The Effect of Credit Access on Food Security of Small Fishermen in East Java
Asfi Manzilati1*, Yenny Kornita Sari1, Suprayogi2, Anthon Efani3
1Department of Economics, Faculty of Economics and Business, Brawijaya University
2Faculty of Agricultural Technology, Brawijaya University
3Department of Socio-Economic, Faculty of Fisheries and Marine Science, Universitas Brawijaya Received: 21 November 2022; Revised: 25 May 2023; Accepted: 12 July 2023
ABSTRACT
The development of access to credit in various developing countries has increased. Some of these studies show a positive and significant impact on the productivity of rural communities. Although several previous studies have proven the importance of credit in increasing the productivity of rural communities. The purpose of this study was to examine the effect of access to credit on the food security of small fishermen in East Java. Yet, the data was analysis using an ordinary least square (OLS) and an ordered probit model.
The results of this study show that fishermen's food security is included in the borderline category. In this sense, the majority of small-scale fishing communities are classified as having moderate food security but cannot be said to be safe. Therefore efforts are still needed to improve the food security of small-scale fishing communities in East Java. Other findings show that credit, education, ship size, Fisherman groups and the number of fishing gears have a significant influence on the food expenditure of small-scale fishing communities in East Java. Meanwhile credit, education, multigear adoption and trip length have a significant effect on fishermen's food security. Therefore, to support food security, it is necessary to increase access to credit, increase education levels, ship size, join fishermen groups, so that the number of catches and the length of fishing trips will increase which will have an impact on increasing income, in the end food security will be achieved.
Keywords: little fisherman; access to credit; food safety; FIES How to cite:
Manzilati, A., Sari, Y. K., Suprayogi, & Efani, A. (2023). The Effect of Credit Access on Food Security of
Small Fishermen in East Java. HABITAT, 34(2), 132–140.
https://doi.org/10.21776/ub.habitat.2023.034.2.12 1. Introduction
So far, a number of international studies have emphasized the importance of access to credit services which are considered capable of reducing the poverty line for people with low incomes. For example (Rahman et al., 2023) revealed that credit is an important instrument for reducing poverty, because it is able to help rural communities; just as fishermen buy various factors of production (fuel, supplies and labor) so as to increase their productivity. However, participation in credit in rural areas, especially in coastal communities, is still low.
The development of access to credit in various developing countries has increased. In Asian countries more than 515 million households
have access to credit (The World Bank, 2018).
Furthermore (Beck et al., 2009) explained, that in African countries, only 20 percent of households have access to credit. In coastal communities, low access to credit has an impact on decreasing fishery production (Guerrieri et al., 2020). The lack of access to credit is considered as one of the important reasons why coastal communities in developing countries continue to live below the poverty line (Collins, 2018). Therefore, coastal communities, especially fishermen, are an interesting topic for researchers and policy makers, so that they can help coastal communities get out of the dynamics of poverty.
Several previous studies have proven the role of credit in rural communities. On the other hand, the allocation of credit to small fishermen is considered a challenge by financial institutions (Rahman et al., 2022). This is because the fisheries sector is considered a high-risk investment because it is very vulnerable to failures such as
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*Corresponding Author.
E-mail: asfi@ub.ac.id
Available online at HABITAT website: http://www.habitat.ub.ac.id weather and uncertain catches (Rahman, 2017).
Furthermore, (Nordjo & Adjasi, 2020)revealed that limited access to credit was due to imperfect financial markets caused by imperfect information.
Several previous studies related to the impact of access to credit on the productivity of rural communities have been carried out and the results obtained have varied. Some of these studies show a positive and significant impact on the productivity of rural communities (Chisasa &
Makina, 2013); (Wicaksono, 2014). In other words, with access to credit fishermen are able to increase productivity because they are able to meet input needs in their production activities.
However, several studies have also found that rural communities have limitations in accessing credit, such as loan values that do not match the value proposed, requirements that are quite complicated, and imperfect information regarding credit (Reyes et al., 2012). The results of some of these studies show how important credit is for reducing poverty in rural areas and the limitations that prevent rural communities from participating in credit.
Although several previous studies have proven the importance of credit in increasing the productivity of rural communities (Ayaz &
Hussain, 2011); (Chisasa & Makina, 2013);
(Mendonça & Pereira, 2014). However, research on the impact of credit on food security in coastal communities is yet to be found. To fill the gap.
