MATEC Web of Conferences 204, 03010 (2018) https://doi.org/10.1051/matecconf/201820403010 IMIEC 2018

Development of fatigue, accident experiences and safety relationships to the risk of fishing on the accidents of fishing vessel small and medium

Septi Nurindah Sari1,*, Ratna Sari Dewi1, and Adithya Sudiano1 1Industrial Engineering, Faculty of Industrial Technology, Institut Teknologi Sepuluh Nopember, 60111 Surabaya, Indonesia

Abstract. Working at sea is associated with many challenges and risk in the job, such as a high workload, inappropriate working hours, minimum time for hanging out with family and increasing the risk of accidents. When an accident occurs, the perception of the risk of occupational accidents seafarers increased so that all workers start to think about their safety. Fatigue is one of the factors that can affect the seafarer safety. Fatigue among the seafarers is affected by lack of sleep duration and low sleep quality. Besides fatigue, accidental experiences can also influence risk . When the workers themselves or their friends see or experience an accident, it is likely to increase the risk of accidents perception among the workers. In addition to fatigue and accident experience, safety culture can also affect the perception of risk. Safety training, identification and , safety awareness and incident reporting are several factors that can be used to assess the safety culture. Therefore, the aim of this study is to examine the influence of fatigue, sleep quality, accident experiences and safety culture on the risk perception of fishermans who works at the Indonesian maritime territoires.

1 Introduction Working at sea is associated with many challenges and risk in the job, such as a high workload, working hours are not appropriate, and least time hanging out with family and increasing the risk of accidents [1]. Although accident rates go down in the few decades but fisherman still one of high rates of fatal occupational [2]. National Institute for Occupational Safety (NIOSH) reported that commercial fisheries are a dangerous occupation. According to data from NIOSH 2014 in the US, there are 124 deaths from 100,000 workers between 2000 and 2009 in this sector [3]. In the years from 2010 – 2016 there were 337 fatal injuries and 474 wounded in the Indonesian. This data from that data

* Corresponding author: [email protected]

© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/). MATEC Web of Conferences 204, 03010 (2018) https://doi.org/10.1051/matecconf/201820403010 IMIEC 2018

not including unregistered small fishermen and recorded in the KNKT investigation [4]. When an accident occurs, risk perception of occupational accidents seafarers increased so that all workers to think about their safety. Risk perception cn be defined as personal assesment with respect to the likelihood of undesired consequences occuring and defferent level depending on the type of risk [5]. Perception risk of accidents or injuries causing tension such as anxiety, distress, tension and reduce the physical and psychological resources. Risk perception can affect sleep quality and fatigue too [6]. Fatigue in maritime have become aspects which can trigger concerns in working life as a sailor [7]. International Maritime (IMO) describes fatigue can lead to reduced physical / mental abilities resulting from the use of physical, mental or emotional activity that can disrupt the performance of seafarers [6]. Working hours during sailing are a contributing factor to fatigue in ship crews where the International Labor Organization (ILO) recommends limits on working hours on shipping ie eight hours a day or forty-eight hours a week [8]. Although a rules maritime regulated the maximum hours of work but fishermans still a 24 hours of work on board. Negative effect of fatigue can inclued into willingness to take risk, performance impairments and increased accident involvement for safety workers. Sleep quality the most important contribution to fatigue [1], sleep quality can also include quantitative aspect such as sleep latency and number of hours [9]. Besides fatigue, accidental experiences can also influence risk perceptions. When the workers themselves or a friend who see an accident, likely to increase the risk of accidents perception even after the accident occurred [10]. In addition to fatigue and accident experience, safety culture can also affect the perception of risk. Safety culture is also determined together with the relevant way of thought or action that is created through the collective bargaining of the social environment [11]. To determine the safety culture assessment Corigan use safety training, hazard identification and risk assessment, safety awareness and incident reporting [12]. Safety Culture has an important element used to measure whether the safety culture is going well or not. An important element of safety culture is from employee and corporate comitment to the safety of its workers, the culture of reporting and learning, training and communication on safety [11]. Employee perceptions of the risk of injury and accidents are a feeling of future accidents or injuries and have been identified as predictive of risky behaviors that can increase accidents and injuries to health. Risk perceptions are divided into two types: the inherent risk perception of the worker as the nature of the job is more dangerous than other occupations and the second type of risk perception is the risk caused by action and inaction management such as ineffective safety equipment or training failure [13]. The goal of study is to find out how much influence the correlation of fatigue, accident experience and safety culture to risk perception. From all the above problems to determine the model of the effect of the correlation between fatigue, experiences of accidents and safety culture against the risk perception is used Structural Equation Modeling (SEM) software. SEM is a multivariate analysis to examine the relationship between complex variables both recursive and nonrecursive to obtain a comprehensive picture of a model [13]. SEM can perform testing jointly that is: structural model that can measure relation between independent and dependent construct, and measurement model that measure relation (loading value) between indicator variable with construct (latent variable) [14].

2 Methods and Measurement

2.1. Participant and procedure

Participant in study were fisherman working on fishing vessel size 10-30 GT and working for 15 days in the sea. Total participants 200 fisherman and captain.

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Questionnaries shared to fisherman and all of questionaries return. Of the total 200 return questionaries, 176 participant as fisherman and 24 captains. And than measurement questionaries with SPSS 16 to determine validity and use reliability α for the abridged version 0,60.

