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SPASIAL-BASED DECISION-MAKING SYSTEM MODEL ON PATIN
FISH (PANGASIUS.Sp) AGROINDUS SUPPLY CHAINS IN WEST JAVA
INTRODUCTION
A supply chain is a series of processes that involve the movement and transformation
of raw materials into finished products, as well as the distribution of these products to end
consumers (Blackburn and Scudder 2009). The supply chain is a very crucial aspect in the
sustainability of business and industry, not only for companies but also for the economy as a
whole.
The role of supply chains in the modern business world is increasingly complex and
important due to the following factors: 1) Globalization: The development of technology and
communication has erased the geographical boundaries between countries, so supply chains
are becoming increasingly globalized. Raw materials, components or finished products can be
produced in different locations and integrated in long supply chains. 2) High level of
competition: Business competition is intensifying, and supply chain efficiency is becoming
one of the key factors in achieving competitive advantage. Companies need to ensure their
supply chains run smoothly to meet consumer demand in a timely and cost-efficient manner.
3) Process complexity: Supply chains involve many stages, from raw material procurement,
production, storage, distribution, to sales. These processes require good coordination to avoid
errors or delays that can have a negative impact on business continuity. 4) Uncertainty and
risk: Many factors can affect the supply chain, such as changes in market demand,
fluctuations in raw material prices, logistics problems, natural disasters, regulatory changes,
and so on. All of these lead to high levels of uncertainty and risk that must be managed
properly.
With the rapid growth of the fishing industry, challenges and complexities arise in
managing the pangasius agro-industry supply chain (Kaminski et al. 2018). Some of these
challenges include: 1) Spatial variability: The catfish agro-industry involves many
geographically dispersed elements and actors, such as fish hatcheries located in certain
regions, farming ponds in different locations, and distribution points and markets located in
other areas. This spatial variability affects logistics, travel time, and distribution costs, and can
affect the quality of the product that is ultimately received by consumers. 2) Resource
management: Appropriate decision-making on farm site selection, resource allocation, and
risk management in the pangasius agro-industry supply chain is critical to ensure
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sustainability and operational efficiency. 3) Market demand: Market demand patterns for
catfish may fluctuate due to seasonal factors, consumption trends, regulatory changes, or
economic situations. Therefore, adaptive marketing and distribution strategies are needed.
In the face of these challenges, the use of spatial-based decision-making systems is relevant
and important in the catfish agro-industry. Spatial-based decision-making systems utilize
geographic information system (GIS) technology and spatial analysis to assist stakeholders in
optimizing supply chain processes, identifying potential locations, understanding market
demand patterns, and optimizing supply chain processes manage resources more efficiently
(Keenan and Jankowski 2019). By integrating this data, the system can provide in-depth and
accurate analysis, visualize data geographically, and assist in identifying the best solutions to
the challenges faced by the pangasius agro-industry supply chain.
With the adoption of a spatial-based decision-making system, the pangasius agro-
industry is expected to improve operational efficiency, reduce distribution costs, improve
product quality, and optimize the overall supply chain (Yusianto et al. 2019). This is expected
to have a positive impact on the sustainable growth of the fisheries industry and contribute to
the country's economy.
Supply chain decision-making systems are data-driven and information technology-
driven approaches that combine analytics, modeling, and real-time information to assist
decision-makers in optimizing supply chain operations.
Spatial decision-making systems are approaches to decision-making that utilize geographic
information system (GIS) technology and spatial analysis to integrate geographic data with
other information in the decision-making process (Keenan and Jankowski 2019). This
approach aims to provide deeper insights and understanding of problems related to a
particular geographic location or space. The following are some of the main characteristics
and components of spatial-based decision-making systems (Yao et al. 2017): 1) Spatial Data:
This system uses geographic and spatial data as a core element in the analysis. This spatial
data can be in the form of maps, satellite images, geographic coordinate data (latitude and
longitude), location-related data such as administrative areas, roads, rivers, or mountains, and
other data that has location-related information. 2) Spatial Analysis: This system uses spatial
analysis to process geographic data by applying various analysis techniques, such as overlay,
proximity analysis, spatial interpolation, and spatial clustering. This enables a better
understanding of geographic relationships and patterns that are relevant in the context of
decision-making. 3) Data Integration: This system integrates spatial data with other non-
spatial or attribute data to provide a more complete and comprehensive picture. For example,
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spatial data on production locations and non-spatial data on market demand can be combined
to optimize product distribution geographically. 4) Visualization: GIS allows visualization of
data geographically through maps, graphs, and other visualizations. These visualizations help
decision makers to quickly understand complex information and help identify relevant
patterns or trends. 5) Decision Making: Geographic data and spatial analysis are used as a
basis for better and more informative decision-making. These systems can help in identifying
the best solutions, evaluating alternative scenarios, and planning appropriate actions in
contexts involving geographic locations or spaces.
Overall, spatially-based decision-making systems allow users to gain more in-depth
and contextualized insights in dealing with problems involving spatial elements or geography.
This can help companies, governments, or other organizations to optimize their decision-
making processes and achieve their goals more efficiently and effectively.
Some important benefits of supply chain decision-making systems are: 1) Better planning:
With a decision-making system supported by data analysis and modeling, planning can be
done more accurately and in detail to anticipate fluctuations in market demand, plan
inventory, and predict possible situations. 2) Cost reduction and efficiency: The system can
help identify areas that require improvement or efficiency in the supply chain, thereby
reducing operational costs and increasing productivity. 3) Better risk management: With the
ability to identify risks and anticipate changes in market or environmental conditions,
companies can plan effective risk mitigation strategies. 4) Improved customer service: With
an effective decision-making system, companies can better meet customer demands, provide
faster and more responsive services, and ensure adequate product availability.
Fisheries are a global food source that must be preserved and sustained. The 2030
Sustainable Development Agenda sets goals for the contribution and behavior of fisheries and
aquaculture towards food security and nutrition, and the use of natural resources in ways that
ensure sustainable development in economic, social and environmental terms.
T h e r e f o r e , developing countries need to fully optimize their fisheries potential. The
potential of fisheries is huge, but since the late 1980s capture fisheries production has been
relatively static, so aquaculture is expected to grow and meet the needs for human
consumption (FAO 2018). One aquaculture that has great potential to be developed is catfish.
Patin fish (Pangasianodon hypophthalmus) is a freshwater fish species that has high
economic potential, both in domestic consumption and export. The ever-increasing market
demand for catfish drives the development of a complex and extensive catfish agro-industry
supply chain. This supply chain covers the entire process from the production of catfish in
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hatchery ponds, rearing in aquaculture ponds, processing and distribution up to the production
of catfish all the way to the end consumer.
The main problem with fisheries supply chains is the high vulnerability, complexity,
and uncertainty of the product characteristics caused by the perishable nature of the
commodity, sensitivity to climate change, and the way the product is handled. In addition,
spatial conditions significantly affect supply capability (Rosita et al. 2019). Therefore, a
Decision Support System (DSS) is needed to improve product resilience that considers
product characteristics with a spatial perspective. This study proposes a new fisheries supply
chain approach, namely a material management solution, by minimizing supply and demand
imbalances using spatial analysis within a Spatial Decision Support System (SDSS)
framework.
