring accident far away from it might be
happened. In other word, if there is a problem with ship
handling process such as the difficulty of controlling ship
behavior, it might lead to accident. It could be general-
ized that ship handling difficulty potentially directs to
C
opyright © 2012 SciRes. IIM

A. A. PRIADI ET AL.
278
Figure 1. The numbers of Ro-Ro ferry routes in Indonesia
(2006-2010).
Figure 2. Number of means for transporting cargo and
passenger across islands in Indonesia (2006-2010).
Figure 3. Percentage of Ro-Ro accident in Indonesia (2003-
2009).
ship accident [3].
The ship handling difficulty will transmit a signal to
ship officer in charge to take action properly to current
ship handling situation which it depends among technical
issues, environment issues and human issues. Here, the
information system bridge among human factors, techni-
cal factors, environment factors. The use of appropriate
information will guide the officer to take an appropriate
action and vice versa. Therefore, in the writer’s opinion,
the information system through decision support system
in the complex criteria situation as consequences of ship
handling difficulty is one challenge answer to minimize
the potential of ship accident. The development of ship
handling model for ferry at port water and strait water
based on Analytic Hierarchy Process and Fuzzy Infer-
ence System approach has been developed [4]. The
model is named AHP FIS which consisted of four criteria
such as ship condition with six factors, ship handling
facility condition with six factors, navigation condition
with six factors and weather condition with six factors.
The total numbers of factors considered are 24 factors.
The output of model is ship handling values which de-
termine the level of ship handling difficulty.
The aim of this paper is to assess the ship handling
level of ferry at several straits in Indonesia such as Bali
Strait and Lombok Strait through the paper order of in-
troduction, the overview of AHP FIS ship handling
model, simulation result and conclusion.
2. The Overview of AHP FIS Ship Handling
Model
The AHP FIS ship handling model is based on two
methods. The first method is Analytical Hierarchy Proc-
ess (AHP) which is used for analyzing multi criteria de-
cision problems with multiple criteria. The method of
analytic hierarchy process (AHP) has been used for this
purpose [5]. The hierarchy structure of complex estima-
tion criteria can be represented clearly and definitely.
Then, ratio scale can be utilized to make reciprocal com-
parison for each element and layer. When the reciprocal
matrix is developed, weight comparison for each element
can be obtained. A paper has proposed the AHP for
weighing factor of sh ip danger score during sailing at sea
[6]. Additionally, the method is also used for choosing
the container port in multiple port regions [7] as well as
for assessing ship system risk [8].
The second method is Fuzzy Inference System (FIS).
The FIS consists of fuzzifier, fuzzy inference system and
defuzzifier. Generally, it is a method of calculation us ing
linguistic/word variables, as a replacement of counting
numbers [9]. Meanwhile, the linguistic/words used in
fuzzy logic are not as accurate numbers, nevertheless the
words used are closer to human intuition. A paper was
proposed using a fuzzy logic method for determining the
probability of occurrence (event probability) and cones-
quence of occurrence on formal safety assessment on
LNG carrier [10]. It was begun with the uncertainty of
system failure on the LNG carrier vessel. Uncertainty
LNG carrier system failure in limited water was assumed
at subjectivity of navigational safety, subjectivity of ma-
neuverability, and subjectivity of collision avoidance.
The end output of the research is the risk index of com-
mon hazards which previously calculated in event prob-
ability.
The research on high speed craft ship on the naviga-
tion system had been performed [11]. The research was
begun with the difficulty to assess and analyze the quan-

