The 1st International Conference on Education, Science, Art and Technology (the 1st ICESAT) Universitas Negeri . 22 – 23 July 2017

demand estimation of fresh sea fish with panel data model

Abd. Rahim1*, Diah Retno Dwi Hastuti1 1Study program of Development Economic, Faculty of Economic, Universitas Negeri Makassar, ,

*Corresponding e-mail : [email protected],

Abstract: The existence of seasonal change factor (arrest and famine) causes an inequilibrium between demand and supply of fresh sea fish in Indonesia. When the famine season causes the production of fish catches to decrease so that fish prices rise, while the other side of demand or consumption is relatively fixed or increased. Research conducted in Indonesia, especially South province aims to estimate the demand of fresh marine fish with selected fish species, indian mackerel, sardinella longiceps, and scads mackerel. The method used by econometric model of data panel with fixed effect method. Based on time dimension used time series data of 1991-2014 with combined data of 3 districts (Barru, Jeneponto, and Sinjai) in Province. The results of the study found that in general the price of marine fish itself positively and negatively influenced significantly to the demand of fresh sea fish in South Sulawesi. This is because of the taste and preferences of the people of South Sulawesi. Income per capita has a positive effect because of the desire to consume sea fish so that demand always increases. Regional differences have positive and negative effects on the demand for fresh sea fish both in rural and urban areas. Another case the price of chicken eggs have no significant effect. This is because of the factors of consumption behavior and consumer attitudes and culture influence in the decision of the people of South Sulawesi to buy marine fishery products

Keywords: estimation demand, fresh sea fish, and panel data

1. INTRODUCTION Organization, 2015). Although Indonesia is an Fish is one of the most important sources archipelagic country with a large coastline but of meat supply worldwide (Moses et al., 2015) fish consumption is much smaller than in Asian because it contains not only essential fatty acids countries such as Vietnam at 14.6 kg per capita and proteins but also other nutrients (Feng et al., per year, Myanmar 21 kg per capita per year, 2009) and contains omega-3 (Trondsen et al., Thailand 31.4 kg per capita per year, 2004) with low cholesterol levels compared to Phillippines 40.2 kg per capita per year and red meat and easy to digest (Herath and Cambodia 63.2 kg per capita per year (FAO, Radampola, 2016) useful to reduce the risk of 2015), United States 80 kg per capita, South some diseases (Trondsen et al., 2004), so to Korea and Hongkong respectively 85 kg per fulfill those needs, It is necessary to intake 150 capita per year, and Japan 110 Kg per capita per grams of fish to meet the needs of protein year (Vigantari et al. 2011). Community fish consumption of 50-60% for adults (Yilmaz et al consumption in South Sulawesi is 60-80 kg per 2016) making it beneficial to human health capita per year higher than the national (Busova, 2013). consumption in Indonesia which is only 46 kg Fish consumption in Indonesia reaches per capita (Hasanuddin, 2016). 12.8 kg per capita per year of 16.4% of total Consumption of fish per capita can only protein consumed. The highest consumption be maintained or enhanced if global fish supply rates range from 26.4 kg per capita per year in is relatively stable and stable (Merino et al., Maluku and the lowest to 4 kg per capita per 2012). Per capita consumption of fish in the year in Yogyakarta (FAO/Food Agriculture Asia Pacific region The highest in the Pacific