The main objective of this research is to examine access to credit in coastal communities and its impact on the food security of small fishermen.
2. Theoretical Underpinning
Credit is a basic need in various sectors;
including the fisheries sector for the sustainability of their production activities. For the modernization and commercialization of the fisheries sector, credit has a very important role (Saleem & Jan, 2018). Credit in the fisheries sector is able to provide the input needs of fishermen to carry out fishing activities. In developed countries, credit has been able to provide technological transformation in a more advanced direction, for example, America and China (Zulfiqar et al., 2021). The availability of credit services makes fishermen more eligible to increase their productivity so that it becomes natural that the existence of credit is required to improve the welfare of the fishing community.
National food security can be interpreted as independence in food supply (Kuwornu et al., 2013). According to the Life Science Research Organization (LSRO) food security is the availability of access where all people at all times get enough food for an active and healthy life and at a minimum includes: a) availability of food that is safe and nutritionally adequate, and b) ensuring the ability to obtain socially acceptable food (for example: without using emergency food supplies, scavenging, stealing, and other coping strategies).
Conversely, food insecurity is the limited or uncertain availability of adequate and safe nutritious food or the ability to obtain food in a socially acceptable manner (Saleem & Jan, 2018).
The concept of food insecurity as thought in the United States includes not only lack of availability, access, and utilization or use of food (e.g., food preparation and distribution of food within the household), but also perceptions (e.g., that food is not enough, not enough , unacceptable, uncertain, or unsustainable) (Ma & Abdulai, 2016).
Several previous studies have investigated the impact of credit on farmers' income, food security and technical efficiency levels. For example (Reyes et al., 2012),agricultural credit has a significant impact on farmer income, food security, rural development and production scale.
According to ,(Barrett, 2000) a large number of farmers in developing countries have to sell some of their crops to be able to raise funds to meet their cash needs. As a consequence of this phenomenon repeating every year, many agricultural households are trapped in poverty.
Access to credit also plays a central role in increasing the technical efficiency of farmers (Ayaz & Hussain, 2011), where technical efficiency is one of the determinants of welfare. In this regard, rural community finance has played an important role in increasing the capacity of farmers to adapt to new technologies (Abunga et al., 2012). Although many studies have been conducted on the impact of credit on food security.
However, the objects they studied were rural communities in general and crop farming. There is no research that examines the impact of credit on the food security of coastal communities according to the purpose of this study.
3. Research Method 3.1. Research Sites
This research will use Multistage sampling methods to determine the research location. First, two regencies in East Java Province will be determined based on the two regencies including Malang Regency and Probolinggo Regency with the consideration of the low participation of fishermen in these two locations towards credit.
Second, the determination of the sub-district sample locations was determined randomly based on information from related institutions including the fisheries and maritime services, the port office and fishermen's groups.
Two sub-districts belong to sub-districts that have fishing ports including Sendang Biru port for Malang district and Paiton port for Probolinggo district. The next step is from the 2 sub-districts, 2 villages will be randomly selected for each so that in total there will be 4 villages. The research location can be seen in Figure 1. Finally, 50 respondent was selected from each village, and we consider 200 respondents as our sample.
3.2. Data Analysis
There are many approaches to measuring food security, but a more appropriate approach to measure household resilience is the Food Security Experience Scale (FIES). This approach is able to describe the four pillars of food security, including availability, accessibility, stability, and utilization.
FIES was developed by FAO with the aim of eliminating global hunger. FIES measures household resilience based on eight questions related to household experience of food security.
This question is a response dichotomy (yes/no). Furthermore, the results of household measurements will be categorized into 4 categories of food security. First, it is vulnerable if the respondent has a FIES score of 1 or higher than 1. It is in a moderately vulnerable category if the respondent has a FIES value of 4 or more. and very prone to have a score of 7 or 8.
Data analysis using Ordinary Least Squares (OLS) can provide valuable insights into the impact of credit on food expenditure. OLS is a statistical method used to estimate the relationship between variables by minimizing the sum of the squared differences between the observed and
predicted values. In this case, we can examine how credit, represented by variables such as credit score, loan amount, or debt-to-food expenditure ratio, influences an individual's food expenditure.
By employing OLS, researchers can analyze a dataset comprising information on credit-related factors and corresponding food expenditure levels.