A. A. PRIADI ET AL.
IIM
279
tity of high speed craft navigation safety factor so formal
safety assessment method based on fuzzy analytic hier-
archy process was done. The development of the system
of risk assessment factors for high speed craft navigation
depends upon three different things which are operator,
the movement of high speed craft and environment. In
such research include the assessment of safety factor of
four parts, namely landform of the navigation channel,
hydrometeorology, traffic, and navigation mark.
The research on new approach in maritime risk assess-
ment for safety at sea which was based on risk factor as a
new development tool of decision that were equipped on
VTIS or naval communication and information system
(CIS) so the individual risk of particular ship could be
monitored was conducted through fuzzy expert system
[12]. An expert system is a tool that mimics th e cognitive
mechanisms of human expertise. This system consists of
three parts, namely an event base, rule-based and infer-
ence engine. In their research, they have used static risk
factors and dynamic risk factors to determine the final
result of i ndividua l ship risk factor.
In reference [13], the use of fuzzy method as a tool for
safety assessment had been performed. It is associated
with classical safety assessment (PRA: probabilistic risk
assessment) which has its disadvantages, especially re-
lated to systems that have fairly high degree of uncer-
tainty such as design of feasibility and design of system.
A significant contribution of theory of fuzzy systems is
the availability of systematic procedure to change the
knowledge based into a non linear mapping. Fuzzy IF
THEN rules is a statement IF THEN in which some
words are characterized by continuous membersh ip func-
tion. For example: IF the likelihood of hazard is frequent
AND severity of occurrence is catastrophic, THEN the
risk level is high. In this case, frequent, catastrophic and
high are membership functions. The fuzzy system is con-
structed from the collection of fuzzy IF THEN rules. In
summary, the fuzzy logic method has been used in sev-
eral researches to deal with uncertainty condition, the
lack of official data, the simplicity of method to handle
complex system, the possibility of involvement of expert
knowledge system. The fuzzy logic system as mentioned
above has been used as a decision tool to monitor indi-
vidual ship risk with several parameters.
The detail of AHP FIS ship handling model architec-
ture is illustrated in Figure 4. The first step of proposed
model is the output of AHP model which are consist of
four variables such as ship con dition, ship handling facil-
ity condition, navigation conditio n and weather conditio n.
Such outputs then are utilized as input of second step
SHIP CO ND IT ION (A)SHIPHANDLING
CONDITION(B) WEATHER CONDITI ON(D)
NAVIGATI ON
CONDITION(C)
AHP Part
FUZZY INFERENCE ENGINEFUZZY RULED BASED
EXPERT KNOWLEDGE BASEDFUZZIFIER
DEFUZZIFIER
SHIP HAND LING DIFFICULTY
VALUE
LINGUISTIC VALUE
A1 -SHIP TONNAGE A5 -B RID GE LOC. A4 -AGE OF SHIP A2 -SHIP DRAF T A3 -S HIP TY PE A6 -S HIP TRIM C3- C4- C5- C6- D1- D2- D3- D4- D5- D6- B1- B5- C1- C2- B2- B3- B4- B6
INFORMATION SY STEM OUTPUT
FOR DECISION MAKING
FIS Part
Figure 4. AHP FIS ship handling model structure.

A. A. PRIADI ET AL.
280






 
min, ,,
fc tStFtNtWt
 
which is fuzzy logic step. The method of Mamdani
(Max-Min) is used on this model. The metho d Mamdami
is used because of several advantages such as intuitive,
wide accepted and suitable by human input. The proce-
dure of fuzzy inference system (FIS) is begun with the
development of membership function (µ), the develop-
ment application of implication function, the develop-
ment of rule composition and defuzzification. The detail
process is illustrated in Figure 4.
The construction of AHP part is based on previous re-
search [14]. Meanwhile the FIS part construction is based
on previous research [4]. Similar approach was per-
formed to determine the rank of ship which will be in-
spected [12]. This approach has used dynamic risk fac-
tors and static risk factors for fuzzy risk evaluation. The
static risk evaluation factors consist of ship flag, year of
construction, gross tonnage, number of companies, dura-
tion of detentions and type of ship. Meanwhile, dynamic
risk evaluation factors consist of sea state, wind speed,
visibility, and night or day. They used such factor with-
out any justification for determining which factor has
importance priority among others. The AHP FIS model
uses AHP approach to determine the importance level of
factors which are then processed through fuzzy logic.
This approach could give a way to limit level of uncer-
tainty before input factors are processed through fuzzy
inference system. It also will simplify the development of
rules in fuzzy inference system.
3. The AHP FIS Algorithm
In this section, the overall of algorithms which are used
to construct the AHP FIS ship handling model is pre-
sented. The algorithm is presented from the development
of fuzzy membership function until the end of result
which is ship hand ling difficulty.