Background:
Patin fish is one of the freshwater fish commodities that has great potential to be
developed and has a high selling price. This is what causes catfish (Pangasius sp) to receive
attention and interest by entrepreneurs to cultivate it. Patin fish can be kept in a place that
does not require running water and in just 6 months of maintenance can reach a length of 35-
40 cm (Prihatman 2000).
As a prospective commodity in the world, catfish has become a substitute commodity
for other white meat fish fillets such as catfish (Ictalurus punctatus) (Hong and Duc 2009).
According to Polanco (2011), the penetration of catfish (Pangasius) fillets into the EU market
affects the market preference of fish fillets in the EU. Pangasius is also one of the
commodities in the fisheries and marine sector in Indonesia, and its production is likely to
increase and has considerable potential for its development with various high market
opportunities, both at home and abroad (Hayandani et al. 2013).
Quoting the statement of Azam B Zaidy, Secretary General of the Indonesian Catfish
Entrepreneurs Association (APCI), in Kompas Daily dated March 2, 2018, said that catfish
production in Indonesia continues to increase along with the growth of catfish production
centers in several regions, especially in Sumatra and Java. Patin production has superior
productivity, reaching around 200-400 tons per hectare (ha). This number is almost
comparable to the productivity of catfish in Vietnam, which reaches 300-500 tons per ha.
With such productivity levels, patin production in Indonesia is in the range of 250,000 to
300,000 tons per year. About 85 percent of it is sold in fresh form. In addition, the production
of patin processed into sliced meat or patin fillets has also increased rapidly. In 2010, patin
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fillet production was only about five tons per month, but now it has increased to an average of
700 tons per month (Yulianus 2018).
Catfish (Pangasius) fillet is a processed product by separating the meat from thorns,
skin, and other unnecessary materials while maintaining the intact shape of the meat which is
then stored at freezing temperatures. Fillets have the advantage of being an easy-to-process
and consume foodstuff where all parts of the meat can be consumed. Also, in the storage
process, they require less space due to their flat shape making them easy to stack. The added
value of Pangasius processed into fillet products can also support the growth of Pangasius
production. In Indonesia, catfish (Pangasius) fillets have only emerged in recent years.
Previously, fillets were imported from Vietnam, mostly known as Dori fillets. In 2022,
through the Decree of the Minister of Maritime Affairs and Fisheries Number 80 of 2022, the
government included catfish into certain types of fishery products that are restricted from
entering the territory of the Republic of Indonesia (KKP 2022). This makes the domestic
catfish fillet industry more free to do business. Import restrictions have sparked excitement
among farmers and local industries in several locations in Indonesia.
Government support can be seen in the way it facilitates the provision of
infrastructure, the development of fishery farmers, technology development, and work.
stakeholder cooperation. Infrastructure provision includes nursery centers, and processing
facilities and infrastructure. Meanwhile, fishery farmer development includes the
encouragement of aquaculture and processing-level certifications (CBIB, HACCP, GMP, and
SSOP) (Yuwono and Zakaria 2012; Rimmer et al. 2013).
The Ministry of Maritime Affairs and Fisheries (KKP) of the Republic of Indonesia
released data on the total national patin production which began to increase in the last two
years. Indonesia's patin production is still increasing (Figure 1) and will continue to be
boosted not only through KKP but through the synergy of 25 related Ministries and
Institutions as mandated by Presidential Instruction (Inpres) Number 7 of 2016 concerning the
Acceleration of the Development of the National Fisheries Industry. Note that in 2016, which
was recorded as 2017, national patin production amounted to 437,111 tons, an increase of
28.91% from the previous year which was only 339,069 tons.
The opportunity for the patin industry for local consumption is very wide open with
t h e policy of limiting the entry of patin from outside countries by the KKP (KKP 2022).
Even with the news of declining patin and Dory exports from Vietnam due to the issue of the
country using chemicals to whiten fish meat. In addition, the high food safety requirements
that will be set by the KKP through the Indonesian National Standard (SNI) is an opportunity
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for local patin to dominate the market. One of the other problems faced in patin production is
the imbalance between capacity and factory demand. Currently, the quality, color, and aroma of
Indonesian patin products do not meet the standards and demands of the industry. For
example, the color variation of patin meat produced is still inconsistent, including white,
yellow, and red, while the largest demand comes from white patin meat. Samiono told
Kompas (April 19, 2023) that there are several challenges in improving the competitiveness of
the patin industry from upstream to downstream. One of them is the location of the processing
industry which is not close to the production center, resulting in high logistics costs. For
example, a catfish processing company based in Jombang, East Java, has to incur additional
costs to obtain raw materials from outside Java. In addition, the cost of shipping products to
consumers, who are mostly located in Papua and Kalimantan, is also high contributing to high
logistics costs. He stated that factories are located in areas without sources of raw materials,
so they have to add the cost of transporting raw materials to the factory. This logistics cost
component is then incorporated into the final product price (Grahadyarini 2023).
Although the target consumers are wide open among ASEAN countries, domestic
production of catfish (Pangasius) fillets should be focused on competitiveness in meeting
local needs before expanding to overseas markets. Therefore, a comprehensive study is
needed by focusing on internal and external factors in generating alternative strategies in an
effort to strengthen the competitiveness of the domestic industry in the production of catfish
(Pangasius) fillets. Presidential Instruction No. 7 of 2016 on Accelerating the Development of
the National Fisheries Industry has mandated 25 relevant Ministries and Institutions to take
the necessary strategic steps to support efforts to accelerate the development of the national
fisheries industry. One of the steps mandated in the Presidential Instruction is to increase the
production of capture fisheries, aquaculture and fishery product processing. Sustainable
business has been defined in several ways, with one goal being the "creation of resilient
organizations through integrated economic, social and environmental systems" (Dijkman et
al. 2015).
A sustainable business must meet the current needs of the organization and its
stakeholders while protecting, sustaining and enhancing the environmental, social and
economic resources needed in the future (Dakov and Novkov 2008). Supply chains are
dynamic processes that include the continuous flow of materials, funds and information across
multiple functional areas within and between chain members (Panigrahi et al. 2018). A focus
on supply chains is therefore a step towards the wider adoption and development of
sustainability (Linton et al. 2007). Investigating the ways in which sustainable supply chains
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are defined, interpreted and applied in practice is essential for such an understanding and is,
therefore, in strong demand (Ashby et al. 2012).
One of the goals of the supply chain is to maximize the overall value generated in an
industrial process. This leads to a discrepancy between the value of the final product to the
customer and the costs incurred in the supply chain to meet customer demand. For
commercial supply chains, this is highly correlated with supply chain profitability (Axsäter
2003). Naturally, companies seek to reduce costs and increase revenues. To achieve one or
more of the company's goals, various actions can be taken and to survive in the market,
companies must have a competitive strategy. Another thing to note is that, the competitive
strategy should be in line with the supply chain strategy as the success or failure of the
company largely depends on it. According to Chopra and Meindl (2007) there are three
important steps in achieving strategic objectives. First, the competitive strategy and all
functional strategies must be compatible, and each functional strategy must support the other
functional strategies to help achieve competitive goals. Second, different functions must
structure their processes and resources correctly to be able to execute the strategy
successfully. Third, the supply chain design and the role of each stage in the supply chain
must be aligned to support the supply chain strategy.
