Productivity of Small-Scale Yellowfin Tuna Fishing in West Region of Ceram District, Moluccas Province, Indonesia

─Analysis on factors which influence productivity of fishing businessis an essential matter to increase fisherman income. This research aims to: 1) Analyze factors which influence productivity of small-scale yellowfin tuna fishing business, 2) Establish structure model of small-scale Yellowfin tuna fishingbusiness productivity. The analysis on factors which influence development of yellowfin tuna fishing in West Region of Seram District uses Structural Equation Model (SEM). The result of the analysis shows that Fishing Operations Material (BOP) is the primary factor which contributes 88% influence. Furthermore, Fishing Operations Unit (UOP) factor has 26% influences. Yet, Fishermen Resources (SDN) does not have any influences on small-scale yellowfin tuna fishing business. Parameter of FishingGround (DRP) has 91% influences and Fishing Season (MSP) has 79% influences on yellowfin tuna fishing business productivity. Productivity structure of small-scale yellowfin tuna fishing has trust level of 99%. Hence, this model of small-scale yellowfin tuna fishing productivity has well accuracy and may become reference model for tuna fisheries management especially sustainable smallscale yellowfin tuna. Keywords— productivity, fishing business, Yellowfin tuna, small-scale fisheries, Ceram Sea.


I. INTRODUCTION
Moluccas province is a potential area of Tuna-Cakalang which gives the second largest contribution in Indonesia (KKP, 2014) and located within area of "Coral Triangle Tuna" (Cabral et al, 2012;Bailey et al, 2012). Yellowfin Tuna (Thunnus albacares) is one of important fish commodities with high market demand. However, the fishing business immensely depends on the availability of fish resources and the aquatic environment. In other sides, national fisheries are still characterized by small-scale fisheries (Hermawan 2006;Tawari et al, 2014;Haruna et al, 2018). Yellowfin tuna fishing is intensely determined by various factors either from internal factor of fish or environment factor. Production rate in fishing is determined by how big the effortof fishing which is done to utilize fish resources. Low production and productivity of yellowfin tuna fishing are generally caused by environment condition dynamics relating to fish distribution pattern, fish size, fishing season characteristic, and area of fishing (Tawari et  In fact, technically production factor becomes a complicated issue in tuna fishing. The success of fishing operation is influenced by fishing tools, boat, supporting tools, and its human resources. Consequently, it needs knowledge between factor and output of production (Soekartawi, 2002;Tawariet al, 2013, Tawariet al, 2014Sangadji, 2014). Development of fisheries business including yellowfin tuna fishing gives social or economic impact on fishermen prosperity level if it is followed by the increasing of fishing result volume (Alhuda, 2016;Rahim and Hastuti, 2016;Maulana F, 2018). In consequences, analysis on factors which influence productivity of fishing business is an essential matter in increasing fishermen income. This research aims to: 1) Analyze factors which influence the productivity of small-scale yellowfin tuna fishing business, 2) Establish a structure model of small-scale yellowfin tuna fishingbusiness productivity. of fishermen who catch Yellowfin tuna. The sample of fishermen is spread in 9 urban villages in WestRegion of Seram District (Fig 1).

Data Collection
The collected data in this research consist of primary and secondary data which are acquired through literature review and field survey. Technique of sample collection (expert survey) is carried out with purposive sampling. The data collection is performed through questionnaire and structured interview to the fishermen (respondents) in 9 fishermen's urban villages. Questionnaire and interview assessment are carried out by using scale of Likert 1 until 5 with low until high category.

Extremely Low Extremely High
Sample in this research is in the number of 150 respondents of yellowfin tuna fishermen in 9 urban villages. The obtained data numbers refer to Maximum Likelihood Estimation (MLE) technique.  Path diagram in this research is developed to see the interaction between the observed variables and know which interactions which have the biggest influence on productivity of small-scale yellowfin tuna fishing business in WestRegion of Seram District. After it is portrayed in a diagram, conversion into structural equaition series is performed. This equation represents causality relationship between various constructions with structur equation as follows: = 1 1 + 2 2 + 3 3 + Information: = latent endogenous variable (dependent) = latent exogenous variable, n = 1,..,3 = latent errors in equations = coefficient matrix for latent exogenous, m = 1,…, 3 Model compatibility test uses standard proposed by Wijanto (2008) with 15 sizes of GOF in Lisrel to assess compatibility of a SEM calculation model. Limitation and criteria to assess a model use goodness of fit.