St St  
  
,a SHD t

a
SHD t
1
th nn
N
aa
n
sA P



234 6
,,,
(1)
where is obtained from

SHD t (2)
and An is function of A1, A2, A3, A4, ···, A6
1
,,
n
A
fAAAA A (3)
where, A1: sh ip tonnage, A2: ship draft, A3: ship typ e, A4:
ship age, A5: bri dge l ocat ion, A6: ship trim.
The same analogy is performed for the algorithm of
ship handling facility condition, navigation condition and
weather condition.
The next formulation is the formulation of member-
ship function of fuzzy consequence as described in algo-
rithm:
(4)
where,


St 
: membership function of the criterion of Ship
Condition;


F
t 
: membership function of the criterion of Ship
Handling Facility Condition;


Nt 
: membership function of the criterion of Navi-
gation Conditio n;


Wt  : membership function of the criterion of Wea-
ther Condition.
Further, the formulation membership function of fuzzy
solution could be written as illustrated in algorithm:




max ,
fsfs fc
ttt   (5)
where,


t 
fs : membership functions of the fuzzy solutio n of
x until rule of t;


t 


fc : membership functions of the fuzzy conse-
quence of x until rule of t,
and the final formulation of the implication of fuzzy
solution could be written as :
d
d
fs
t
s
fs
t
ttt
SHD tt



 (6)
where, SHDs is value of Ship Handling Difficulty.
4. Simulation
The simulation of model to assess ship handling diffi-
culty level on several ferry routes in Indonesia is con-
ducted. The first ferry route is Ketapang-Gilimanuk at
Bali Strait where is located between East part of Java
Island and West part of Bali Island. The second ferry
route is Lombok Strait where is located between East
part of Bali Island and West P ar t of Lom bok Islan d.
The simulation of model uses scenario which is deve-
loped from several data such ship particular, weather
condition and preference state of ship master on ship
handling behavior. The ship particular was extracted from
website. [15,16]. Some ship particular data are created
due to limitation of data source. The weather condition
was taken from Badan Meteorology Klimatologi Geofi-
sika Indonesia for the date of 14 April 2012 [17]. The
preference state of ship master is used and based on an-
other study [18,19]. The detail of simulation data is pre-
sented in Table 1.
The application of model will use 12 ships for each
strait with seven phases of navigation. The seven phases
consists of two phases at departure port, three phases at
sea area and two phases at arrival port. Therefore, each
strait will have 84 scenarios. The detail is presented in
Table 2.