The method allows for the identification of potential causal relationships and the quantification of their effects. OLS regression models can be constructed, where food expenditure serves as the dependent variable, and credit-related variables act as independent variables. Through this analysis, patterns and trends may emerge. The coefficients generated by the OLS regression provide insights into the magnitude and direction of the relationship between credit and food expenditure. Positive coefficients indicate that an increase in credit is associated with a higher food expenditure, while negative coefficients suggest the opposite. The statistical significance of these coefficients helps determine whether the relationships observed are likely due to chance or represent genuine associations. Furthermore, OLS analysis enables the identification and control of potential confounding factors. By including other relevant variables such as education level, occupation, or age, researchers can isolate the specific impact of credit on food expenditure and account for other factors that may also influence food expenditure levels. The equation can be seen in equation 1:
Exp = β0+β1C+xβ+ (1)
Where Exp is the dependent variable namely food expenditure (Rupiah per month), C is credit decision measured by dummy variable. x is a vector of independent variables that influence food. α indicates the coefficient of the parameter to be measured. is the error term.
Furthermore, the to examine the impact of credit access on household food security (FS) we used an ordered probit, since the dependent variable is ordinal (Rahman et al., 2023), and it was presented in Equation 2:
FS = β0+β1C+xβ+ (2)
Available online at HABITAT website: http://www.habitat.ub.ac.id Figure 1. Research Locations (Rahman et al., 2021)
4. Result and Discussion 4.1. Respondent Characteristics
Table 1. Show the food consumption score shows a value of 2,321 which means that fishermen's food security is included in the borderline category. In this sense, the majority of small-scale fishing communities are classified as having moderate food security but cannot be said to be safe. Therefore efforts are still needed to improve the food security of small-scale fishing communities in East Java.
The total household expenditure on food for one month is 226,958 USD or equivalent to Rp.
3,404,823.92. This means that the food expenditure of small-scale fishing communities in East Java is high. Therefore, to offset existing food expenditure, efforts to increase household income are needed so that they are able to have secure food security.
The credit variable shows a value of 0.263, which means that the majority of fishermen do not have access to credit. This condition indicates that small-scale fishing communities in East Java still have difficulty obtaining access to credit. This is because in general creditors do not accept collateral in the form of ships.
The average age of fishermen is 44 years.
This means that small-scale fishermen in East Java
are included in the category of fishermen who have a productive age in carrying out fishing activities. Whereas the experience of fishermen shows an average value of 23 years, which means that fishing communities already have sufficient and qualified experience in carrying out fishing activities.
The average ship size shows a yield of 2.5 GT. This means that fishermen in East Java have vessels that are classified as small scale because they have a size of less than 5GT. So it can be concluded that the cargo capacity that can be loaded by fishing boats is not much or little.
The fishermen group variable shows a result of 0.990, which means that the majority of fishing communities participate in fishing groups.
The average age of the ship shows results of 11 years. The variable number of fishing gear shows a result of 1.96, which means that the average fisherman has 2 units of fishing gear. The multigear variable shows a result of 0.488, which means not using more than one type of fishing gear. The average length of fishing trips in a week is 14 hours. The subsidy variable shows a result of 0.306, which means that the majority of small fishermen in East Java do not receive subsidies from the government.
Table 1. Descriptive Statistics
Variables Measurements Means std.
Food Consumption Score
1 = poor 2 = borderline 3 = acceptable
2,321 0.72
Food Production Total household expenditure on food for one month (USD)
226,958 497,988 credits 1 if fisherman has access to credit; 0
otherwise
0.263 0.441
age Fisherman's age in years 44,603 11,474
Education Fisherman education in years 3,431 4,283
Experience Years of fishing experience 23,445 11,907
Ship size Fishing boat size in gross tonnage (GT) 2,571 3,229
Fishermen group 1 if fisherman participates in fisherman groups; 0 otherwise
0.990 0.098
Ship age Age of the ship in years 11.115 6.203
Number of fishing gear Number of fishing gear owned by fisherman (Unit)
1966 2,959
Multigear 1 if the fisherman uses more than one type of fishing gear; 0 otherwise
0.488 0.501
Long trips Length of trip in week (hours) 14,069 16.166
subsidized 1 if fisherman gets subsidies, 0 otherwise 0.306 0.462 4.2. Effect of Credit and Socio-Economic
Conditions on Food Expenditures The results of the study in table 2 show a regression in the food expenditure of small-scale fishermen. The results of this study obtained a Prob>F value of 0.000. This explains that the variables of food expenditure, namely credit, age, education, experience, boat size, fisherman group, age of the vessel, number of fishing gear, multigear, trip length and subsidies have a simultaneous effect on food expenditure. The
results on the R-squared obtained from this study amounted to 0.163. The R-squared value obtained is relatively low.
