Ijciet 10 01_065

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 01, January 2019, pp. 715-723, Article ID: IJCIET_10_01_065
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=01
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication Scopus Indexed
VARIABILITY OF CHLOROFIL-A AND SEA
SURFACE TEMPERATURE, THE EFFECT ON
THE CATCHES OF CAKALANG FISH IN SAWU
SEA OF EAST NUSA TENGGARA
Marius Agustinus Welliken K and Edy H.P Melmambessy
Universitas Musamus, Merauke, Indonesia
Jumsar
Universitas Diponegoro, Semarang, Indonesia
ABSTRACT
Information about the variability of chlorophyll-a and sea surface temperature is a
reference to determine the potential fishing area (fishing ground). This study aims to
determine the variation of chlorophyll-a and sea surface temperature effects on
Cakalang (Katsuwonus Pelamis) fish catches in the waters of Sawu sea, East Nusa
Tenggara. Predictions of potential areas of skipjack capture are determined based on
statistical analysis and multitemporal analysis. The results showed that variations in
chlorophyll-a and sea surface temperature were very influential with the catches of
Cakalang in the waters of Sawu. Chlorophyll-a increases in the East season (June-
August) and at the beginning of Transition II (September), so this season has the
potential to catch Cakalang fish.
Keywords: Chlorophyll-a, sea surface temperature, Cakalang fish, Sawu sea
Cite this Article: Marius Agustinus Welliken K, Edy H.P Melmambessy and Jumsar,
Variability of Chlorofil-a and Sea Surface Temperature, the Effect on the Catches of
Cakalang Fish in Sawu Sea of East Nusa Tenggara. International Journal of Civil
Engineering and Technology, 10(01), 2019, pp. 715–723
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=01
1. INTRODUCTION
The Savu Sea waters are in the small Sunda region, which is in the Province of East Nusa
Tenggara (NTT) which has an area of 3.5 million hectares. This waters has a strategic role for
the development of NTT, because almost a part of the Regency / City is very dependent on the
Savu Sea. Especially in the field of fisheries more than 65% of the sustainable potential of fish
resources in this province is contributed by the Savu Sea. The sustainable potential of pelagic

Variability of Chlorofil-a and Sea Surface Temperature, the Effect on the Catches of Cakalang
Fish in Sawu Sea of East Nusa Tenggara
fish in the Savu Sea is 156,000 tons / year (KEPMEN-KP Number 6 of 2014). This shows that
the potential of fish in the waters needs to be utilized optimally by operating fishing gear
effectively and efficiently.
According to Syamsuddin et al. (2008), the level of exploitation of fish resources in Kupang
has not reached optimal conditions. In this connection, efforts need to be made in the form of
adding fishing operations, fishing gear units and searching for new fishing areas by utilizing
fish detection devices (echosounder and remote sensing).
Fishing operations by East Nusa Tenggara fishermen are generally still dependent on
information from fellow fishermen and their own experience by utilizing the five senses to
predict fishing grounds. While the availability of fish resources in a waters region always
changes along with changes in the environment.
In addition to optimizing the use of fishing gear in fishing activities, information on
environmental conditions is also needed in the form of oceanographic parameters.
Oceanographic parameters include chlorophyll-a and sea surface temperature (SPL). By
knowing the environmental conditions, especially chlorophyll-a and optimum sea surface
temperature of a fish species in a waters, of course it will facilitate fishermen in predicting
potential fishing areas. Sea surface temperature is closely related to the suitability of
physiological conditions and morphological adaptation of fish. Besides that sea surface
temperature becomes an indirect indicator of biological productivity or the presence of fish
food (Santos, 2000). Whereas chlorophyll-a is a factor that can provide a direct indication of
the existence of fish food and the pathways of fish migration areas (Polovina et al., 2011).
Some results of research conducted in Indonesian waters indicate that oceanographic
parameters such as temperature, salinity, chlorophyll-a concentration, upwelling, eddies are
related to fish existence (Mukhlis et al., 2009; Mugo, 2010; Zainuddin et al., 2015) . According
to Gaol (2010) it is more assertive that information about oceanographic parameters and
dynamics is an absolute necessity for forecasting potential fishing areas.
One alternative that can be used to obtain environmental conditions in the form of
oceanographic parameters is to utilize GIS capabilities and marine sensing. Ocean senses are
able to provide data on the scale of globa on the surface layer of the water. Data from the results
of oceanographic satellite shooting can be used to monitor various marine phenomena such as
upwelling, eddy, fronts and altimetry which are closely related to fisheries activities (Kotta et
al., 2018; Padmaningrat et al., 2017). One sensory satellite equipped with a sensor that can
detect chlorophyll-a and SPL content is the Aqua Moderate Resolution Imaging
spectroradiomete (Aqua MODIS) satellite.
Based on the description above, it is necessary to do research on the variability of
chlorophyll-a and sea surface temperature spatially and temporally as a basis for determining
fishing areas in the waters of Sawu sea. The purpose of this study is to determine the variability
of chlorophyll-a and sea surface temperature and the factors that influence it.
2. METHODOLOGY
This research was conducted in January - December 2017 in the Savu Sea Waters of East Nusa
Tenggara. The waters of the Savu Sea lie in a geographical position 118o
54'54,44" –
124o
23'17,089" E and 8o
45'49,964"–11o
09'43,919" S.

