Journal of Agroindustrial Technology
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LIFE CYCLE ASSESSMENT OF WET NOODLES PRODUCTS AT MIE CEPET IBU RUBIYEM MICRO SMALL MEDIUM ENTERPRISE (MSME) BANDAR LAMPUNG CITY
Full text linkWet noodles are a type of noodle that undergoes a boiling process before being marketed. Activities in the wet noodle production process can produce waste and emissions that have the potential to cause environmental impacts. The resulting environmental impacts include greenhouse gas (GHG), acidification, and eutrophication. The amount of environmental impact produced can be determined through the life cycle assessment (LCA) method. This research aimed to measure the potential impact of GHG emissions, acidification, and eutrophication, and provide recommendations for alternative improvements to reduce the resulting emissions. The scope used was gate-to-gate and the functional unit was1 kg of wet noodles. The environmental impact analysis that has been carried out showed that the amount of GHG, acidification, and eutrophication were 4.72x10-1 kgCO2eq, 1.82 x 10-5 kgSO2eq, and 5.97 x 10-3 kgPO43-eq, respectively. Recommendations for alternative improvements that can be made are (1) Substitution for the use of renewable energy, namely off-grid solar power plants (SPE), which can reduce GHG emissions by 0.19%, acidification by 63.1%, and eutrophication 79.5%. (2) The use of electric vehicles (EV) as the main energy source from off-grid solar power plants can reduce GHG emissions by 0.02% and acidification by 3.64%. (3) Converting wastewater into liquid organic fertilizer (LF) can reduce GHG emissions by 78.4% and eutrophication by 1.12%, and (4) Selling solid waste (SSW) to livestock feed can reduce GHG emissions by 19.2% in all processes.
Keywords: acidification, eutrophication, Greenhouse gases (GHG), Life Cycle Assessment (LCA), wet noodle
CUSTOMER SEGMENTATION WITH K-MEANS ALGORITHM AND BUSINESS STRATEGY BUSINESS INTELLIGENCE IN VEGETABLE ONLINE RETAILING
No full textMost MSMEs still have obstacles to growing and developing at the business level. Applying a business intelligence system is expected to assist in making appropriate and quick business decisions so that MSMEs can grow and develop. This research aimed to determine customer segmentation based on product clustering that consumers demand. In addition, this study aims to determine the benefits of business intelligence in providing business performance information to make decisions. This research uses the k-means algorithm for clustering. Business intelligence uses Power BI software for visualisation. Based on the results of analysing product clustering with the k-means algorithm, the optimal number of clusters is 2 (k = 2). Determination of the value of k = 2 uses an average centroid distance of 121,624,275,127, and validation of the minimum DBI value = 0.052. Based on the clustering results, cluster 0 (28%) and cluster 1 (72%) are two consumer segments. Insights on the sales dashboard are daily sales fluctuations, the dominance of certain products in demand, and products with low sales. Strategy initiatives for the long term are customer segmentation for more personalized promos, focus on subscriptions and repeat orders, optimising digital marketing, and the use of predictive analytics to forecast sales trends. On the dashboard of production, order, and stock, information, such as daily production tends to exceed orders, leading to overstock, while orders fluctuate inconsistently. The key challenges are unbalanced production and demand, overstock on certain products, unstable orders, and underproduced products.
Keywords: business intelligence, data analytics, k-means algorithm, Micro Small Medium Enterpris
SYSTEM ANALYSIS AND DESIGN PRODUCTION OF EDIBLE BIOFILM FROM MINT LEAF ESSENTIAL OIL AS AN ANTIMICROBIAL
No full textPoor packaging can definitely contribute to food spoilage, reducing food quality and shelf life. Active packaging using edible biofilm with antimicrobial essential oils can inhibit microbial growth and extend product freshness. The purpose of this study was to classify edible biofilm products to determine their quality and predict proper drying conditions. The method involved system modeling using Unified Modeling Language (UML) and Business Process Model and Notation (BPMN) to map the production process from raw material handling to industrial scale manufacturing. Subsequently, machine learning models were applied: the Decision Tree model for classifying product quality including physical, mechanical, and antimicrobial properties and Ordinary Least Squares (OLS) linear regression for predicting drying parameters. The research steps consisted of creating system models to improve clarity and team alignment, collecting relevant data on elongation, tensile strength, moisture content, and antimicrobial activity, then applying the Decision Tree for quality classification and antimicrobial categorization into four levels. OLS regression was used to model the relationship between drying conditions and final moisture content. Results demonstrated that UML and BPMN modeling enhanced understanding and consistency in production flow. The Decision Tree classified edible biofilm quality into three categories with 80.5% accuracy and antimicrobial ability into four inhibitory levels with 95% accuracy. The OLS regression predicted drying outcomes with 64% explanatory power and statistical significance (p-value < 0.05). This study contributes to intelligent packaging development by integrating system modeling and machine learning, enabling early classification a nd drying prediction to improve quality control, efficiency, and reliability in active food packaging.