The results of the regression analysis on food expenditure found five variables that had a significant effect. These variables include credit, education, boat size, fishing groups and number of fishing gear. The regression results on credit are 0.080. In education obtained by 0.094 and the size of the ship by 0.018. Fishermen group obtained of 0.001 and the number of fishing gear of 0.07.
Table 2. The Effect of Credit and Socio-Economic Conditions on Food Expenditure
Food EXP Coef. std. Error t P > | t |
credits 155.52 88.43874 1.76 0.080*
age -3.173136 3.57547 -0.89 0.379
Education 16.54253 9.844504 1.68 0.094*
Experience 1.543877 3.488188 0.44 0.659
Ship size 24.61921 10.31923 2.39 0.018**
Fishermen group -1217.068 347.3768 -3.5 0.0001**
Ship age -4.431041 5.554148 -0.8 0.426
Number of fishing gear
-21.44759 11.76509 -1.82 0.07**
Multigear -38.47665 74.27511 -0.52 0.605
Long trips -1.085961 2.137305 -0.51 0.612
subsidized 49.0753 79.43975 0.62 0.537
_cons 1487.46 381.7951 3.9 0.000
F(11,196) 3,480
Prob > F 0.000
Available online at HABITAT website: http://www.habitat.ub.ac.id
Food EXP Coef. std. Error t P > | t |
R-square 0.163
From table 2 it can also be seen that credit has a significant influence on the food expenditure of small-scale fishing communities at a significant level of 10%. Credit can increase consumption or income so that credit helps expand the budget (Basu & Wong, 2015). Credit is one access to the budget that helps in increasing capital and income.
The use of credit access is made to make it easier for financial users, especially fishermen. In food expenditure, credit is access for fishermen to obtain their needs. The results in this study credit have a significant effect on food expenditure. The higher the credit access used, the greater the food expenditure made by fishermen. In general, fishermen use credit for input needs from fisheries. Things to explain according to (Carranza
& Niles, 2019), that men spend credit for fishing inputs and other consumption.
The education variable has a significant effect on food expenditure with a significant level of 10%. In this case it shows that the higher the level of education, the impact on the household expenditure of small-scale fishing communities (Moh Afrizal Miradji et al., 2020).
Ship size has a significant influence on access to credit which has an impact on food expenditure with a significant level of 5%. The size of the ship that is getting bigger will give an illustration that the input used for going to sea will also increase. This is related to the perception that the farther the fishing range or the longer the trip is due to the adequate size of the ship, inputs will also increase, one of which is for food production (Nugraha et al., 2018). Food expenditure referred
to here is consumption during fishing trip activities.
The fishermen group has a significant influence on access to credit which has an impact on food expenditure with a significant level of 5%.
Fishermen who participate in fishing groups will have greater opportunities to obtain information related to food. So that the opportunity for fishermen to carry out food expenditure will be even greater (Firdaus & Witomo, 2016). The fishermen group shows that each individual has social capital that can affect income or expenses, which of course is related to financial capital.
The amount of fishing gear has a significant effect on food expenditure with a significant level of 5%. The larger the fishing gear, the opportunity for fishermen to increase the proportion of food consumption will also increase (Sahetapy, 2017).
4.3. Effect of Credit and Socio-Economic Conditions on Food Security
Based on the research results obtained in table 3 that Pseudo R2 is equal to 0.333, which means that the variable explains that credit, age, education, experience, boat size, fisherman group, boat age, number of fishing gear, multigear, trip length and subsidies have an effect simultaneously fishermen's food security. These results explain that the pseudo R2 value is in the moderate category and makes the model in this research good. 0.009, the number of fishing gear is 0.007, multigear is 0.336, trip length is -0.012, and subsidies are -0327.