Model Interpretation
After all of the previous steps have been conducted and the model is quite good, SEM performs interpretation. The usage of SEM is not to generate a theory, but to test model which has appropriate and well fundamental theory. Based on this idea, interpretation of the model can be accepted or prediction power from the model is not needed compared to the produced residual. The use of standardized residual covariance matrix will generate standard residual value. If interpretation towards produced residual through variable observation has bigger standard residual value from particular size, it means the model can be accepted and does not need model modification.

III. RESULT AND DISCUSSION Business Productivity Analysis result uses Structural Equation Model (SEM).
There are nine (9) parameters which categorized as exogenous parameters with various connectivity levels towards three (3) latent independent variables. Furthermore, there are two (two) parameters which become endogenous variables and directly affect Yellowfin tuna fishing business productivity as the latent dependent variable in the research location. Analysis result of interaction and parameters connectivity level with latent variables is presented in form of analysis path diagram (Fig 3).
Three main factors are used as latent variable which influence yellowfin tuna fishing productivity. They are, fishing operations material (BOP), fishermen resources (SDN), and fishing operations unit (UOP). Each of those latent variables has parameter with various connectivity levels which shows the amount of influence towards independent latent variable as the determinant factor on yellowfin tuna fishing especially in the research location. In addition, there are two parameters/endogeneous variables which directly influence dependent laten variabel of yellowfin tuna productivity namely area of fishing parameter (DRP) and fishing season (MSP). .

Fig 3. Connectivity and value of each element which influenceproductivity of yellowfin tuna(Thunnus albacares) fishing business
The amount of connectivity and the level of influence happenned between each factor either between exogeneous paramters with independent latent variable, independent latent variable towards dependent latent variable (productivity), or endogenous parameter towards productivivity (dependent latent variable) is a depiction of yellowfin tuna fisheries in the research location. More details are presented in Figure 3.  Figure 3, it shows that the three assessed parameters have various influences on fishing operations material. Yet, correlation connectivity of fishing trip parameter has bigger influence in which 77% towards fishing operation unit, followed by fishing tool with 47% influence and fishing fleet to the value of 12%. The influence amount of fishing trip parameter shows that dependency of fishing operation unit towards fishing trip parameter itself is more dominant than other parameters. Endogeneous parameter is a parameter which has direct influence on yellowfin tuna fishing productivity (dependent variable) and can be measured as well as controlled. There are 2 endogenous parameters in which fishing ground (DRP) and fishing season (MSP). Based on analysis, fishing ground has error variance value of 0.17 and fishing season has error variance value of 0.37. Thus, it shows that fishing ground has dominant determinant factor towards yellowfin tuna fishing productivity compared to fishing season parameter. Fishing ground is a parameter which has dominant influence with factor loading value of 91% on yellowfin tuna fishing productivity (dependent latent variable). Meanwhile, fishing season parameter only has factor loading value of 79%.

International Journal of Environment, Agriculture and Biotechnology (IJEAB)
The high influence of fishing ground and fishing season on yellowfin tuna fishing productivity in the research location is highly related to habitat and behavior of yellowfin tuna. Dynamics of yellowfin tuna fishing ground is temporary but it is highly influenced by environment condition and oceanograpic oceanic parameter such as sea surface temperature, chlorophyll-a, salinity, stream, depth, front, and upwelling (Zainuddin, 2013;Safruddin, 2018;Hidayat, 2019). Fishing ground influence is followed by fuel oil and ice usage on production because of tuna characteristics which always migrates so that fishing ground becomes uncertain and far away.

Business Productivity Structure Model
From basic model path diagram of the research, it shows clearly that yellowfin tuna fishing productivity is the latent variable which is influenced by two independent latent variable factors namely fishing operations material (BOP)and fishing operations unit (UOP). Among those two independent latent variables, it is found that fishing operations material has extremely big influence on Yellowfin tuna fishing productivity compared to factor of fishing operation unit. Based on result of the analysis, 88% yellowfin tuna fishing productivity is influenced by fishing operation material, followed by fishing operation unit with 26%, while fishermen resources factor does not give influence on the increasing of yellowfin tuna fishing productivity and even it has loading factor with value of -0.14%. Furthermore, based on analysis result, correlation stucture of independent latent variable (BOP,UOP, SDN) on