In this context, an appropriate method of calculating the fish logistics performance
index is needed. To make this happen, there needs to be regulations that facilitate and support
fish procurement, storage, transportation and distribution. Adequate infrastructure, including
road conditions, accessible airports, access to finance, and access to information, are also
important factors. In addition, trained and skilled human resources in managing fish
procurement, storage, transportation, and distribution are needed. The existence of fisheries
businesses and logistics service players also needs attention so that their operations run well.
One of the factors contributing to the adoption of technology use is the penetration of internet
users (Ho et al. 2007). According to data from the Indonesian Internet Service Providers
Association, APJII (2019), based on the results of the APJII survey and Polling Indonesia, the
number of internet users in Indonesia in 2022 was 204.7 million. This means that the
penetration of internet users in the country has increased to 64.8% of the total population of
264.16 million. This figure increased from 2017 when the internet penetration rate in
Indonesia was recorded at 54.86% (Figure 2). This value ranks Indonesia as the 6th largest in
the world in terms of the number of internet users (Informatika 2019).
The rapid growth of internet users in Indonesia has influenced various industry sectors to take
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advantage of the "information revolution" provided by the internet, including the agribusiness
sector. Some experts say that the internet has the ability to improve performance in the
agribusiness sector, among others through time savings due to available information (Rolfe et
al. 2003), the creation of additional markets for inputs and outputs (Gabriele 2004), and
increased competitiveness (Courtright 2004; Smith et al. 2005).
While Nistor et al. (2010) added that the agribusiness sector has the potential to apply
e-commerce which refers to the use of the internet for markets, buying and selling goods and
services, exchanging information, and creating and maintaining web-based relationships
between users. The application of e-commerce in the agribusiness sector is called e-
agribusiness. E-agribusiness offers e-agribusiness is a great opportunity for producers and
retailers, while demanding in-depth study of marketing strategies and consumer knowledge
(Goldsmith 2000). E-agribusiness-related applications can be categorized from a farmer's
perspective according to production, service and output factors (Cloete and Doens 2008;
Manouselis et al. 2009). In recent years, food safety issues have become more serious and
continue to threaten public health. It is crucial to track detailed event information in the entire
food supply chain including food production, processing, warehousing, transportation and
retail. Establishing an accurate and effective food safety traceability system has become a key
solution to food safety issues.
Decision system models are necessary for all people, stakeholders, and leaders.
Decision-making can be daily or even momentary, many important decisions stem from the
information available and the treatment of that information. In essence, the more relevant the
information needed, the higher the level of knowledge and the smarter the decisions that can
be made. Decision-making related to planning and managing fish supply chains requires the
role of decision-making systems, because this decision-making process contains large
amounts of data (Nurdin et al. 2019).
Fisheries are activities related to the management of the utilization of fish resources,
from production and processing to marketing carried out in a fisheries business system. The
fish supply chain is a process of production activities to get to the hands of consumers by
involving several systems to support the distribution process of fish to the destination. The
need for a fish supply chain aims to meet the demand for fish in areas far from fish resources.
The supply chain of fishery products involves several actors, including farmers,
collectors, and industries. The fishery products produced have perishable characteristics and
are a type of product with a short expiration period (Seyedhosseini and Ghoreyshi 2014) and
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are seasonal in nature that depends on the environment with temperature and humidity being
important factors (Blackburn and Scudder 2009), so to get to the hands of consumers, good
products and an adequate supply chain management system are needed. According to some
researchers, supply chain management is the process and overall production activities starting
from processing and distribution activities, until the product is desired by consumers or
society with the aim of improving product quality at minimum cost (Ferguson 2000; Shepherd
and Günter 2006; Xu et al. 2009; Yu et al. 2015). In the face of the above conditions, an
artificial intelligence-based model for integrated supply chains is needed to support the era of
the industrial revolution 4.0 (Jiao et al. 2018).
Decision-making processes in fish supply chains are highly complex and the need for
modeling is increasing to support strategy and implementation for high-performance supply
chain network design (Biswas and Narahari 2003; Jason et al. 2006; Nurdin et al. 2019). This
complexity is due to the large number of variables and data (Biswas and Narahari 2003). In
this regard, optimization has become a high technology in fish resource management
planning, which in this regard includes the supply chain (Chan and Kumar 2009; Li and
Amini 2012). Some important variables in fish supply chains include:
1) Cultivation: Farming practices, and the technology used can affect the quantity and
quality of fish supplied. 2) Availability and Seasonality: The availability of fish in nature, the
fishing season, and climatic factors affect the supply and price of fish. 3) Processing: The
process of processing fish into products ready for consumption also involves technology,
equipment, and labor that affect the quality of the final product. 4) Distribution and
Transportation: Efficient distribution and transportation infrastructure is required to ensure
that fish reaches the market and consumers in a fresh condition. 5) Regulations and Policies:
Government policies related to licensing, fish resource management, and international trade
also have a significant impact on the fish supply chain. 6) Market and Demand: Market
conditions, consumer demand, consumption trends, and consumer preferences also play a role
in shaping the fish supply chain. 7) Product Quality and Safety: The quality, freshness, and
safety of fish products are critical in maintaining consumer confidence and meeting food
safety standards. 8) Cooperation between Parties: Collaboration and good working
relationships between stakeholders in the fish supply chain, such as fishermen, farmers,
suppliers, traders, and retailers, are also important factors in the success of the fish supply
chain. 9) Technological Innovation: The use of modern technologies, such as information and
monitoring systems, can help improve efficiency and transparency in the fish supply chain.
All these variables must be managed holistically and sustainably to ensure the fish supply
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chain runs smoothly, efficiently, and is able to meet market and consumer needs while
maintaining the sustainability of fish resources and the environment.
One of the uniqueness of catfish is that it has a different color and taste from each
different farming site, depending on where it was produced. This can be both an advantage
and losses, depending on the business strategy to be decided. Traceability is one way to
provide more transparency, and it is argued that by increasing transparency, production issues
in the supply chain can be better mapped and understood, ultimately helping to improve the
environmental and social impact of the supply chain (Gonzálvez-Gallego et al. 2015).
Consumers are increasingly interested in knowing where and how the ingredients they
consume are extracted and produced (Angelis and Ribeiro da Silva 2019). This study started
from the industry point closest to the largest market share, which is the capital city of Jakarta
and which has obtained a quota for the export of catfish fillets. From the results of field visits,
two fairly large processing industries were obtained, namely PT Kurnia Mitra Makmur
Purwakarta (KMMP), which is located in Cikopo Bungursari, Purwakarta Regency and PT
ADIBS, which is located in the Balai Service Business Production FisheriesAquaculture,
Hamlet Sukajadi, RT.01/RW.04, Pusakajaya Utara, Cilebar sub-district, Karawang. These
industries often source raw materials in the form of fresh fish from Tulungagung Regency and
Pringsewu Regency, Lampung. The reason is that often the closest areas, namely Subang and
Purwakarta, are unable to fulfill the demand catfish with the desired quality.