A. A. PRIADI ET AL. 281
The result of each application scenario is presented in
the table form and column chart form. By using algo-
rithm 1 - 6, the ship handling value is calculated and
processed through two steps which are AHP and FIS.
The result of calculation is shown at Table 3 as an ex-
ample.
The calculation result shows that ship handling value
for Padangbai (PAD) at Lombok Strait has the highest
value both on Minimum SHDs and Maximum SHDs. It
means that ship handling difficulty at Padangbai as de-
parture port relatively more difficult than at port of Keta-
pang (KET), port of Gilimanuk (GIL) and port of Lem-
bar (LEM). Port of Ketapang (KET) has the lowest value
of ship handlin g difficult y .
Meanwhile, at sea area, ferry route of Ketapang-Gili-
manuk has higher value of ship handling difficulty than
Table 1. Simulation scenario.
Ship Condition Data Bali Lombok Nav. Cond. Data Bali Lombok
Tonnage Real Ship speed Scenario 1 1
Ship draft Scenario 4 4 Depth of water Scenario 2 2
Ship type Scenario 1 1 Communication Scenario 2 2
Age of ship Real 0 0 Ship Position Scenario 7 7
Bridge position Scenario 1 1 Nav.Status Scenario 1 1
Trim Scenario 1 1 Traffic situation Scenario 6 6
Ship Hand. Fac. Cond Data Bali Lombok Weather Cond. Data Bali Lombok
Main Eng Type Scenario 1 1 Wave Real 2 3
Number ship prop. Scenario 1/2 1/2 Wind Real 5 5
Type prop. Scenario 1 1 Current Scenario 2 2
Number ship rudder Scenario 1/2 1/2 Visibility Scenario 3 3
type ship rudder Scenario 1 1 Swell Real 2 2
Side thruster Scenario 1/2 1/2 Day/Night Scenario 1 1
Table 2. Scenario application of ship handling model.
Scenario time (tn)
Strait location Number of ship Departure Sea Arrival Remarks
Bali 12 2 3 2
Departure from Ketapang (KET), arrival at Gilimanuk
(GIL), the total number scenario is 84.
Lombok 12 2 3 2
Departure from Lembar (LEM), arrival at Padang bai
(PAD), the total number scenario is 84.
Table 3. Part of ship handling calculation.
IF Scenario A B C D SHDsTHENX LInguistic Shiphandling Diff.
Accept.
Criteria
IF F1 t1 0.394 0.440 0.145 0.5511.53 THEN1.82 Somewhat SafeNegligence Acceptable
IF F1 t2 0.394 0.440 0.145 0.5511.53 THEN1.82 Somewhat SafeNegligence Acceptable
IF F1 t3 0.394 0.425 0.147 0.5221.49 THEN1.65 Fairly Safe Negligence Acceptable
IF F1 t4 0.394 0.425 0.147 0.5221.49 THEN1.65 Fairly Safe Negligence Acceptable
IF F1 t5 0.394 0.425 0.147 0.5221.49 THEN1.65 Fairly Safe Negligence Acceptable
IF F1 t6 0.394 0.436 0.145 0.5681.54 THEN1.90 Somewhat SafeNegligence Acceptable
IF F1 t7 0.394 0.436 0.145 0.5681.54 THEN1.90 Somewhat SafeNegligence Acceptable

A. A. PRIADI ET AL.
282
Figure 5. Result of simulation.
ferry route of Padangbai-Lembar. In general, ship hand-
ling difficulty at sea area has lower value than at port
area. The detail of ship handling value for the simulation
is illustrated in Figure 5.
5. Conclusion
Based on this approach, port of Padangbai (PAD) has
highest ship handling difficulty value in any case fol-
lowed by port of Lembar (LEM), port Gilimanuk (GIL)
and port of Ketapang (KET). Therefore, for ship master
at port of Padangbai (PAD) should give attention to ship
handling of their ferry. Further, Bali Strait has higher
ship handling difficulty on maximum valu e of SHDs than
Lombok Strait. Whereas, in any cases, average value of
SHDs showed that Lombok Strait has higher ship han-
dling difficulty than Bali Strait. The result of simulation
of ship handling model could be used for several parties
concerned such as ship master, shipping company and
port authority. Ship master of Ro-Ro ferries should more
aware during ship handling process especially during
departure and arrival at port. The appropriateness of the
arrangement of officer for departure and arrival process
would prevent the potential accident refers to ship han-
dling difficulty. Further, the shipping company could
establish strategies which are different for each ferry
route. Special attention should be given to ferry routes
which ship handling difficulty value is in higher level.
Finally, the port authority could develop ship handling
difficulty index for each ferry route, so each ferry will be
justified and verified for ship handling characteristic be-
fore they put in to service.
REFERENCES
[1] Directorate General of Land Transportation, “Land Trans-
portation in Number 2010,” Directorate General of Land
Transportation, Ministry of Transportation Indonesia,
2011.
[2] Directorate Coast Guard, “Ship Accident Recapitulation
2003-2009,” Directorate Coast Guard, 2009.
[3] K. Inoue, “Evaluation Method of Ship-handling Difficulty
for Navigation Restricted and Congested Waterways,”
Kobe University of Merchantile Marine, Kobe, 1998.
[4] A. Priadi, T. Tjahjono and A. Benabdelhafid, “Ship Hand
ling Difficulty Decision Tool for Safety Improvement of
Ship Operated at Port Water and Strait Water Based on
the Combination of AHP and Fuzzy Logic: Study Case
Ferry,” World Conference Transport Research Society
(WCTRS) Conference, Antwerp, 21-22 May 2012.
[5] T. L. Saaty and L. G. Vargas, “Model Methods Concepts
and Application of the Analytic Hierarchy Process,”
Kluwer Academic Publication, Norwell, 2001.
[6] H. Persada, “Study on Determining Hazard Navigation
Map through Danger Score by Using AIS Data,” Thesis
Paper, Sepuluh Nopember of Institute Technology, Sura-
baya, 2011.
[7] C. Chuo, “AHP Model for the Container Port Choice in
the Multiple-Ports Region,” Journal of Marine Science
and Technology, Vol. 18, No. 2, 2010, pp. 221-232.
[8] H. Nguyen, “The Application of the Ahp Method in Ship