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followed by Southeast Asia, South Asia and as well as demographics and attitudes in North Asia. However, although fish decision-making buy marine fish (Ahmed et al. consumption in countries such as India and 2011). Pakistan is relatively low (2.85 and 0.6 kg per In theory, demand explains the behavior capita per year respectively) but large fish of consumers to meet their needs confronted by populations from these countries produce choice problems (Henderson and Quant, 1980; significant quantities of fish (FAO , 2015). Jogiyanto, 2004), whereas demand functions Globally, FAO said that there has been can be derived from utility functions with an increase in fishery production in the world, constraint income (Henderson and Quant, 1980 from 140 million tons in 2007 to 145 million ) or money (Jogiyanto, 2004) owned by the tons in 2009 (FAO, 2011). This product is still consumer faced by the problem of choice to the 'most traded food commodity' with a trade obtain maximum satisfaction while the value of more than 102 million dollars, up 9% consumer has the income terbtas (Henderson from 2007 (FAO, 2011; Virgantari et al. 2015). and Quant, 1980). This function is known as the The growth of total fishery production in Marshallian request function name (Jogiyanto, Indonesia during the period of 2002-2009 2004; Tasman and Aima, 2013, Rahim, 2016). continued to increase, from 5.5 million tons in The demand function is influenced by the price 2005 to 9.5 million tons in 2009. In the period itself, the price of other goods, the level of 2002-2005 growth of about 6% per year, but the income, the taste, and the population (Salvatore, 2005-2009 growth reaches about 10% per year 1996). (Virgantari et al. 2015). The production of fresh Furthermore, the findings of this model marine fish catches in Indonesia, especially are certainly different from other research South Sulawesi Province on 2011-2015 is models, such as Vigantari et.al (2011) using the 249,524 tons (Statistik Perikanan Sulawesi model of Almost Ideal Demand System (AIDS) Selatan, 2016). The high production of these and Kiziloðlu and Kizilaslan (2016) with Logit catches illustrates the large amount of fish model. Basically the purpose of fisheries supply to meet domestic consumption, but has development is among others the increase of not been utilized from the increase in fish fish consumption in line with the awareness in demand (Fauzi, 2005). improving the nutrition of the society in order to The existence of seasonal change factor improve the quality of human resources in the (arrest and famine) causes an imbalance implementation of fisheries development between demand and supply of fresh sea fish in (Keputusan Menteri Kelautan dan Perikanan South Sulawesi Indonesia. According Fauzi No.18/ Men/2002). Based on that, the purpose (2005) famine season causes the production of of this research is to estimate the demand of fish catches decreased so that the price of fish fresh sea fish with data panel model in Indonesia rose, while the other side of demand or consumption is relatively fixed or increased. Demand for fresh sea fish is the number 2. STUDY AREA of fish requested at the price and income levels South Sulawesi Province is located at 0 within a certain period (Setiadi and Irham, 2003; ° 12 '- 8 ° South Latitude and 116 ° 48' - 122 ° Abdusysyahid, 2006; Rahim, 2012). Changes in 36 'East Longitude (Biro Pusat Statistik demand for fresh fish are influenced by the price Sulawesi Selatan, 2016). South Sulawesi is of fish (Dalhatu and Ala, 2010; Vigantari et al, adjacent to West Sulawesi Province in the north 2011), income (Nayga and Capps 1995, of Toraja Utara District, Bone Bay, and Leopold et al. 2004; Vigantari et al., 2011; Southeast Sulawesi province in the east in East Moses et al., 2015 ), Price of other products , and border with Makassar Strait (Setiadi and Irham 2003; Kiziloðlu and in the west and Flores Sea in the east. In Kizilaslan, 2016), availability of fish addition, sea breeze rates of 5-20 knots and sea (Abdusysyahid, 2006), socio-economic fishing wave height between 0.75 and 2 meters with practices (Moses et al., 2015), consumer culture surface temperatures have fluctuated between (Dey et al. 2008), characteristics of behavior 26C and 32.4C (Biro Pusat Statistik Sulawesi and consumption habits (Erdogen et al., 2011), Selatan, 2016).