The need for fresh catfish to be processed as fillets is quite large. For PT KMMP
alone, the need for catfish can reach 100-150 tons of catfish per month. Whereas the ability of
fish farming around the factory, namely the Purwakarta and Subang areas, is a maximum of
only 40 tons per month. There is a huge difference in the demand for catfish, so inevitably,
the industry takes fresh catfish from other areas, namely Pringsewu and Tulungagung.
Problem Formulation:
Supply chain network design (SCND) is one of the most important strategic decisions that has
recently received increasing attention from researchers. The SCND problem involves the
number of facilities organized to procure and transfer raw materials to finished products,
distribute these products and present after sales services to meet customer needs. This
problem determines the number, location, capacity level and facilities to be considered.
Therefore, supply chain configuration is a key strategic issue that affects tactical/operational
activities and needs to be optimized for long-term efficient operation of the entire supply
chain.
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Many companies emphasize customer responsiveness and quality as a way to stay in
business over their lifetime. One measure to gauge the level of customer service is the fill rate
of the number of customer requests fulfilled within the promised delivery time (demand
fulfillment rate). Many attempts have been made to model and optimize SCND problems that
are mostly based on deterministic and single-objective approaches (Melo et al. 2019), while
most real SCND problems are composed by diverse sources of uncertainty and multiple
measures. As pointed out by Sabri and Beamon (2012), uncertainty is one of the most
challenging but significant issues in SCM.
A fish supply chain decision system is a system designed to assist in decision-making
regarding the entire fish supply chain. The fish supply chain covers all stages, from fish
production and harvesting, processing, distribution, to marketing fish products to end
consumers. This system plays an important role in optimizing the performance and efficiency
of the overall fish supply chain.
The following are the main components involved in the fish supply chain decision
system: 1) Data Collection: This system collects data from various sources, such as fisheries,
fish processing industries, transportation, and markets. The data collected may include
information on fish stocks, market demand, prices, weather conditions, and other factors that
affect the fish supply chain. 2) Data Analysis: The collected data is analyzed to understand
patterns, trends, and opportunities in the fish supply chain. This analysis helps in identifying
problems, opportunities, and evaluating the performance of each stage of the supply chain. 3)
Decision Making: Based on the results of data analysis, the fish supply chain decision system
provides relevant and accurate information to aid decision-making. Decisions can relate to
fish harvesting site selection, marketing strategies, resource allocation, and distribution route
optimization, for example. 4) Market Prediction: The system is also capable of performing
market predictions to anticipate future fluctuations in fish demand and prices. These
predictions help stakeholders in planning production and distribution more efficiently. 5)
Inventory Management: The fish supply chain decision system helps in managing fish
inventory efficiently. This includes monitoring fish stocks, arranging production and harvest
scheduling, and minimizing overstocks or shortages. 6) Distribution Route Optimization: The
system can help optimize fish distribution routes from producers to consumers by considering
factors such as distance, transportation costs, and road conditions. 7) Integration and
Collaboration: Fish supply chain decision systems facilitate integration and collaboration
between all stakeholders in the supply chain, including fishers, fish processors, distributors,
traders, and consumers. This helps improve transparency and coordination in the overall
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supply chain.
Fish supply chain decision systems serve to increase efficiency, reduce costs, improve
product quality, and ensure sustainable availability of fish for consumers. With the help of
advanced technology and data analysis, this system can provide great benefits to the fishing
industry.
Spatial-based supply chains in catfish commodities involve spatial data management and
analysis to ensure the smooth flow of catfish from upstream to downstream. Some of the
requirements or components that need to be considered in spatially-based supply chains on
catfish commodities include: 1) Resource Mapping: Identification and mapping of catfish
resources is the first step in building a spatial-based supply chain. This involves mapping the
location of production centers, fishing waters, and patin cultivation areas. 2) Infrastructure
and Transportation Access: Mapping infrastructure such as roads, and distribution channels
enables efficient logistics planning in transporting catfish from fishing or farming grounds to
processing plants and markets. 3) Use of Spatial Technology: Utilization of spatial
technologies such as geographical information systems (GIS) and satellite monitoring can be
assist in mapping, monitoring, and analyzing data related to the catfish supply chain. 4)
Resource Management: Spatial-based management is also important in optimizing the
utilization of catfish resources. This involves the establishment of fisheries management
areas, fishing quotas, and restrictions on cultivation areas. 5) Production and Demand
Prediction: Spatial analysis can help in forecasting catfish production in different regions and
also predict market demand in different locations. 6) Surveillance and Security: Spatial
technology can be used to monitor and supervise illegal activities such as illegal fishing and
smuggling practices. 7) Product Quality Assurance: Spatial monitoring can also be used to
ensure the quality and safety of catfish products from upstream to downstream. 8)
Collaboration and Coordination: Effective communication and collaboration between various
stakeholders in the catfish supply chain is essential to achieve efficiency and sustainability in
spatial operations. By fulfilling these requirements, spatially-based supply chains in catfish
commodities can run more efficiently, transparently and sustainably, and be able to better
meet market demand.
Patin Fish (Pangasius sp):
Patin has a slender, elongated body that exhibits a silver-white hue, accompanied by a
bluish dorsal region. The skull region of the fish shows a relatively small size, with the mouth
opening positioned in the inferior part of the skull (Figure 3). This is a distinctive feature
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exhibited by members of the catfish group. These organisms have a pair of short snouts
located at the corners of their mouths, which serve as sensory appendages for tactile
exploration (Prihatman 2000).
Patin is considered a more health-conscious food choice due to its relatively lower
cholesterol content compared to meat from livestock. The protein content of catfish meat
increased significantly by 16.58%.
According to Khairuman and Sudenda (2009), the categorization of patin includes
various species. Local patin species, scientifically classified as Pangasius sp., Jambal patin
(Pangasius djambal Bleeker), a widely recognized species, shows potential as an export
commodity due to its habitat in major river systems in Indonesia. Another species is the
turmeric patin, which inhabits major rivers in Riau. There are five species of Pangasius fish
found exclusively in East Kalimantan: Pangasius polyuranodo (known as juaro fish),
Pangasius macronema (also referred to as rios, riu, or lancang fish), Pangasius micronemus
(commonly called wakal or rius caring), Pangasius nasutus (referred to as pedado), and
Pangasius nieuwenbuissii (known as mace fish).
The patin species known as pangasius maintains a kinship with the Siamese patin
species, scientifically referred to as Pangasius sutchi. This relationship is currently evolving
and breeding throughout the Southeast Asian region. Within the scope of biological
classification, patin belongs to in the taxonomic hierarchy, specifically those belonging to the
Order Ostariophysi, Family Pangasidae, and Genus Pangasius (Prihatman 2000). Jambal
catfish, scientifically known as Pangasius djambal, is classified within the broader category
of large catfish. The Pangasius group includes a total of 19 species distributed in various
regions including mainland India, Indochina, Burma, Malaysia, and India (Khairuman and
Sudenda 2009).
