INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 6, ISSUE 08, AUGUST 2017 ISSN 2277-8616 The Effect Of Technical Aspects Of Purse Seine On Productivity In ,

Resky Amalia Rajab, Najamuddin, Andi Assir Marimba

Abstract: Based on some research that has been done about the influence of technical aspects on productivity of purse seine only examine some variables from the technical aspects. This research is done by combining several variables based on previous research which influences the productivity of purse seine in the coverage of technical aspects as well as adding the variables which are considered to influence the productivity of the purse seine. This study aims to analyze the effect of technical aspects on productivity of purse seine in Jeneponto Regency. This research was conducted in Jeneponto District which is a area which operated the gear fishing gear which is in Pabbiringa village, Binamu district and Pao village, Tarowang district. Survey methods carried out by taking 100% of the total population of purse seine in Jeneponto and following fishing operations with purse seine during 30 trips. The result of this research shows that the technical aspect that gives a real effect to the catch of fish on the net is the net length (X1), sinking power (X3), vessel length (X5), pursing speed (X9).

Index Terms : Fishing Productivity, Technical aspect, Purse seine, fish catches ————————————————————

1 INTRODUCTION According to Pratama et al. (2016) [10], the factors that Fishing productivity is a measure of the production influence on the productivity of purse seine are long trip, capability of a type of fishing gear. Fishing productivity is number of crew, watt, net length, width or depth of net, expressed in the ratio between production and fishing effort. engine power, fuel, and captain's experience. According Each type of fishing gear has different catching principles, Laissane (2011) [6], a high sinking speed it will accelerate so capture capability in production is also different (Nelwan the decline in the net completely, thereby reducing the et al., 2012) [8]. The performance of purse seine depends chances of fish to escape. According to Zhang et al. (2013) on the design and physical characteristics of the materials [17], which affects the sinking speed of fishing gear is used to build the fishing gear. Structural components such netting knotless, the instability of sinking of purse seine as mesh that provide varying in chemical composition and especially in areas with complex currents and waves occurs specific gravity. Similarly, mesh size, yarn thickness, and because the inertial mass coefficient is less than knotless float volume and weight sinker are used to provide positive netting. Rumpa (2016) [13] the most influence on the and negative buoyancy in different parts of the web can productivity of purse seine are net length, net depth, sinking affect the behavior and performance of fishing gear (Kim et speed, vessel capacity, and engine power. Based on some al., 2007) [5]. There are various technical factors that research done on the effect of the technical aspects of the influence the productivity of the purse seine. According to productivity of purse seine only examine a few variables Purwanto and Nugroho (2011) [11], it is influenced by the from the technical aspects, So that in this research is done engine power of vesssel, besides that the speed of sinking by combining several variables based on previous research of fishing gear influences the productivity of purse seine which have an effect on productivity of purse seine in the (Hosseini et al., 2011 [2]; Widagdo et al., 2015) [15]. scope of technical aspect as well as adding new variable According to Suryana et al. (2013) [14], the productivity of which is considered to influence the productivity of purse purse seine is influenced by the length of the net, and seine based on the circular accuracy, so it can be seen for power of the engine. According to Imanda et al. (2016) [3], technical aspect which most influence to the productivity of influenced by the engine power of vessel. According to purse seine. Yusuf (2016) [16], the most influential on the productivity of purse seine is sinking speed of purse seine. According Kefi 2 METHODS (2013) [4], the successful operation of the purse seine This research was conducted in September 2016 - based research results show that the purse seine February 2017 in Jeneponto Regency, Pabbiringa Sub- operations using FADs is setting speed and pursing speed. District, Binamu District, and Pao Village, Tarowang District. According to Suryana et al. (2013) [14], technical factors Location of the research are presented in Figure 1. that most influence on the productivity of purse seine catches are net length.