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Land area of approximately 45,764.53 estimate the demand of fresh sea fish in South km2 or 45,764,530 Ha inhabited by 8,032,551 Sulawesi. The types of fish studied were small people then the average population density of pelagic fish species (indian mackerel, sardinella South Sulawesi Province is as much as 176 longiceps, and scads mackerel) in each district, 2 people / km . Of the land area used for the Barru, Jeneponto, and Sinjai of South Sulawesi development of agriculture sector of 4.566 820 between 1991-2014. Testing hypothesis Ha (Biro Pusat Statistik Sulawesi Selatan, estimation of factors influencing the demand of 2016). The number of regencies / cities in South fresh sea fish at 3 (three) district of South Sulawesi is 23 districts, namely Tana Toraja, Sulawesi with multiple linear regression with North Toraja, Bone, Gowa, Luwu, Makassar, econometric model of data panel of fixed effect Bulukumba, Maros, Jeneponto, Pangkep, method as follows: Pinrang, Bantaeng, Enrekang, Wajo, Takalar, β1 β2 QdKmbngit = β0 PKmbngit PLmrit Luwu Utara, Sinjai, Sidrap , Selayar, Soppeng, β3 β4 β5 PLyngit PTAit IPkptit Barru, , and Pare-Pare (Biro Pusat δ1 δ2 μ1it DmWPKBi DWPKJi (1) Statistik Sulawesi Selatan, 2016). The study β7 β8 β9 QdLmrit = β6 PLmrit PLyngit PKmbngit area consists of 3 districts directly adjacent to β10 β11 δ3 PTAit IPkptit DmWPKBi the West Coast Coastal Area or Makassar Strait δ4 μ2it DWPKJi (2) waters, namely , South coast or β13 β14 QdLyngit = β11 β12 PLyngit PLmrit Flores Sea, namely Jeneponto Regency, and east β15 β16 β17 PKmbngit PTAit IPkptit coast or Bone Bay of Sinjai District (Figure 1). δ5 δ6 μ3it DmWPKBi DWPKJi (3) To facilitate the calculation of equation models (1), (2) and (3) then the equation is converted into multiple linear with double log or natural logarithm (Ln) method as follows: LnQdKmbngit = β0 + β1 LnPKmbngit + β2 LnPLmrit + β3 LnPLyngit + β4 LnPTAit + β5 LnIPkptit + δ1 DmWPKBi + δ2DWPKJi + μ1it (4) LnQdLmrit = β6 + β7 LnPLmrit + β8 LnPLyngit + β9 LnPKmbngit + β10 LnPTAit + β11 LnIPkptit + δ3 DmWPKBi + δ4DWPKJi + μ2it (5) LnQdLyngit = β12 + β13 LnPLyngit + β14 LnPLmrit + β15 LnPKmbngit + β16 LnPTAit + β17 LnIPkptit + δ5 DmWPKBi + δ6DWPKJi + μ3it (6) Where : QdKmbng: indian mackerel demand, year-t (kg) QdLmr : sardinella longiceps demand, year-t (kg) QdLyng: scads mackerel demand in, year t (kg) β0, β6, and β12 : intercept Figure. 1. Case Study Area: South Sulawesi β1, ..., β5, β7, ..., β11, and β13, ..., β17,: the Province, Indonesia independent variable regression coefficient δ1, ..., δ6 : regression coefficient of dummy 3. Material and Method variables The type of research used is explanatory PKmbng : the price of real indian mackerel, method (Singarimbun and Efendi, 1989) used to year-t (Rp)

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PLmr : the price of real sardinella longiceps, Tests on individual (partial) regression year -t (Rp) coefficients t-test was used with a certain Plyng : the price of reall scads mackerel, confidence level. According to Greene (1990) year-t (Rp) and Gujarati and Porter (2009) with the formula: 훽푖 PTA : the price of chicken eggs, year-t (Rp) 푡 ℎ𝑖푡푢푛𝑔 = Ipkpt : income per capita, year-t (Rp) 푆훽푖 DmWPKB: 1, for dummy of Barru District; and (7) 0, for others 푡 푡푎푏푒푙 [(푛 − 푘); 훼/2] (8) DmWPKJ: 1, for dummy of Jeneponto District; i : regression coefficient of to-i and 0, for others Si : standard error of regression coefficients μ1, ..., μ3 : error disturbance to-i t : time series (year) By hypothesis: i : cross-section (district difference) H0 : i = 0, meaning that there is no influence Furthermore, the equation model of independent variables to-i are partial specifications (1), (2) and (3) are equipped with on the dependent variable the measurement of model accuracy (adjusted H1 : i  0, meaning that there are significant R2) and hypothesis testing (F-test and t-test). independent variable to-i individual the Measurement The appropriateness or suitability dependent variable of the model (goodness of fit) is calculated by adjusted R2. According to Gujarati (1978) and 4. Result Gujarati and Porter (2009) formulated as The measurement of model accuracy or follows: the suitability of the model (goodness of fit) of (n−1) adjusted value R2 (Gujarati, 1978; Gujarati and Adjusted R2 = 1 − (1 − R2) (4) (k−1) Porter, 2009) shows independent variables on the demand function model of fresh sea fish in where : the form of indian mackerel, sardinella Adjusted R2 : coefficient of determination longiceps, and scads mackerel at the consumer adjusted level presented each (93.6%), and 81.6% of the k : the number of variables not included variation for the demand of fresh sea fish in intercept South Sulawesi while the remaining amounted n : number of samples to 6.5%, 19.4% and 18.4% Influenced by other Testing the hypothesis of the regression variables not included in the model (Table 1). coefficient is simultaneous with the F-test Furthermore, F-test results (Greene, certain level of confidence, which, according to 1990, Gujarati and Porter, 2009) are Greene (1990) and Gujarati and Porter (2009) respectively 110,144; 32.501; and 34,540 defined as follows indicate that the factors influencing the demand 퐸푆푆/(푘−1) 퐹 ℎ𝑖푡푢푛𝑔 = (5) of fresh sea fish in South Sulawesi significantly 푅푆푆/(푛−푘) influence the error rate of 1% or 99% confidence level (Table 1). Furthermore, 퐹 푡푎푏푒푙 [(푘 − 1): (푛 − 푘); 훼] (6) individual influence based on t-test (Greene, 1990, Gujarati and Porter, 2009) from each where: independent variable to the production of catch  : level of significance or specification error in marine waters of South Sulawesi using By hypothesis : regression coefficient value. H0 : 1 = 2 =... = n = 0, meaning that there is Based on the result of regression analysis no influence of independent variables (Table 1), the value of multiple linear regression to-i simultaneous on the dependent equation which is raised with econometric variable model of data panel of fixed effect method H1 : at least one of independent variables  0, follows: meaning that there is the influence of LnQdKmbngit = 3.507 + 0.819 LnPKmbngit