Marius Agustinus Welliken K, Edy H.P Melmambessy and Jumsar
Figure 1. Research Location Map
The material used is the data of chlorophyll-a, sea surface temperature of Aqua MODIS
images for 15 years from 2003-2017 and Cakalang catch data in the form of results and catch
coordinates for 1 year from January to December 2017 obtained from lookbook for catching
Cakalang at UPT Port NTT Province Fisheries. The tools used and their uses can be seen in
table 1 below.
Table 1. Tools and functions
No Tools Functions
1
Computer with an Intel Pentium
processor
To carry out the entire process of data
and research reports
2 Software winSCP To download MODIS image data
3 Programming Software
For processing data of Chlorophyll-a,
sea surface temperature, and Fish
4 Microsoft Excel dan SPSS 17
For correlation analysis and statistical
data regression
5 ArcMap 10.2 For a Spatial Map layout
Regression analysis is used to determine the effect of independent variables with dependent
variables. According to Padmaningrat et al. (2017) regression analysis method can be used to
see linear regression and correlation analysis to find out how much the relationship between
oceanographic parameters (sea surface temperature and chlorophyll-a) to the number of fish
catches. Regression analysis according to Bender et al. (2014) can be expressed in equation 1,
i.e.:
Y = a0 + a1x + a2x2
(1)
Where:

Y = CPUE the results of the capture of Cakalang
a = constant
X = Oceanographic parameters (chlorophyll-a and sea surface temperature).
A perfect linear relationship occurs between x and y if the value r = +1 or -1. If the value
of r approaches this value, there is a high correlation between the two variables, whereas if the
value of r approaches zero, the linear relationship between the values of x and y is very weak.
Correlation analysis aims to measure the strength or closeness of the relationship between two
variables (Bender et al., 2014). According to Bender et al. (2014) correlation analysis can be
expressed in equation 2, i.e.:
(2)
Where:
= correlation coefficient value
= amount of catch data
= the amount of Cakalang's catch
= Oceanographic parameters (sea surface temperature and chlorophyll-a)
According to De Vaus (2001), to interpret the results of correlation studies are presented in
Table 2.
Table 2. Interpretation of correlation coefficients
Correlation coefficient (r) Interpretation
0.75 – 0.99
0.5 – 0.75
0.25 – 0.5
0.0 – 0.25
0
Correlation is very strong
Strong correlation
Correlation is quite strong
Correlation is very weak
No correlation
Other useful methods were provided (Djamali et al., 2018; Mangkoedihardjo, 2010;
Nurcholis and Muchlis, 2018; Suryaningsih et al., 2018; Untari and Mekiuw, 2018; Waremra
and Bahri, 2018).
3. RESULTS
Catching Cakalang fish in the waters of the Savu sea is one day fishing. Cakalang fishing
activities in Sawu sea waters during the period of January - December 2017 are divided into 4
seasons namely the West season, Transition I season, East season and Transition II season.
Based on data from look book pole and line capture of Cakalang fish obtained by catch data
during the period January - December 2017 as many as 193 fishing trips with a total production
of 579,217 kg, of which in the West season as many as 11 trips with catches reached 22,028
kg, in the Transition I season 53 trip with the catch of 127,038 kg, the East season 14 trips with
the catch of 70,225 kg and the transition season II as many as 114 trips with the results of
359,926 kg. Cakalang fish production during the period of January - December 2017 can be
seen in Figure 2.

Figure 2. Chart of Cakalang Fish Production for January - December 2017 Period
3.1. RELATIONSHIP BETWEEN CHLOROPHYLL-A PARAMETERS AND SEA
SURFACE TEMPERATURE AGAINST CAKALANG CATCHES
The relationship of the chlorophyll-a pathameter and sea surface temperature to Cakalang's
monthly CPUE can be seen in Figure 3.
Figure 3. Graph of relationship between Chlorophyll-a and sea surface temperature to Cakalang
monthly CPUE
Figure 3 shows CPUE tends to start increasing in June and peaked in August and then began
to decline again in September. This indicates that the increase in chlorophyll-a and cooling of
sea surface temperature has a very strong relationship to the CPUE of Cakalang catches in the
waters of Sawu sea, in August the sea surface temperature cooled to reach a low value of 27
oC causing an increase in chlorophyll-a concentration reaching 0.5 mg / m3 and followed by a
high CPUE catch of 6,330 kg. Zainuddin et al. (2013) High CPUE of skipjack fish from April
to June to the east following a periodic increase in chlorophyll-a concentration in the eastern
part of Bone Bay. It is strongly suspected that the food of skipjack fish increases along with