A. A. PRIADI ET AL. 283
System Risk Estimation,” Polish Maritime Research, Vol.
59, No. 16, 2009, pp. 78-82.
[9] L. Zadeh, “Fuzzy Sets,” Information and Control, Vol. 8,
No. 3, 1965, pp. 338-353.
doi:10.1016/S0019-9958(65)90241-X
[10] P. Zalewski, “Risk Assessment of LNG Carrier Systems
Failure Using Fuzzy Logic,” Scientific Journal of Mari-
time University of Szczecin, Vol. 97, No. 2, 2011, pp. 77-
85.
[11] J. Li, “Risk Assessment Model of High Speed Craft
Navigation Based on Fuzzy Analystical Hierarchy Proc-
ess,” Journal of Computational Information System, Vol.
6, No. 5, 2009, pp. 1661-1667.
[12] J. Balmat, F. Lafont, R. Maifret and N. Pessel, “Maritime
Risk Assessment (MARISA), a Fuzzy Approach to De-
fine an Individual Ship Risk Factors,” Ocean Engineering,
Vol. 36, No. 15, 2009, pp. 1278-1286.
doi:10.1016/j.oceaneng.2009.07.003
[13] H. S. Sii, T. Ruxton and J. Wang, “A Fuzzy-Logic-Ba sed
Approach to Qualitative Safety Modelling for Marine
Systems,” Reliability engineering and System Safety, Vol.
73, No. 1, 2001, pp. 19-34.
doi:10.1016/S0951-8320(01)00023-0
[14] A. Priadi, A. Benabdelhafid and T. Tjahjono, “Deter-
mining Ship Handling Difficulty Level for Ferries at Port
Water and Strait Water,” International Conference on
Management, Social and Humanities (ICMeSH), Kuala
Lumpur, 2012.
[15] Directorate General of Land Transportation, “Profile and
Performance of Land Transportation of Bali Province,”
Directorate General of Land Transportation, Ministry of
Transportation Indonesia, 2011.
[16] Directorate General of Land Transportation, “Profile and
Performance of Land Transportation of Nusa Tenggara
Barat Province,” Directorate General of Land Transpor-
tation, Ministery of Transportation Indonesia, 2011.
[17] BMKG, “Maritime Weather Prediction Sunda Strait, Bali
Strait and Lombok Strait,” 2012.
http://maritim.bmkg.go.id/index.php/main/pra_penyebera
ngan_det/2
[18] A. Priadi, “Descriptive Study on Determining Ship Han-
dling Difficulty of Ferry: Case Study Ketapang—Gili-
manuk,” Part of Dissertation Progress Report No. 2, Uni-
versity of Indonesia and Unive rsity of Le Havre, Le Havre,
2012.
[19] A. Priadi, “Descriptive Study on Determining Ship Hand-
ling Difficulty of Ferry: Case Study Lembar—Padang-
bai,” Part of Dissertation Progress Report No. 3, Uni-
versity of Indonesia and University of Le Havre, Le
Havre, 2012.