2.2. Measurement Scale

In this study, the questionnaire used a Likert scale to measure the degree of importance of sleep quality, fatigue, accident experiences, safety culture and risk perception variabel. The weighting scores are as follows: a. Strongly Agree (SS) with a score of 5 b. Agree (S) with a score of 4 c. Simply Agree (CS) with score weight 3 d. Disagree (TS) with score weight 2 e. Strongly Disagree (STS) with the weight of score 1

3 Result 3.1. Validity and Reliability The number of respondents in this study is 200 people and tested the validity for each attribute using SPSS 16 so that the value of r calculated. The value of r count is valid if> r table is 0,138. Reliability value test value> 0.60 for all variables studied. The result can be concluded that all variables are reliable. According to [15], Cronbach's Alpha usually uses certain limitations such as 0.6. The reliability of less than 0.6 is less good, whereas 0.7 is acceptable and above 0.8 is good.

3.2. Test assumptions SEM

3.2.1. Outlier Data Test and Normality Test It is known that in the outlier test no observation has dalanquin d-squared above 35,910, so the observation can be done in further analysis. Based on the results of data processing known CR value of multivariate is equal to 1,180 outside the hose -2.58 to 2.58. Thus, it can be said that the data used in this study is normally distributed or in other words the assumption of normality is met.

3.3. Structural Equational Modelling (SEM) Analysis 3.3.1.Structural Model Analysis After the structural model has been made, the next step is to test the goodness of fit model to ensure that the structural model that has been prepared can explain the direction of the relationship and the direction of influence correctly and does not cause the bias of the estimation. The estimation and fit model of one step approach to SEM by using Amos 21 application program can be seen below:

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Table 1. Goodness of Fit

Cut-off Criteria Goodness of Fit Model Evaluation Value Expected Χ2 - Chi Square 246,963 UnFit small Probability 0.000 ≥ 0,05 UnFit CMIN/DF 1.929 ≤ 2,00 Good Fit RMSEA 0.068 ≤ 0.08 Good Fit GFI 0.882 ≥ 0,90 Marginal Fit AGFI 0.842 ≤ 0,90 Marginal Fit TLI 0.952 ≥ 0,90 Good Fit CFI 0.960 ≥ 0,90 Good Fit NFI 0.921 ≥ 0,90 Good Fit

Table 1 shows that the goodness of fit criteria in chi square have not met the cut off value. Furthermore, this model will be done modification indices in accordance with the guidelines in AMOS 21.

Fig. 1. Structural Models

Table 2. Goodnes Of Fit after Modification Indices

Criteria Goodness of Fit Cut-off Value Model Evaluation Expected Χ2 - Chi Square 137,930 Good Fit small Probability 0.063 ≥ 0,05 Good Fit CMIN/DF 1.210 ≤ 2,00 Good Fit RMSEA 0.032 ≤ 0.08 Good Fit GFI 0.933 ≥ 0,90 Good Fit AGFI 0.899 ≤ 0,90 Marginal Fit TLI 0.989 ≥ 0,90 Good Fit CFI 0.992 ≥ 0,90 Good Fit

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NFI 0.956 ≥ 0,90 Good Fit

Table 2 shows that most of the goodness of fit criteria have met the cut off value or at least have met the marginal fit criteria, it is that the evaluation results show a good model. This explains that the model used in this study yielded the expected level of estimation. the model produces a better evaluation than before. The results of the running full model that has been modified can be seen in Figure 2.

Fig. 2. Modified Structural Models Table 3. Standardized Regression Weight Full Model Structural Modification Corelation Estimate S.E. C.R. P-value Exp. Sleep quality  0,349 0,104 3,369 0,000 Significant fatigue fatigue  risk 0,338 0,063 5,365 0,000 Significant perception Accident experiences 0,548 0,099 5,532 0,000 Significant  risk perception safety culture  risk -0,024 0,067 -0,357 0,721 Not Significant perception

This value obtained from SEM output and then look estimate positif value. If estimate positif value, this variabel positif correlation and significant corelation if P value > 0,05 sinificantly but if estimate negative value this variabel inverserly proporsional corelation. Based on the result of causality test shown in Table 3, can be explained as follows:

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1) Sleep quality has a positive and significant effect on fatigue because estimate value shown is positive, that is 0.349 with probability of 0.000. 2) Fatigue has a positive and significant impact on risk perception because the estimate value shown is positive, that is 0.338 with probability of 0.000. 3) Crash experience has a positive and significant impact on risk perception because estimate value shown is positive, that is 0,548 with probability 0.000. 4) Safety culture has a negative but not significant impact on risk perception because the value of estimate is negative, -0.024 with probability of 0.721.

4 Discussion The aim of this study was to to find out how much influence the correlation of fatigue, accident experience and safety culture to risk perception. Previous studies of risk perception have shown that workers can have fairly accurate perceptions of the risks that they face [16]. In our study, we hypothesized that fatigue would influence risk perceptions significantly. The results showed that significantly of fatigue were related to increases in perceived risk of both personal injuries and ship accidents. Fishermen are experience fatigue by the way they work with traditional tools and long duration of work. There is no shift work for fishermen one of the factors accident because all fishermen have to work at night, when the fish gather. Fishermen also often loss of due to fatigue which affects the safety of fishermen as a loss of control when catching fish that makes fishing fell and drowned into the sea. To prevent fatigue among seafarers, management use 6/6 watch system that is 6 hours and 6 hours of rest or 4 hours and 8 hours of rest depends on development policy of the management of the ship itself. The second hypothesized is accident experience has a positive and significant impact on risk perception. further reinforces previous research that workers with low frequency of accidents have low risk perceptions as well and vice versa. Workers who have witnessed accident of peers or themselves are more likely to perception a higer personal accident risk and ship accident. Even if the probability of an accident is not greater after such an event has occurred. The third hypothesized is safety culture has a negatif and not significant impact on risk perception.

5 Conclusion Fatigue, accidental experience can direct effect to increase risk perception. The higher variabel value so higher risk perception value too. But inversely propotional to safety culture, this variabel not significant corelation to risk perception and has negatif value. The better safety culture the less likely to have an accident.

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