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 Resky Amalia Rajab is currently pursuing masters degree program in Fishery Science, Faculty of Marine and Fishery in Hasanuddin University, , South , Indonesia, tel: +6285242515152. E-mail: [email protected]  Najamuddin, Lecture in Faculty of Marine and Fishery in Hasanuddin University, Makassar, , Indonesia. Email: [email protected]  Andi Assir Marimba, Lecture in Faculty of Marine and Figure 1. Location of the research in Jeneponto Regency Fishery in Hasanuddin University, Makassar, South Sulawesi, Indonesia. Email: [email protected] 248 IJSTR©2017 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 6, ISSUE 08, AUGUST 2017 ISSN 2277-8616

2.1 Sampling Technique 3 RESULTAND DISCUSSION The method used is a survey method which takes a sample Based on Table 1 the results of analysis using anova test of the population purse seine equal to 100% of the total obtained the value of F calculated was 48.254 with a population of purse seine in Jeneponto. Data collection for significance level of 0.020, the probability value was much technical aspect is done by following fishing operation smaller than 0.05. This indicates that the regression model activity for 30 trips. can be used to predict the number of catch on the purse seine. In addition, the F table value is 19.371, so F 2.1 Analysis Data arithmetic> F table (48.254> 19371) this shows that the In this study used multiple linear regression analysis. independent variable can be used to predict the dependent Before multiple regression analysis, first classical variable. assumption test is used to fulfill multiple linear regression test assumption. The classical assumption test is normality Tabel 1. Analysis Of Variance (Annova) of independent test, multicollinearity test, correlation, and autocorrelation variable and dependent variabel test. Here are the equations for multiple linear regression tests: Model Sum of Squares df Mean Square F Sig. a Y=a+b1X1+b2X2+b3X3+b4X4+b5X5+b6X6+b7X7+b8X8+b 1 1.009E8 9 1.121E7 48.254 .020 Regression 464455.775 2 232227.888 9X9 Residual Total 1.013E8 11 Where : Y = The weight of the catch (Kg) For multicollinearity test, the eight factors of production a = Constant indicate the existence of multicollinearity among factors of b1,b2 = Regression coefficients production, it is viewed from the value of tolerance and VIF X = Independent variable (Variance Inflation Factor) value. VIF value> 10.00, so in X1 = Net length (meter) this case there are some omitted variables of net depth X2 = Net depth (meter) (X2), sinking speed (X4), and setting speed (X7). This is X3 = Sinking power (Kgf) because the net depth associated with the drowning speed X4 = Sinking speed (meter/second) of the fishing gear and the net width size tends to follow the X5 = engine power (PK) length of the net, the sinking velocity is related to sinking X6 = Vessel length (meter) power and the speed of the setting with respect to the X7 = Vessel speed (Knot) engine power of vessel. This is because the net depth has X8 = Circular accuracy related with sinking speed and net depth have related with X9 = Pursing speed (meter/ second) net length, sinking speed is related to sinking power and setting speed is releted to the engine power. Furthermore, F test is performed, this test is used to find out whether the independent variable (X1, X2 ... ,X9) together Tabel 2. Multicollinearity test of independent variables (X) significantly influence the dependent variable (Y). As for the hypothesis used are: Collinearity Statistics Model Ho: There is no significant influence between the nine Tolerance VIF variables X together against the number of catches. (Constant) Ha: There is a significant influence between the nine X1 .151 6.618 variables X together on the number of catches. X3 .555 1.802 Based on the above hypothesis as for the test criteria, 1 X5 .700 1.428 namely: X6 .453 2.206  If F arithmetic F table then Ho is rejected X8 .765 1.307 X9 .222 4.503 Furthermore, to know the effect of variable X to Y partially then t test. As for the hypothesis used are: The result of multicollinearity test in Table 2 shows that Ho: Partially no significant influence between variable X there is no multicollinearity among production factors, it can with variable Y be seen based on tolerance value, tolerance value for the Ha: Partially there is significant influence between variable six variables is greater than 0.10 which shows that there is X with variable Y no multicollinearity among production variables. In addition, can be seen on VIF (Variance Inflation Factor) <10.0, Based on the above hypothesis as for the test criteria, indicating that there is no multicollinearity between factors namely: of production.  If -t table t table, then 3.1 Coefficient of Determination (R2) Ho is rejected The coefficient of determination can be used to know the level of influence of independent variable (X) to the value of dependent variable (Y). In Table 3 the value of 249 IJSTR©2017 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 6, ISSUE 08, AUGUST 2017 ISSN 2277-8616 determination coefficient of the analysis result is 0.875 or of catch are net length (X1), sinking power (X3), vessel 87.5%. It shows that 87.5% of the factors of production length (X6), and pursing speed (X9). Based on the results affect the catch, and 12.5% comes from other factors. of multiple linear regression analysis in Table 5, the equation is obtained: Tabel 3. Coefficient of determintaion Y = - 20506.280 + 26.906X1 + 13.265X3 + 92.402X6 – R Adjusted R Std. Error of the 10.311X9 Model R Square Square Estimate 1 .935a .875 .656 1779.02075 3.3.1 Net length (X1) The length of the net has a significant value. = 0.019, the sig value <0.05, it shows that the net length has significant 3.2 F Test effect on the catch, but it can also be seen on t value = For the F test can be used to determine the effect of 3.401, t value> t table (3.401> 2.571) it shows that the net variable X jointly or thoroughly against the variable Y. length was significantly affect the number of fish catches. Based on the results of F test in Table 4 obtained value of F This happens because the greater the dimension of the net arithmetic = 17.297, F count> F table (17.297> 5.050) this the greater the coverage of areas that can be blocked so as indicates that the model of regression can be used to to have great possibilities to obtain the catch. Based on the predict the catch or all the variables X give a real effect on above equation states that the constant value -20506.280 the variable Y. In addition, can be seen on the significance means that if the independent variable does not exist then value = 0.003, the value of significance