the development of concentrations of chlorophyll-a and is then followed by a high cluster of
gathered tuna. Thus a potential zone of catching skipjack fish will be created.
The relationship between chlorophyll-a parameters and sea surface temperature on
Cakalang catches was analyzed using multiple regression with catch as dependent variable,
chlorophyll-a and SPL as independent variables.
Analysis of variance (Test F) was used to see the relationship of chlorophyll-a and sea
surface temperature together to the catches of Cakalang fish, the results of the analysis can be
seen in table 1 (b). Table 1 (b) shows that the significant value obtained is 0,000 less than (0.05)
with Fcount = 57,789 (> Ftable = 3.12), this shows together that chlorophyll-a and sea surface
temperature have a significant effect on Cakalang catches.
Table 1(a). Model Summaryb
Model R R Square Adjusted R Square
Std. Error of the
Estimate
Durbin-Watson
1 .783a
.613 .602 1713.40615 1.083
a. Predictors: (Constant), Chlorophyll-a, Sea Surface Temperature
b. Dependent Variable: Catch Katsuwonus pelamis
Table 1(b) ANOVAb
Model Sum of Squares Df Mean Square F Sig.
1
Regression 3.393E8 2 1.697E8 57.789 .000a
Residual 2.143E8 73 2935760.644
Total 5.536E8 75
a. Predictors: (Constant), Chlorophyll-a, Sea Surface Temperature
b. Dependent Variable: Catch Katsuwonus pelamis
Correlation coefficient value is used to determine the magnitude of the influence of
independent variables on the dependent variable, table 1 (a) shows the correlation coefficient
(R) of 0.783, this means that the relationship between chlorophyll-a and sea surface
temperature to Cakalang fish catches is 78%. The detrmination coefficient (R2) is 0.613,
meaning that 63% of the effect of the catch is influenced by chlorophyll-a and sea surface
temperature while 37% is influenced by other factors.
The results of the analysis using regression analysis can be used to see the magnitude of
the influence of chlorophyll-a and sea surface temperature on Cakalang catches, in the analysis
all data from chlorophyll-a converts, sea and fish surface temperatures, data generated in
converts to 80 data for chlorophyll-a and 125 data for sea surface temperature. The results of
the regression analysis showed a relationship between chlorophyll-a and Cakalang catch
(Figure 4), with a coefficient of determination (R2) 0.686, which means that 68% of the catches
of Cakalang are affected by chlorphyl-a. The trendline line (Figure 4) shows an increase in
chlorophyll-a concentration followed by an increase in the number of catches of Cakalang,
catches of Cakalang in Sawu sea water increase when the chlorophyll-a condition reaches 0.92
mg / m3 and decreases in chlorofi-a 0.16 mg / m3.

Figure 4. Relationship of chlorophyll-a to catch
The relationship of sea surface temperature to Cakalang catches can be seen in (Figure 5),
with a coefficient of 0.486 which means that the effect given by sea surface temperature on
Cakalang catches is 48% smaller than chlorophyll-a. Sriawan (2002) explains that sea surface
temperature does not have too much influence on the catches of Cakalang in the waters of the
Savu Sea. Sawu sea water from Cakalang catch tends to increase at a temperature of 26o
C and
decreases at a temperature of 30.28o
C.
Figure 5. Relationship of sea surface temperature to Cakalang catches
3.2. Potential Area Predictions Catching Cakalang
The results of data analysis using indicate a very strong relationship between oceanographic
parameters, especially chlorophyll-a, where the higher the concentration of chlorophyll-a the
higher the catch of Cakalang, while for the sea surface temperature the lower the variation in
sea surface temperature the higher the catch Cakalang, thus predicting the potential area of
Cakalang catch is determined based on areas that have high chlorophyll-a concentrations and
cold sea surface temperatures. In the waters of the Savu Sea based on the results of 15 years of
image processing for the period 2003-2017, it was found that there were quite high areas of
chlorophyll-a conduction and colder sea surface temperatures in the East (June-August) and
early Transition II (September) . The area is presented in Figure 6.
y = 307.46x2 - 19129x + 299179
R² = 0.4869
0
2000
4000
6000
8000
10000
12000
14000
25 26 27 28 29 30 31 32 33
CPUE(Katsuwonuspelamis)
Sea Surface Temperature (SST) 0C

Figure 6. Potential and temporal potential areas for Cakalang capture.
4. CONCLUSION
Based on the results of data analysis, the variation of chlorophyll-a and SPL is very influential
with the catches of Cakalang in the waters of the sea of Sawu. And based on the results of
image processing for 15 years, the period 2002-2017 shows that chlorophyll-a construction
increases in the East season (June-August) and at the beginning of Transition II (September),
thus this season has the potential to catch Cakalang Fish.
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