In the Indonesian context, there are two different varieties of patin fish, namely
Siamese patin (Pangasius hypopthalmus) and local patin (Pangasius sp). Jambal patin
(Pangasius djambal) has emerged as a well-known local patin species with export potential in
the fishing industry (Prihatman 2000). Jambal catfish, belonging to the genus pangasius,
inhabit various rivers, lakes, and public waters in Indonesia, with noticeable concentrations in
the regions of Jambi, Riau, and Kalimantan. Findings from field evaluations indicate that
certain fish species possess desirable traits for aquaculture and have the potential to reach
body weights exceeding 20 kg. However, the availability of these species still depends on
their capture in natural habitats. The Jambi Freshwater Aquaculture Center has achieved
significant success in its mass production of fry since 2002, leading to the emergence of
14
business prospects for potential expansion. To establish Jambal catfish cultivation as a viable
freshwater alternative commodity for the future.
Patin, one of the freshwater fish species, shows promising development prospects and has
considerable market value. The factors that influence the attractiveness of catfish (Pangasius
sp) cultivation among entrepreneurs are as follows. Catfish have several favorable
characteristics. First, they can be placed in environments that lack running water, which is an
important advantage. In addition, catfish have a low oxygen demand, which further contributes
to their adaptability. In addition, it should be noted that with only six months of rearing,
catfish can reach a length of 35-40 cm (Prihatman 2000).
2.1 Production Potential of Patin Fish (Pangasius sp):
Nguyen et al. (2007) reported that catfish is a major aquaculture commodity in the
Mekong River region of Vietnam. The market name "pangasius" is commonly used to refer to
the species of catfish. In Vietnam, catfish products derived from Pangasius hypopthalmus
catfish are commonly referred to as "Tra", while those obtained from Pangasius bocourti
catfish are known as "Basa". Pangasius bocourti patin variety was initially introduced to the
market, characterized by its white meat and relatively high fat content. Over time, there has
been a shift towards more intensive cultivation of Pangasius hypopthalmus, mainly due to its
shorter cultivation period compared to the Pangasius bocourti variety. The growth period of
Pangasius hypopthalmus, from juvenile stage to harvest size, usually lasts about six months.
This particular fish species exhibits a higher level of resistance to oxygen-deficient
environmental conditions.
Each year, Vietnam demonstrates a remarkable capacity to produce one million tons of
catfish in bulk, thus building its potential to meet the global demand for this product. Demand
in According to Sidatik (2013), the market share in Europe currently requires patin,
accounting for about 25 percent. Lack of competitiveness is an obstacle to the progress of
catfish farming in Indonesia. The high price of fish feed, mainly due to continued dependence
on imported feed, contributes to the rising price of fillets in the market.
Based on statistical data obtained from the Ministry of Maritime Affairs and Fisheries
(MMAF), as depicted in Figure 5 for 2017, catfish production was recorded at 319,967.2 metric
tons. The quantity experienced an upward trend in 2018, reaching a total of 373,262.3 metric
tons, and further showed growth in 2019, reaching a total of 380,130.2 metric tons. The year
2020 witnessed a substantial decline in the quantity of 327,145.8 tons as a result of the
15
profound impact of the Covid-19 pandemic. The projected amount for 2021 is expected to
increase to 332,023 tons.
According to data provided by KKP, there is a consistent trend of increasing catfish
production every year. This growth can still be further increased because the potential for
catfish cultivation is very wide in various environments, including public waters such as
rivers, lakes, reservoirs, swamps, and ponds. The development of catfish farming on a large
scale is very possible. The propaganda campaign effectively aroused public enthusiasm to
cultivate a particular species of fish commonly called catfish. Patin fish farming has
experienced significant development, especially in areas with abundant river resources
(Figure 6).
2.2 Patin Fish (Pangasius sp) Processing
Patin fish is one of the leading freshwater fish and has begun to be cultivated on a
large scale to meet both local and export needs. Patin fish for export is usually processed in
the form of fillets, both "frozen fillets" and "breaded fillets". The main problems often
encountered in the processing of catfish fillets are mud odor, "drip loss" and "oxidative
rancidity" followed by a change in fillet color to yellowish. Some of these technical problems
need attention in developing research on catfish. In addition, catfish is a high-fat fish. The
high fat content in the body of catfish causes the meat of this fish to e a s i l y undergo
oxidation reactions.
Commonly consumed catfish weigh around 500 g to one kg. The parts of the catfish
body that are usually utilized by consumers are divided into several parts according to the
purpose and method of utilization (Figure 7). Yield is the part of the body that can be utilized.
Yield is also the most important parameter to determine the economic value and effectiveness
of a product or material. Yield is used to estimate how many parts of the fish body can be
used as food (Prihatman 2000).
The diagram in Figure 8 provides a comprehensive overview of the distribution of
catfish utilization in various body parts. According to Oktavianawati and Palupi (2017),
various anatomical components of fish such as skin, head, fins, bones, and entrails are
commonly referred to as inedible body parts or body parts that cannot be consumed. In contrast,
fish meat is considered the edible part or the part of the body that is fit for consumption. The
term commonly used to refer to these non-consumable anatomical components is fishery
processing waste, the use of which is currently restricted to fish feed or other forms of animal
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husbandry.
In the processing of catfish fillets, there are by-products that are discarded or utilized
only as raw materials for fish feed, which has a relatively low market value. The waste consists
of various components such as head, bones, tail, belly flaps, remaining pieces, and offal,
characterized by the presence of significant belly fat. The by-products generated during the
processing of catfish fillets have the potential to create a value-added commodity, especially
in relation to the fat component which potentially contains beneficial fatty acids with health-
promoting properties (Suryaningrum 2008).
2.3 Supply Chain
The supply chain (SC) consists of all parties involved, directly or indirectly, in
fulfilling customer demand as defined (Axsäter 2003). This includes suppliers, manufacturers,
distributors, retailers, and customers. In addition, all functions and departments within each
organization are included in the SC. Supply Chain Management (SCM) is the coordination
between all these parties and functions for the benefit of the entire supply chain. Supply chain
is designed for all aspects of operations that include all aspects of procurement, production,
delivery, sales, service, and other endeavors.
Supply chain management involves managing and synchronizing various entities and
processes to produce products and services for customers (Sing 2004). SCM is a central
concept in supply chain management that aims to manage the flow of information, raw
materials, and services from raw material suppliers through factories and warehouses to end
consumers (Chase et al. 2014). Supply chain management involves the integrated planning,
coordination, and control of all business processes and activities in the supply chain, with The
goal is to provide optimal value to consumers (Vorst 2006). Supply chain management also
includes the integration of activities related to materials and services, transformation into
semi-finished goods and final products, and delivery to customers (Chase et al. 2014). The
importance of interaction through good information exchange in the supply chain is highly
emphasized to achieve efficient flow of goods, finances, and information. This interaction
occurs between suppliers, distributors, and customers.