Table 3. Effect of Credit and Socio-Economic Conditions on Food Security
FCS Coef. Std. z P>[z]
Credit 0.702 0.280 2.500 0.012**
Age -0.005 0.011 -0.440 0.660
Education 0.293 0.039 7.430 0.000***
Experience 0.015 0.010 1.400 0.163
Ship size 0.013 0.026 0.500 0.614
Fisherman group -1.902 268.454 -0.010 0.994
Ship age -0.009 0.016 -0.580 0.561
Number of fishing gear 0.007 0.039 0.190 0.849
Multigear 0.336 0.207 1.620 0.095*
Long trip -0.012 0.006 -2.270 0.023**
Subsidy -0.327 0.235 -1.390 0.163
/cut1 -2.582 268.455 -528.743 523.580
/cut2 -0.907 268.455 -527.069 525.254
Log likelihood -138.410
Prob > chi2 0.000
Pseudo R2 0.333
The results of this analysis also show that there are four variables that significantly influence the food security of small-scale fishermen. The four significant variables are credit, education, multigear and trip length. Table 2 shows that the credit variable has a significant effect on food security at the (5%) level. The probability value (p-value) is 0.012 with a coefficient value of 0.702. It can be concluded that every 1% increase will cause an increase of 7.02%. This means that the higher access to credit will have an impact on food security (Moh Afrizal Miradji et al., 2020).
Credit is one of the access to financial capital carried out by fishermen. Fishermen who have access to credit can apply adaptation strategies. From limited financial capital and fishermen who fail to meet the costs of adaptation strategies, access to credit is an opportunity for these failures and limitations. Access to credit is also a source of support for fishing. This source of support can help fishermen to easily access and buy the inputs they need (Rahman, Toiba, &
Huang, 2021). Credit in this study has a significant effect on the food security of small-scale fishermen. The existence of credit provides great opportunities for fishermen, especially as capital.
The need for food security is met with access to credit. The easier and more understandable it is to access credit, this can increase food security for small-scale fishermen.
Education variable has a significant effect on food security at the (1%) level. The probability value (p-value) is 0.000 with a coefficient value of 0.293. It can be concluded that every 1% increase will cause an increase of 2.93%. This means that the higher the level of education will have an impact on food security (Moh Afrizal Miradji et al., 2020).
Education is a factor that has the ability to influence technology, innovation, information, and decision-making in carrying out activities as fishermen (Limi, Zani, & Selvi, 2021). The results of this study indicate that education has a significant effect on fishermen's food security.
This shows that the higher the education, the greater the chance for fishermen to understand how to maintain the quality of food. Food quality is maintained, can increase food security.
The multigear variable has a significant effect on access to credit and has an impact on food security at the (10%) level with a probability
value (p-value) of 0.095 with a coefficient value of 0.336. It can be concluded that every 10%
increase will cause an increase of 3.36%. This means that each addition of multi-gear to fishing gear will make it easier to obtain access to credit and will have an impact on food security (Tuda et al., 2016)
Multigear is used to catch fish. The use of multigear allows the target fish species to become more numerous, so that the catch is expected to increase. Multigear is very important to support efforts to manage capture fisheries in a responsible and sustainable manner (Fauziyah, Agustriani, Satria, Apriansyah, & Nailis, 2018). In this study, it was found that multigear had a significant effect on fishermen's food security. The advantages of multigear can catch more fish targets thereby supporting the increase in food security for small- scale fishermen.
The trip length variable has a significant effect on access to credit and has an impact on food security at the (5%) level. The probability value (p-value) is 0.023 with a coefficient value of 0.012. It can be concluded that every 5% increase will cause a decrease of 0.006%. Which means that the shorter the time for fishing, it can be concluded that food security will increase because the input for fishing is not too much (Pratama et al., 2016).
The length of the trip is applied to the possible impact on fish stocks over time. Based on economic theory, it is defined as a cost or benefit that affects a third party who does not invite or otherwise chooses to incur the cost or benefit (Sumaila, et al., 2019). The length of the trip has a significant effect on the food security of fishermen. This helps and improves food security in small-scale fishermen by minimizing fishing inputs.
5. Conclusion
This study estimates the impact of credit access on food security. Using a cross-sectional data from 200 fishermen in east java, and estimated by OLS and ordered probit, the results of the study show that fishermen's food security is included in the borderline category. In this sense, the majority of small-scale fishing communities are classified as having moderate food security but cannot be said to be safe. Therefore efforts are still needed to improve the food security of small-scale
Available online at HABITAT website: http://www.habitat.ub.ac.id fishing communities in East Java. Other findings
show that credit, education, boat size, fishing groups and the number of fishing gear have a significant effect on the food expenditure of small- scale fishing communities in East Java.