the independent variables to-i together + 0.009 LnPLmrit - 0.111 LnPLyngit

on the dependent variable + 0.017 LnPTAit - 0.010 LnIPkptit +

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0.706 DmWPKBi + 0.889DWPKJi + the South Sulawesi consumer market at 1% μ1it (9) error rate or 99% confidence, meaning that any LnQdLmrit = 6.468 - 0.044 LnPLmrit + increase of indian mackerel price of Rp 1 will

0,081 LnPLyngit + 0.352 LnPKmbngit increase the indian mackerel demand by 0.819 + 0.166 LnPTAit + 0.170 LnIPkptit - kg. This is not in accordance with the negative

0.620 DmWPKBi + 0.010 DWPKJi + sign of hope because the people of South μ2it (10) Sulawesi in this district of Barru, Jeneponto, and LnQdLyngit = -3.523 - 0.888 LnPLyngit - Sinjai have tastes and preferences of the fish so 0.329 LnPLmrit + 0.409 LnPKmbngit that despite the increase in fish prices can still

+ 0.219 LnPTAit + 0.686 LnIPkptit + buy the commodity. It is also proven that the 0.166 DmWPKBi - 0.188 DWPKJi + price of sardinella longiceps and kite did not μ3it (11) affect the scads mackerel demand in South From equation (9), (10) and (11) then the Sulawesi consumer market equation is changed again in the form of power This result is different from the findings function by anti-Ln as follows: of Setiadi and Irham (2003) that the demand of 0.819 0.009 QdKmbngit= 33.348 PKmbngit PLmrit tuna is negatively influenced by the price of -0.111 0.017 -0.010 PLyngit PTAit IPkptit mackerel tuna itself and positively by the price 0.706 0.889 μ1it DmWPKBi DWPKJi (12) of catfish in Jogjakarta Special Region. Dalhatu -0.044 0.081 QdLmrit = 644.194 PLmrit PLyngit and Ala (2010) finds that prices negatively 0.352 0.166 0,170 PKmbngit PTAit IPkptit affect fish demand in Nigeria, while the findings -0.620 0.010 μ2it DmWPKBi DWPKJi (13) of Vigantari et.al (2011) using the model of -0.888 -0.329 QdLyngit = 0.029 PLyngit PLmrit Almost Ideal Demand System (AIDS) that fish 0.409 0.219 0.686 PKmbngit PTAit IPkptit prices negatively affect the demand for fish 0.166 - 0.188 μ3it DmWPKBi DWPKJi (14) (catch and Cultivation) in Indonesia such as the Table 1. Demand Estimation of Fresh Sea Fish islands of Sulawesi, Maluku, and Java. Another with Panel Data Model in South finding of Kiziloðlu and Kizilaslan (2016) with Sulawesi, Indonesia the Logit model that fish prices have a positive Indpendent Indian Sardinella Scads effect on fish consumption in Erzurum, Turkey. Variable ES mackerel longiceps mackerel Another case of sardinella longiceps Coef. () Coef. () Coef. () demand is scads mackerel positively influenced PKmbng - 0.819*** -0.044ns -0.888*** by the overpass price at a 5% error rate (95% PLmr - 0.009 ns 0.081 ns -0.329** confidence). This means that each increase in PLyng - -0.111 ns 0.352** 0.409*** price of Rp 1 the sardinella longiceps demand