SCM is a series of interconnected actions that aim to transform and flow raw materials
into finished products until they reach the end consumer. This process involves collaboration
between various organizations that work together to ensure the smooth running of the chain of
activities (Pujawan 2017). The organizations involved in SCM involve different types of
17
companies, such as partners or suppliers, manufacturers, wholesalers, retailers, and consumers
(Lewis and Voehl 2020). In this chain of SCM activities, there are various actions performed,
including integration, procurement, production, testing, logistics, customer service,
performance measurement, and so on.
SCM applies a multi-dimensional approach that aims to manage the flow of raw
materials and intermediate goods in the production process within the organization as well as
manage the final product until it reaches the final consumer outside the organization. In each
step, the main emphasis is placed on satisfying customer needs (Blackburn and Scudder
2009). According to the Indonesian National Work Competency Standards Document
(SKKNI) Number 94 of 2019 concerning Logistics, logistics is an integral part of the supply
chain that regulates the movement of goods, information, and money through processes such
as procurement, warehousing, transportation, distribution, and delivery services
(KemenakerRI). All of these processes must be carried out effectively and efficiently, taking
into account the type, quality, quantity, time, and place according to consumer demand, from
the point of origin to the point of destination.
Several research studies have examined various aspects of chain management. For
example, Yolandika and Nurmalina (2016) analyzed broccoli supply chain management at
CV Yan Vegetable and Fruit in Bandung Regency. Sari (2012) focused on analyzing the
supply network and supply control of organic rice. Riwanti (2011) examined the organic
broccoli supply chain at PT Agro Lestari. All of these studies conducted supply chain analysis
using the Food Supply Chain Networks (FSCN) framework, with descriptive analysis
techniques. The FSCN framework is used to assess the six constituent elements that comprise
the supply chain. The elements assessed in the supply chain include supply chain objectives,
supply chain structure, supply chain management, supply chain resources, business processes,
and performance. The determination of marketing channels in the aforementioned studies was
done through purposive sampling and snowball sampling. The results indicate the existence of
a single marketing channel, which is mainly centered on the implementation of supply chain
management activities by a single marketing agent. Marketing channels usually include
various entities such as partner farmers, marketing agents, and retail companies.
2.4 Supply Chain Performance:
Improved supply chain performance has the potential to increase competitiveness in
the supply chain. Supply chain performance measurement plays an important role in assessing
18
the effectiveness of supply chain management, identifying operational challenges, and
developing appropriate improvement strategies. Various studies have been conducted to
investigate the performance of various supply chains. For example, Purba (2015) examined
the performance of cabbage supply chains in Simalungun Regency, North Sumatra. Similarly,
Sari (2012) analyzed the supply chain performance of certified organic rice in Bandung
Regency. Saragih (2015) focused on the performance of the rice supply chain in Cianjur
District. In addition, Sari (2014) assessed the efficiency of catfish supply chain performance
and derived managerial implications for the catfish supply chain in Indramayu.
In a study conducted by Purba (2015), an analysis was conducted to assess the
performance of the cabbage supply chain in Simalungun Regency located in North Sumatra
Province. This study examines the performance of the cabbage supply chain in Simalungun
Regency through the application of marketing margin analysis and farmer share assessment.
Based on the application of the Food Supply Chain Network (FSCN) framework, it can be
concluded that the cabbage supply chain in Simalungun Regency is currently experiencing
less than optimal performance. The goal of integrating quality and optimizing the supply
chain has not been universally pursued by all stakeholders in the cabbage supply chain.
Findings obtained from the utilization of a product traceability tool to track cabbage products,
which serves as a metric to assess food quality, reveal that entities involved in the cabbage
supply chain are unable to provide assurance regarding the quality and safety of cabbage. The
efficiency of the marketing system in the cabbage supply chain in Simalungun District was
rated as satisfactory.
In a study conducted by Sari (2012), an analysis was conducted to evaluate the supply
chain performance of certified organic rice in the Bandung area. This study examined supply
chain performance, focusing on internal and external dimensions. Internal dimensions include
total supply chain management costs, cost of goods sold (COGS), cash-to-cash cycle time,
and percentage of defects. Dimensions External measures include perfect order fulfillment,
order fulfillment lead time, and on-time delivery. The supply chain performance analysis
lasted for two years, followed by subsequent growth measurement. Based on an evaluation of
the performance growth demonstrated by all participants in the supply chain, it can be
observed that the internal dimensions of supply chain performance are below standard, while
the external dimensions show relatively satisfactory performance levels. The certified rice
supply chain showed sufficient success in meeting the needs of end consumers due to the
favorable external dimensions. Among the three results obtained from the analysis used as
inputs for the final analysis, the conclusive findings of this study indicate that the
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implementation of relational marketing results in a good and important impact on supply
chain integration. Supply chain integration has been found to have a favorable impact on
supply chain performance. Both hypotheses in this study were validated. The utilization of
relationship marketing has been observed to have a beneficial and noticeable impact on
supply chain performance through supply chain integration.
2.5 Decision Support System:
An intelligent decision support system called DSS is a computer-based system that
interactively uses data, models, and knowledge expertise to support decision making in
organizations to solve complex problems by combining artificial intelligence techniques,
namely fuzzy systems, neural networks, machine learning, and genetic algorithms, with the
aim to assist users in accessing, displaying, understanding, and processing data more quickly
and easily (Dhar and Stein 1997). This research uses fuzzy systems for decision-making using
fuzzy logic to predict the productivity of catfish farmers in the region under study and the
fuzzy analytic network (ANP) process for selecting the best strategy to increase the
productivity of catfish farming. Fuzzy systems are one of the multicriteria decision-making
techniques that help decision makers make decisions quickly without reducing the quality of
the decision, or can improve the quality of the decision in the same period of time. In decision
making, decision makers define their subjective preferences among different criteria (Kordi
and Brandt 2012).
2.6 Methods and Approaches for Determining Top Processed Food Products:
This superior product can illustrate the ability of an agroindustry to process
commodities, produce products, create value, create employment opportunities, and increase
income. Decision-making on the determination of superior products determines the success of
agro-industry development in the area. Decision-making methods for determining regional
superior products that are widely applied include VIKOR, AHP, ANP, LQ, ELECTREE,
TOPSIS, PROMETHE II, Fuzzy methods. Each method have their own advantages and
disadvantages. TOPSIS is a method that has a simple process, easy to use and programmable,
the number of steps is fixed regardless of the number of attributes. These advantages make
many researchers which uses this method. But besides the simple process, TOPSIS is difficult
to consider attribute correlation and maintain assessment consistency, especially with
additional attributes. Research using this method for determining regional superior products
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includes (Fiati et al. 2019). Besides TOPSIS, an easy-to-use method is promethee. However,
this method does not provide a clear method for determining weights and requires value
assignment. Research conducted by Umam et al. (2018) used the VIKOR method. This
method is part of the Multi-Attibut Decision Making (MADM) concept, which requires
normalization in its calculations.