The t test is used to determine the effect of independent 3.3.2 Sinking Power (X3) variable regression model that is the net length (X1), The sinking power has significance value = 0.022, the sig sinking power (X3), vessel engine power (X5), vessel length value <0.05, it shows that sinking power has significant (X6), circular aacuracy (X8), and pursing speed (X9) effect on the catch, but it can also be seen at t value = partially significant effect on the number of results (Y). 3.265, t value> t table (3.265> 2.571) Shows that sinking Table 5 shows that the variables that influence the number 250 IJSTR©2017 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 6, ISSUE 08, AUGUST 2017 ISSN 2277-8616 power has a significant effect on fish catches. Sinking al. (2013) [14], that the greater the dimension of the vessel power may affect the amount of catches for sinking power the ability of the vessel to purse seine, Fishing ground will will affect the sinking speed of a fishing gear, high sinking be more extensive, in addition to the size of the ship also power then the sinking speed will also increase so that will affect the movement of the ship at sea like a circular reduce the chances of fish to escape because it will quickly motion. In addition, according to Imanda et al. (2016) [3] form a wall that prevents fish escape horizontally. The value states that the size factor of the vessel affect the catch of the variable regression coefficient of sinking power (X3) because length vessel are generally equipped with large is 13.265 indicates that each 1 kgf will increase the number powered engines, length nets, and accommodate more of catches by 13,265 Kg for 30 trips or 0.44 Kg per trip. The catches. So, when the operation of fishing gear will facilitate sinking power of the purse seine has a significant effect on the process of catching so that indirectly able to increase the productivity of the purse seine, in accordance with the catch. Widagdo et al. (2015) [15], the speed of sinking of the fishing gear is influenced by the weight of the net in the 3.3.4 Circular accuracy (X8) water, knot type, mesh size, thickness of the yarn, hanging Based on the result of t test show that circular accuracy ratio, geometry of the net, and length of float line, have low does not affect to the number of catch, this is based on water resistance. In this case the speed of sinking the value of significance = 0.117, value significance> probability fishing gear in the research location is still low this is value (0.117> 0.05), but also can be seen at t value = 1. suspected because of the type of knot, mesh size, and 896, the value of t arithmetic probability value (0.339> larger swimming speed. 0.05) it shows that power engine does not give significant effect to the number of catches. It can also be viewed on t 3.3.5 Pursing Speed (X8) value, t value of ship machine = 1.058, t count t table (2.608> drawing of the ropes indicates more catches. This means 2.571) this shows that the length of the vessel has a that the speed of withdrawal of the cord has a great effect significant effect on the number of catches. The value of the on the catch because at the time of drawing, the rope will vessel lenght (X6) is 92.402 indicates that any addition of 1 pass just below the fish so that the faster drawing speed of meter length of vessel will increase the number of catches the rope will be better and quickly closes the bottom of the by 92.402 Kg for 30 trips or 3,080 Kg per trip. The length of net and minimizes the possibility of the fish escaping of the the vessel has a significant effect on the productivity of the section. This is also in line with the opinion of Muntaha et purse seine, in accordance with the opinion of Suryana et al. (2012) [7], the longer the hauling speed then the catch