Meanwhile credit, education, multigear and trip length have a significant effect on fishermen's food security. Therefore, to support food security, it is necessary to increase access to credit, increase education levels, ship size, join fishermen groups.
References
Abunga, M., Emelia, A., Samuel, G., & Dadzie, K.
(2012). Adoption of Modern Agricultural Production Technologies by Farm Households in Ghana : What Factors Influence their Decisions ? 2(3), 1–14.
Ayaz, S., & Hussain, Z. (2011). Impact of Institutional Credit on Production Efficiency of Farming Sector: A Case Study of District Faisalabad. Pakistan Economics and Social Review, 49(2), 149–162.
Barrett, CB (2000). 10.1007/978-1-4020-8304-4.
CrossRef Listing of Deleted DOIs,
1(January 2008).
https://doi.org/10.1007/978-1-4020-8304-4 Basu, K., & Wong, M. (2015). Evaluating seasonal food storage and credit programs in east Indonesia. Journal of Development Economics, 115, 200-216.
Beck, T., Demirgüç-Kunt, A., & Honohan, P.
(2009). Access to financial services:
Measurement, impact, and policies. World Bank Research Observer, 24(1), 119–145.
https://doi.org/10.1093/wbro/lkn008 Carranza, M., & Niles, MT (2019). Smallholder
farmers spend credit primarily on food:
gender differences and food security implications in a changing climate.
Frontiers in Sustainable Food Systems, 3, 56.
Chisasa, J., & Makina, D. (2013). Bank Credit And Agricultural Output In South Africa: A Cobb-Douglas Empirical Analysis.
International Business & Economics Research Journal (IBER), 12(4), 387.
https://doi.org/10.19030/iber.v12i4.7738 Collins, A. (2018). Saying all the right things?
Gendered discourse in climate-smart agriculture. Journal of Peasant Studies,
45(1), 175–191.
https://doi.org/10.1080/03066150.2017.13 77187
Colwell, JM, & Alxerod, M. (2017). Socio- economic impacts of a closed fishing season on resource-dependent stakeholders in Tamil Nadu, India: Differences in income and expenditure effects by occupational group. Marine Policy, 77, 182-190.
Fauziyah, Agustriani, F., Satria, B., Apriansyah, P., & Nailis, W. (2018). Assessment of Multigear Types in Small-Scale Capture Fisheries Businesses in Breech Waters, Banyuasin Regency, South Sumatra.
Marine Fisheries, 9(2), 183-197.
Firdaus, M., & Witomo, CM (2016). Analysis of Welfare Levels and Household Income Inequality of Large Pelagic Fishermen in Sendang Biru, Malang Regency, East Java.
Journal of Socio-Economy of Maritime Affairs and Fisheries, 9(2), 155.
https://doi.org/10.15578/jsekp.v9i2.1218 Guerrieri, V., Lorenzoni, G., & Prato, M. (2020).
Slow Household Deleveraging. Journal of the European Economic Association, 18(6), 2755–2775.
https://doi.org/10.1093/jeea/jvaa049 Kuwornu, JKM, Suleyman, DM, & Amegashie,
DPK (2013). Analysis of Food Security Status of Farming Households in the Forest Belt of the Central Region of Ghana.
Russian Journal of Agricultural and Socio- Economic Sciences, 13(1), 26–42.
https://doi.org/10.18551/rjoas.2013-01.04 Limi, MA, Zani, M., & Selvi. (2021). Factors
Affecting The Food Security of The Bajo Community Households In West Muna District During The Covid-19 Pandemic.
HABITAT, 32(2), 74-81.
Ma, W., & Abdulai, A. (2016). Does cooperative membership improve household welfare?
Evidence from apple farmers in China.
Food Policy, 58, 94–102.
https://doi.org/10.1016/j.foodpol.2015.12.0 02
Mendonça, JT, & Pereira, ALC (2014).