ns ns ns also increased by 0.532 kg. This happens PTA - 0.017 0.166 0.219 because the kite as a substitute commodity is Ipkt + -0.010 ns 0.170* 0.686 ns very popular by the people of South Sulawesi. DWPKB + 0.706*** -0.620* 0.166*** Furthermore, the demand for kites in the DWKJt + 0.889*** 0.010 ns -0.188*** consumer market is positively influenced by the price of the fly over itself at a 1% error rate Intercep 3.507*** 6.468*** 3.523*** (99% confidence). According to Herath and F-test 110.144*** 32.501*** 34.540*** Adjusted R2 0.935 0.806 0.816 Radampola (2016) that lower prices are the n 54 54 54 factors that govern for fish consumption in Sri *** is a level error significance of 1 % (0,01), or Lanka confidence level of 99 %. ** is a level error significance of Furthermore the negative effect of the 5 % (0,05), or confidence level 95 %. * is a level error rill price of indian mackerel at the error rate of significance of 10 % (0,10), or confidence level 95 %. ns 1% and the price of sardinella longiceps at the is not significant. ES is an expectation sign error rate of 5%. This means that each price increase of indian mackerel and sardinella 5. Disscusion longiceps amounting to Rp 1 then the demand In the indian mackerel fish demand for flyovers also decreased by 0.888 kg and function, the price variables of bloated fish itself 0.329 kg respectively. This happens because of have a positive effect on the bloated demand in the influence of people's purchasing power in

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South Sulawesi on the change of fish price (if consumer culture in Asia (Dey et.al. 2008), the price of fresh marine fish increases, it will while consumer behavior and consumption switch to cheaper price of fresh sea fish). habits Seafood is an important factor These findings differ in Turkey that influencing the development of the seafood despite rising prices of substitute commodities sector in many countries (Erdoğan et.al. 2011). such as red meat and chicken meat demand for Further, this finding is certainly different fish increases (Kiziloðlu and Kizilaslan, 2016), from the findings of Setiadi and Irham (2003) whereas in Poland, prices are a factor that that per capita income does not affect the determines their choice compared to nutritional demand of mackerel tuna in Jogjakarta, but value and Health effects (Lebiedzinska et.al. these findings are in line with the findings of 2006). Nayga and Capps (1995) in the United States, At the price of chicken eggs as Dey et. al. (2008) in Asia, Dalhatu and Ala commodity substitution of fresh sea fish (2010) in Nigeria, and Kiziloðlu and Kizilaslan commodity has no significant effect on the (2016) in Turkey that income has a positive demand of indian mackerel, sardinella effect on fish consumption. According to Moses longiceps, and scads mackerel. This happens in et. al. (2015) that preferences and perceptions the field that although there is a good price are an essential element of demand theory but increase during the famine season then the most economic analyzes for market demand are people of South Sulawesi in this case people based on price and income. Barru district, Jeneponto, and Sinjai still choose Dummy regional differences (Barru the sea fish. These results are in line with the regency and Jeneponto) have a significant findings of Setiadi and Irham (2003) in positive effect on the 1% error rate on indian Jogjakarta that the price of chicken eggs does mackerel demand in the consumer market. This not affect the demand of mackerel tuna. has been in line with the positive sign of hope, South Sulawesi's income per capita sardinella longiceps demand in the District of (Barru, Jeneponto, and Sinjai districts) Barru is greater than other districts (Jeneponto). positively affected the 10% (confidence 90%) Similarly, if compared between Jeneponto and error rate on indian mackerel demand in the Sinjai. The demand for sardinella longiceps fish consumer market. This is in line with a positive in Jeneponto Regency is greater than that of expectation sign, which means that every Sinjai District. increase in per capita income of the people of Another case in sardinella longiceps South Sulawesi of Rp 1 will increase demand demand in the consumer market is negatively for indian mackerel by 0.170 kg. This happens affected at a 10% error rate. This does not match because the price of indian mackerel the negative expectation mark. This means that commodity is higher than the commodities of demand for sardinella longiceps in Barru indian mackerel and scads mackerel. In District smaller than Jeneponto district. addition, the factors of taste and preference that Furthermore, the scads mackerel request is determine the people of South Sulawesi choose affected positively and negatively at a 1% error the fish (indian mackerel). This result is in line rate. In the area of Barru District, the overpass with what Onurlubas (2013) finds about fish demand is greater than Jeneponto Regency. This consumption habits or preferences in finding is in line with Vigantari et.al. (2011) that Impression Township Endirne Turkey. differences in rural-urban areas are influencing Consumer behavior and attitudes are fish demand in Indonesia with AIDS models, as important factors in making decisions to well as fish demand in Turkey (Aydin et al. purchase fishery products based on 2011). demographic status (Ahmed et al. 2011; Kessuvan et al. 2015) and attitudes as do 6. Conclussion households in Kuala Lumpur Malaysia (Ahmed Based on the results of the research, it is et.al. , 2011) and socioeconomic conditions, found that in general the price of sea fish itself such as consumer preferences on fish purchases positively and negatively affect the demand of in North Yola of the local government of fresh sea fish in South Sulawesi. Negative Adamawa country (Moses et al. 2015) and influence is the price of indian mackerel and