The method of determining regional superior products that is widely used is the AHP
method. Research using the AHP method in the process of selecting regional superior
products is (Sandriana et al. 2015; Arundaa et al. 2017). In this study, pairwise comparisons
were used to determine the weight of criteria and alternatives. Whereas in the research of
Lamaakchaoui et al. (2018), and Kilic et al. (2013) explained that the selection of the best
complementary products is carried out through the process of evaluating alternatives
according to a number of criteria. The AHP method is widely used because it has various
advantages including being easy to understand, and can be used to solve complex problems.
However, this method also has the disadvantage that there is still a judgment bias that can
affect internal validation (Velasquez and Hester 2013). The shortcomings of AHP can be
overcome by combining with other methods, namely the MPE method. Research by Fasyah et
al. (2016), combined AHP with MPE. The AHP method is used to determine the weight of
superior product criteria and MPE to determine superior product alternatives. The MPE
method can reduce the bias that occurs during expert judgment.
2.7 Traceability:
Similar to other perishable agricultural products, catfish products also require proper
post-harvest handling techniques. One of the recommended strategies and tools to ensure food
quality and safety is the provision of comprehensive information regarding the origin of the
product and the distribution channels through which it passes. This practice helps in
facilitating effective product traceability efforts. The term used to refer to this concept is
traceability system (Raspor 2005). The study conducted by McMeekin et al. (2006) shows
that the main focus of traceability lies in the need to remove food items from the market,
especially those suspected to pose a potential risk to human health. This is mainly achieved
through recall procedures. Thakur and Donnelly (2010) also asserted that traceability serves
as a risk management mechanism for food business organizations, allowing them to initiate
product recalls for items deemed unsafe. With a traceability system, the distribution of
information will occur fairly and evenly to all parties in the supply chain. So that information
21
related to supply and demand will describe the actual conditions and in real time. These
conditions will form a price configuration that is close to ideal.
Traceability is defined as the requirement that a company must have to control and
store information through identity
Traceability is the ability to identify and trace the history, distribution, location, and
application of products, parts, and materials to ensure the reliability of sustainability claims.
According to Christiansen (2016) traceability is also defined as, "Traceability is the ability to
identify and trace the history, distribution, location, and application o f products, parts, and
materials to ensure the reliability of sustainability claims". Furthermore, Farooq et al. (2016)
also described that traceability system is an effort to control the process of a food product and
safety system that is important for sustainable social development in the food industry. This
concept is also defined by Hudrea and Authority (2007) based on several criteria, namely: the
content of the traceability channel, the level of traceability, the usefulness of traceability, the
structure of traceability, and the direction / purpose of traceability itself. Then Blaauboer et
al. (2007) in their empirical research used an exploratory approach regarding decision-making
practices and concluded what factors influence a manager in adopting this traceability system.
Mai et al. (2010) also investigated the benefits of traceability implementation with a case
study on the seafood industry using the cost-benefit analysis (CBA) method to determine the
initial estimate of net benefits and costs distributed along the supply chain network.
The concept of traceability and the application of technology has been growing in the
food supply chain in recent years. This is related to the demands of the times to provide safe
food for consumers. Hobbs (2003) states that a good traceability system in the food supply
chain has the potential to reduce the risks and joint costs of damaged food products. Such as
reducing the likelihood of spoilage, reducing or avoiding health costs, reducing the loss of
labor productivity, reducing the increase in safety costs from the widespread development of
diseases that damage food (March 2007). Langinier and Moschini (2002) in their study
concluded that traceability systems, especially electronic-based ones, have the potential to
improve the efficiency of production, such as reducing ordering, transportation, and storage
costs, as well as assisting the implementation of just-in-time in corporate management.
Improved planning can reduce the cost of the distribution system, expand sales of value-
added products and complement consumer confidence (loyalty) to the product (Golan et al.
2004).
Another reason from an economic point of view for adopting a traceability system is
22
to classify the responsibility of the shared risk of unsafe food product problems resulting in
financial losses to the company, such as: penalties, loss of market, loss of reputation or loss of
brand image. The implementation of traceability systems at the supply chain level has the
potential to reduce costs to downstream actors (such as suppliers) from monitoring the
activities of upstream actors (such as packaging houses) (Hobbs 2003; March 2007).
So far, there is not much scientific literature that examines the cost-benefit of implementing a
traceability system (especially in the supply chain of fresh fishery products), including: Mai et
al. (2010) examined the benefits of traceability in the fish supply chain, namely examining
the traceability system from a cost-benefit relationship that has the potential and provides
benefits in the reduction of costs. Furthermore, Li (2013) explored the cost-benefit in the egg
supply chain, namely examining the case of the egg supply chain based on the actual analysis
of the cost-benefit from the point of view of the supply chain.
The economy produces a traceability system structure, traceability system data and
information, traceability techniques on the egg supply chain network in the Van Beek
business group, and displays profit calculations on the traceability system to increase market
share.
From previous studies from a business perspective, it is concluded that traceability
systems in supply chains generally focus on the need or potential benefits of implementing
traceability systems in the supply chain as well as the cost of instruments implemented in the
traceability of the supply chain network. Based on Mai et al. (2010) and Li (2013), some of
these studies are at the same level, examining electronic-based instruments (such as barcodes
and RFID) in food supply chain studies that focus on individual aspects of the food product
network. So the researcher is challenged in conducting this case study research, especially in
the field of fresh agricultural products in Indonesia which has potential and challenges ahead.
2.8 Previous Research and Research Gaps:
This research is based on a literature review of journals published in the last ten years in
Scopus indexed articles on logistics and supply chains. This study intends to use a
comprehensive approach to research on various issues related to the design and development
of logistics systems. After 188 surveys, it was concluded that logistics research has many
aspects and possibilities to look into in the future. The review further revealed that research
publications on logistics in particular increased after 2011 as a driver of supply chain
improvement and supply chain performance.
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2.9 Research Position and Roadmap
The results of previous research in the range of 2010-2022 show that in the case of
supply chains, there are still several problems including 1) lack of market information; 2) lack
of supply chain transparency; and 3) no ability for tracking and tracing. To achieve good
logistics traceability, unit identification must be traceable and information records must be
detailed as it is an important factor (Pérez Neira et al. 2016). Traceability helps consumers
and producers know who the supplier is and how. In an effort to maintain the quality of
agricultural products and to support government policies in food availability programs,
logistics traceability can be an alternative strategy that can be used to improve the quality of
agricultural products.
Framework of Thought:
Catfish is a commodity that has high economic value, and has an increasing demand
trend. Patin fish has many benefits for humans because it has complete nutritional content.
With a large area of catfish cultivation area, Indonesia is currently able to produce and meet
the world's increasing demand for catfish products. One solution to increase the export value
of catfish products is to develop a catfish agro-industry. The development of the patin
fisheries agro-industry is believed to increase added value, absorb labor and increase
community income. This development can also increase the absorption of domestic catfish
commodities and increase the variety of types of processed catfish products. The development
of this agro-industry requires cooperation from all interested actors to achieve common goals.