Management of gillnet fisheries in the south coast of the state of São Paulo, Brazil. Anais Da Academia Brasileira de Ciencias, 86(3), 1227–1237. https://doi.org/10.1590/0001- 3765201420130139
Moh Afrizal Miradji, Martha Suhardiyah, Bayu Rama Laksono, Sigit Prihanto Utomo, &
Sutama Wisnu Dyatmika. (2020). Analysis of the Sustainability of Micro, Small and Medium Enterprises Undergoing New Normal During the Corona Pandemic Banjarsari Village, Kec. Cerme Gresik Regency. Ecobis Community Service:
Journal of Community Service, 1(2), 155–
161.
https://doi.org/10.36456/ekobisabdimas.1.2 .3036
Nordjo, RE, & Adjasi, CKD (2020). The impact of credit on productivity of smallholder farmers in Ghana. Agricultural Finance
Review, 80(1), 91–109.
https://doi.org/10.1108/AFR-10-2018-0096 Nugraha, SW, Ghofar, A., & Saputra, SW (2018).
Monitoring of Lemuru Fisheries in the Bali Strait. Management of Aquatic Resources Journal (MAQUARES), 7(1), 130–140.
https://doi.org/10.14710/marj.v7i1.22533 Pratama, MAD, Hapsari, TD, & Triarso, I. (2016).
FACTORS AFFECTING THE
PRODUCTION OF THE PURSE SEINE FISHING UNIT (GARDAN) AT FISHING BASE PPP MUNCAR, BANYUWANGI, EAST JAVA Factors Affecting the Production of Purse Seine Unit in Fishing Base Muncar Fishing Port Banyuwangi, East Java. FISHERIES SCIENCE : Indonesian Journal of Fisheries Science and
Technology, 11(2), 120.
https://doi.org/10.14710/ijfst.11.2.120-128 Rahman, A. (2017). Smallholder Agriculture and
Inclusive Rural Transformation.
Bangladesh Development Studies, 40(1–2), 119–147.
Rahman, M. S., Huang, W. C., Toiba, H., & Efani, A. (2022). Does adaptation to climate change promote household food security?
Insights from Indonesian fishermen.
International Journal of Sustainable Development and World Ecology, 29(7), 611–624.
https://doi.org/10.1080/13504509.2022.20 63433
Rahman, M. S., Huang, W. C., Toiba, H., Putritamara, J. A., Nugroho, T. W., & Saeri, M. (2023). Climate change adaptation and fishers’ subjective well-being in Indonesia:
Is there a link?. Regional Studies in Marine
Science, 63, 1-8.
https://doi.org/10.1016/j.rsma.2023.10303 0
Rahman, MS, Toiba, H., & Huang, WC (2021).
The Impact of Climate Change Adaptation Strategies on Income and Food Security:
Empirical Evidence from Small-Scale Fishers in Indonesia. Sustainability, 13(14), 7905. https://doi.org/10.3390/su13147905 Reyes, A., Lensink, R., Kuyvenhoven, A., & Moll,
H. (2012). Impact of Access to Credit on Farm Productivity of Fruit and Vegetable Growers in Chile. October 2014, 18–24.
Sahetapy, W. & Sangdji. (2017). The Impact of Community Activities on Coral Reef Ecosystems in the Coastal Waters of Katapang Hamlet, West Seram Regency.
Triton Journal, 13(2), 105–114.
Saleem, MA, & Jan, FA (2018). The Impact of Agricultural Credit on Agricultural Productivity in Dera Ismail Khan (District).
European Journal of Business and Management, 3(2), 1–8. www.iiste.org Sumaila, UR, Ebrahim, N., Schuhbauer, A.,
Skerrit, D., Li, Y., Kim, SH, . . . Pauly, D.
(2019). Updated estimates and analysis of global fisheries subsidies. Marine Policy, 109, 103695.
The World Bank. (2018). The Global Findex Database 2017 Indonesia. InReport.
Tuda, PM, Wolff, M., & Breckwoldt, A. (2016).
Size structure and gear selectivity of target species in the multispecies multigear fishery of the Kenyan South Coast. Ocean and Coastal Management, 130, 95–106.
https://doi.org/10.1016/j.ocecoaman.2016.
06.001
Wicaksono, E. (2014). The Impact of Agricultural Credit on Rice Productivity. International Journal on Advanced Science, Engineering and Information Technology, 4(5), 322.
https://doi.org/10.18517/ijaseit.4.5.427 Zulfiqar, F., Shang, J., Zada, M., Alam, Q., &
Rauf, T. (2021). Identifying the determinants of access to agricultural credit in Southern Punjab of Pakistan.
GeoJournal, 86(6), 2767–2776.
https://doi.org/10.1007/s10708-020-10227- y