251 IJSTR©2017 www.ijstr.org INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 6, ISSUE 08, AUGUST 2017 ISSN 2277-8616 will decrease, this happens because the fish are clustered if In Southeast Maluku District. Journal of Tropical the net is not quickly pursed then the fish will escape at the Fisheries, 7(1): 611 – 616. bottom of the net. [10]. Pratama M.A.D., Hapsari T.D., & Triarso I. (2016). 4 CONCLUSION Factors affecting the production of the purse seine Based on the results obtained can be concluded that the catchment unit (gardan) di fishing base ppp technical factors that affect the number of fish catches on Muncar, Banyuwangi, Jawa timur, Jurnal Saintek purse seine is net length, sinking power, vessel length, and Perikanan. 11 (2) : 120-128. pursing speed. [11]. Purwanto. & Nugroho D. (2011). The capability of ACKNOWLEDGMENT purse seine vessels and fishing effort on small The authors would like to thank Faculty of marine and fihery pelagic fisheries in the Java sea. Jakarta: in Hasanuddin University and purse seine fishermen in Research Center for Fisheries Management and Jeneponto Regency who have been willing to provide Conservation of Fish Resources. information related to this research. [12]. Rizwan., Setiawan I. & Aprilla R.M. (2011). Effectof REFERENCES production factors on purse seine fish capture in [1]. Boesono H., Setiawan D.R., Prihantoko K.E., the Lampulo coastal fishreies port Banda Aceh. Jayanto B.B., & Malala A.R. (2016). Productivity Jurnal Natural, Vol 11, No. 1. analysis of mini purse seine in PPI Pulolampes Brebes, Central Java, Indonesia. Aquatic Procedia [13]. Rumpa A. (2016). Effect of design of fishing gear 7 ( 2016 ) 112 – 117. and purse seine vessel capacity on purse seine productivity in Bone District. (Thesis). Makassar: [2]. Hosseini S.A., Chun., Lee W., Kim H.S., Lee J., & Hasanuddin University. Lee G.H. (2011). The sinking performance of the tuna purse seine gear with large meshed panel [14]. Suryana S.A., Rahardjo I.P. & Sukandar. (2013). using numerical method. Fish Sci. 77: 503-520. Influence of net length, vessel size, engine power number of crew to production on purse seine [3]. Imanda S.N., Setiyanto I. & Hapsari T.D. (2016). fishing equipment in Prigi waters of Trenggalek Analysis of the factors that influence the catch of regency of East Java. Pspk student journal, vol. I mini purse seine in the fishery port of Pekalongan. no. 1: 36-43. Journal of Fisheries Resources Utilization Management and Technology, 5: 145-153. [15]. Widagdo A., Lee C.W., & Lee J. (2015). Calculating and measuring the sinking [4]. Kefi O.S., Katiandagho E.M. & Paransa I.J. (2013). performance of small scale purse seine gear in Successful operation of the purse seine Sinar Java Indonesia to improve the gear. Fish Aquat Lestari 04 with tools that operate in the waters Sci. 18(2): 221-227. FADs Lolak North Sulawesi. Journal of Science and Technology of Capture Fisheries, 1(3): 69-75. [16]. Yusuf H.N. (2016). Technical characteristics of purse seine, its effect on catch in Pacitan East [5]. Kim H.Y., Lee C.W., Shin J.K., Kim H.S., Cha B.J. Java. (Thesis). Bogor: Bogor Agricultural & Lee G.H.(2007). Dynamic simulation of the University. behavior of purse seine gear and sea-trial verification. Fisheries Research, 88 : 109–119. [17]. Zhang X., Xu L., Song L., Zhang J. & Li, Y, 2013. Effects Of Inertial Mass Coefficient On Knotless [6]. Laissane R.F.J. (2011). Artisanal purse seine Netting Model Used In Tuna Purse Seine. . design improvements suggested for Mozambique Mechanics and Materials Vols. 256-259 (2013) pp fisheries. Mozambique : National Institute for 1980-1984. devvelopment of small scale fisheries.

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