Time and Place of Research:
The research period starts from September 2020 to August 2022. As for the catfish
processing industry, the area closest to the market share will be selected (in this case: Fish
Processing Industry in Karawang and Purwakarta - adjacent to Jakarta). While the research
location for the production area is in Purwakarta Regency and its surroundings as the closest
source of raw material for catfish to the industry under study. The other regions are Pringsewu
Regency, Lampung Province and Tulungagung Regency, East Java Province. These two
regions were chosen because they are also the source of raw materials for catfish. Especially
for Tulungagung Regency, this region is already known as a patin fish producing area with
large quantities and quality that meets the requirements for export patin meat.
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SITUATIONAL ANALYSIS OF CATFISH AGRO-INDUSTRY SUPPLY CHAIN:
4.1 Abstract
This study aims to analyze the situational supply chain of Pangasius.sp agro-industry
by applying the soft system methodology (SSM) approach developed by Checkland (1999).
Six stages of SSM have been carried out, and successfully built a conceptual model. The
conceptual model built consists of eight activities. The activities in question are (1) increasing
the productivity of the Pangasius.sp industry, (2), data mining to retrieve data in predicting
demand, (3) developing collaboration models and optimizing inventory, (4) developing
intelligent decision support systems, (5) developing digital platforms, (6) Increasing added
value, (7) Increasing efficiency and responsiveness to buyers, and (8) Increasing supply chain
performance.The conceptual model has been compared to real-world systems through gap
analysis which decomposes real-world systems into conditions for implementing actions,
tools, and actions that have been taken (current practice). The three recommended corrective
actions for the development of the Pangasius.sp agro-industry are: (1) increasing added value,
(2) developing and implementing a supply collaboration model, and (3) building and
implementing the Pangasius Spatial-DSS digital platform. The SSM implementation stage
which has not been carried out in this study, will be continued in future research. This study
recommends that the government provide assistance and issue policies to support the
development of the Pangasius.sp agro-industry supply chain which has the potential to
become a competitive product that supports the making of Indonesia 4.0.
4.2 Introduction
Patin fish is a group of freshwater catfish with white fish color and relatively easy to
cultivate. In Indonesia, there are at least 13 species of catfish and many are found in the local
market in limited volumes because they are caught from nature and have no economic value
nationally. In the global market, there are three types of patin fish that have been cultivated
industrially, namely Pangasius bacourti, P. hypophthalmus and P. sutci. In Indonesia, P.
hypophthalmus is the most widely cultivated species (Prihatman 2000; Cholik et al. 2005).
Soft systems methodology SSM is an approach that organizes unstructured, complex, elusive
problems (Berge and Dahl 2011; Ngai et al. 2012; Soemartono 2014; Antunes et al. 2016;
Nurani et al. 2018), and is a system of interactions between human and technological
25
components (Beheraa et al. 2015). SSM divides the way of looking at the real world and the
existing system, the model is considered as a learning tool rather than a tool to predict, and an
organized exploration of the situation. The implementation was carried out by Forum group
discussion (FGD) (Soetara et al. 2018).
SSM consists of human activities, as it involves many stakeholders with different
viewpoints, interests and understandings (Novani et al. 2014). SSM offers a systemic
framework based on logical stages (Novani and Mayangsari 2017). Technology issues and
decision-makers are independent, with multiple worldviews, and conflicting goals with regard
to stakeholders (Antunes et al. 2016). SSM cannot measure and assess the likelihood of
change by itself over time (Novani and Mayangsari 2017).
From the results of the research search, the implementation of SSM in: power plant
construction (Beheraa et al. 2015), patient scheduling in hospitals (Berge and Dahl 2011;
Emes et al. 2018), coffee agro-industry (Fadhil et al. 2018), wood processing industry
(Soetara et al. 2018), tuna fishing business (Nurani et al. 2018), educational institutions
(Mehregan et al. 2012; Soemartono 2014), batik industry (Novani et al. 2014), high
techonology companies (Liu et al. 2012), and textile industry (Ngai et al. 2012).
It is concluded that SSM is a systemic approach that requires in-depth discussions such as
FGDs in describing complex and unstructured problem situations, to be poured into real-
world data, which will be used as a database for the pangasius agro-industry supply chain. In
the SSM approach, the behavior of real-world systems is modeled in systems thinking into a
conceptual model to support problem-solving decision making based on root definition
through CATWOE elements.
SSM in designing the agromaritime supply chain of the pangasius industry is defined
as a system-based method that is built holistically without reducing based on real-world
representations of stake holders that interact with each other (starting from seed suppliers,
pangasius processing industries, pangasius downstream product processing industries,
shippers, distributors, retailers, agents, consumers, and waste processing industries) to
generate added value and increase profits, through training data, provided by humans to the
system from real-world databases, so that the system can provide efficient and responsive
support to humans, and the waste processing industry of processed catfish products) to
generate added value and increase profits, through training data, which is provided by humans
to the system from the real world database, so that the system can provide efficient and
responsive support to humans in making decisions based on the training that has been given to
26
the system.
4.3 Methods
The stages of this method were developed by Checkland (2000). The stages are (1)
Examine the unstructured problem, (2) Express the problem situation,
(3) Building a problem definition related to the problem situation, (4) Building a conceptual
model, (5) Comparing the conceptual model with the problem situation, (6) Determining
feasible and desirable changes, (7) Taking corrective action on the problem.
This research limits its implementation to stage 6, for stage 7 can be implemented in future
research. The stages of SSM in supply chain design for the development of catfish agro-
industry are presented in Figure 18. The second stage is expressed with a rich picture. Rich
picture is a description of the situation, including the interests of actors in the supply chain
network, and the interrelationships between actors, the roles between actors, issues, areas of
possible conflict, and conflicts.
4.4 Results and Discussion
The assessment of complex, problematic and unstructured issues was based on visits
and observations to the research field. The first in-depth visit and interview was conducted to
the catfish processing industry at PT Kurnia Mitra Makmur Purwakarta (KMMP), located on
Jalan Cinta Karya Kopo, Purwakarta Regency. It was found that PT KMMP also has fostered
ponds in Jatiluhur Reservoir and Cirata Reservoir, but unfortunately due to the Covid 19
pandemic, many fostered ponds switched to other types of fish.
The second visit was conducted at a catfish farmer in Pringsewu, Lampung Province
who often sends his harvest to Purwakarta and Jakarta. Furthermore, we also conducted a
field visit to Tulungagung Regency, as the best patin fish producing area in Indonesia that has
met export quality standards.
The assessment was conducted by describing the roles of stakeholders and aspects
along the patin fish agro-industry supply chain network. There are seven actors in the patin
fish agro-industry supply chain network, patin fish farmers, collectors, fish processing units,
fish processing industries, exporters, distributors and retailers.
This research uses primary data collected by conducting planned-structured interviews and
filling out questionnaires. Primary data is data obtained or collected directly by researchers
from the source. Interviews were used to obtain additional information that was not captured
in the questionnaire. A questionnaire is a series of questions related to a particular topic given
27
to a group of individuals with the intention of obtaining data. The questionnaires distributed to
respondents had closed-ended questions that provided more structured responses to facilitate
real recommendations. In general, the questionnaire contained questions about general
information, questions about the determinants of competitiveness, and questions about
conditions. The questionnaire was given to expert respondents who are competent and know
the ins and outs of the catfish fillet industry.