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sardinella longiceps to the scads mackerel 3(1):36-43. demand, whereas the positive is the price of the https://agribisnisfpumjurnal.files.wordpr scads mackerel itself against the scads mackerel ess.com/2012/03/jurnal-vol-3-no-1- request. This is because the taste and said.pdf preferences of Indonesian people, especially in Ahmed AF, Mohamed Z, Ismail M.M. (2011). South Sulawesi. Determinants of Fresh Fish Purchasing Income per capita has a positive effect on Behavior Among Malaysian Consumers. the demand of fresh sea fish due to the Current Research Journal of Social consumption of sea fish so the demand always Sciences. 3(2): 126-131. increases. Regional differences have positive http://ikdpm.upm.edu.my/intranet/ru/eC and negative effects on the demand of fresh opy/7.NCJIJ- marine fish, meaning that the different areas of Determinants%20of%20Fresh%20Fish both villages and cities affect the demand for sea %20Purchasing%20Behavior%20Amon fish in South Sulawesi. g%20Malaysian%20Consumers.pdf Another case the price of eggs does not Aydin H, Mehmet, Kamil, Dilek MK, Aydin significantly affect the demand for fresh marine K. (2011). Trends in Fish and Fishery fish. This is because of the factors of Products Consumption in Turkey. consumption behavior and consumer attitudes Turkish Journal of Fisheries and Aquatic and culture influence in the decision of the Sciences. 11: 499-506 people of South Sulawesi to buy marine fishery http://akademikpersonel.kocaeli.edu.tr/a products. ydin/sci/aydin13.10.2011_10.45.43sci.p In order to increase the production of df catches to meet the demand for fresh sea fish Biro Pusat Statistik Provinsi Sulawesi Selatan. consumption in Indonesia, especially in South (2015).“Sulawesi Selatan dalam Angka”. Sulawesi province, it is necessary to support Provinsi Sulawesi Selatan government or stockholder in the form of http://sulsel.bps.go.id/website/pdf_publi increase of Grosstonase (GT) powered fleet, kasi/Statistik-Daerah-Provinsi-Sulawesi- such as 50 - 100 GT to reach fishing ground in Selatan-2015.pdf Zone Economic Exclusive (ZEE), such as 6 sd 12 miles away. This has been referring to the Busova M. (2013). Factors Affecting the 2010 government program through the ministry Quality and Consumption of Fish Meat. of marine and fisheries, the blue revolution as a Indian Journal of Applied Research. grand strategy in implementing the restructuring 3(9):24-27 of the national fleet to increase the production https://www.worldwidejournals.com/ind of catches. ian-journal-of-applied-research- (IJAR)/file.php?val=September_2013_1 7. Acknowledgments 493042664__07.pdf We would like to thank the Postgraduate Program of Universitas Negeri Makassar for Dalhatu M, Ala A.L. (2010). Analysis of Fish the support of this research. We would also like Demand in Sokoto Metropolis, Sokoto, to thank the Development Economics Study Nigeria. Nigerian Journal of Basic and Program, the Faculty of Economics and Applied Science . 18(2): 154-159 Research Institute of Universitas Negeri http://ajol.info/index.php/njbas/index Makassar, the Department of Marine and Dey MM., Garcia YT, Kumar P, Piumsombun Fisheries of South Sulawesi and the S, Haque MS, Li L, Radam A, Senaratne Government of South Sulawesi in collecting this A, Khiem NT, Koeshendrajana S. research data. (2008). Demand for fish in Asia: a cross- country analysis. The Australian Journal Reference of Agricultural and Resource Economics. Abdusysyahid S. (2006). Analisa Fluktuasi 52 : 321–338 Permintaan Ikan Laut Pada Beberapa http://ageconsearch.umn.edu/bitstream/1 Rumah Makan di Kota Samarinda. EPP. 18546/2/j.1467-8489.2008.00418.x.pdf

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