Keywords: antrimicobe, decision tree, edible biofilm, linear regression, use cas
FURNITURE INDUSTRY GREEN SUPPLY CHAIN SUCCESS FACTORS: A SYSTEMATIC LITERATURE REVIEW
Full text linkIn recent years, Green Supply Chain Management (GSCM) has gained significant attention due to the challenges posed by climate change, primarily driven by human activities and harmful emissions. The furniture industry presents considerable potential for GSCM adoption but faces challenges, including high costs, low environmental awareness, and limited government support. This study aimed to identify critical success factors (CSFs) for GSCM implementation in the furniture industry. Using a Systematic Literature Review (SLR) methodology, articles from Scopus and Google Scholar were examined to identify key CSFs. Six CSFs were found management commitment, investment in technology and collaboration, stakeholder involvement, environmental sustainability strategy, environmental regulations and incentives, and performance assessment and monitoring. The study highlighted the importance of a comprehensive approach, outlining essential steps for GSCM implementation, such as strategy development, green practice adoption, and ongoing monitoring and evaluation. Additionally, it emphasized integrating green purchasing, internal environmental management, and forming collaborative partnerships with stakeholders. Regular evaluations were critical to track progress, align with sustainability objectives, and identify areas for improvement. The study contributes to the GSCM literature by offering practical insights and recommendations for furniture companies, including conducting a SWOT analysis, setting clear sustainability goals, collaborating with eco-friendly suppliers, and securing top management support. These findings provide valuable guidance for the furniture industry to achieve sustainability, improve efficiency, and enhance competitiveness in the global market.
Keywords: critical success factors, furniture industry, Green Supply Chain Management (GSCM), Systematic Literature Review (SLR
ENVIRONMENTAL ASSESSMENT STUDY BASED ON THE LIFE CYCLE OF SANJAICHIPS PRODUCTS IN PAYAKUMBUH, WEST SUMATERA
No full textThe growing productivity of the Sanjai chips agro-industry contributes to increasing emissions along the production process. This study aims to evaluate the environmental impact of Sanjai chips production using the Life Cycle Assessment (LCA) method. The assessment follows LCA stages: goal and scope definition, life cycle inventory, and impact assessment. The system boundary is gate-to-gate, focusing on the production stages: peeling, washing, slicing, frying, seasoning preparation (balado), mixing, and packaging. The functional unit is 1 kg of Sanjai chips. For each kilogram of product, inputs include 2.01 kg of cassava, 0.35 liters of cooking oil, 9.63 liters of water, and 2.61 kg of firewood, with 9.63 liters of wastewater produced. Environmental impacts were analyzed using SimaPro 9.4.2 software and the CML-IA Baseline method. Results show that 1 kg of Sanjai chips contributes to Global Warming Potential (GWP) of 1.3619 kg CO₂ eq, Acidification Potential (AP) of 0.0131 kg SO₂ eq, Eutrophication Potential (EP) of 0.0740 kg PO₄ eq, and Ozone Layer Depletion Potential (ODP) of 8.09E-07 kg CFC-11 eq. The frying stage is the primary hotspot, contributing 78.7% of total impacts, mainly due to cooking oil use. It is recommended that future research expand the system boundary to a cradle-to-grave scope and include social and economic dimensions to achieve a more holistic sustainability assessment.
Keywords: environmental impact, life cycle assessment, sanjai chips, simapr
DEVELOPING A QUALITY STANDARD FOR BATIK WITH NATURAL DYES: A PROPOSAL TO IMPROVE BATIK COMPETITIVENESS
Full text linkThis study aimed to develop quality standards for batik using natural dyes to enhance the competitiveness of the product. The method used was the FACTS approach, which included stakeholder analysis, standard comparison, and standard testing. Data were collected through interviews of 25 respondents consisting of government officials, producers, consumers, and experts. The stakeholder analysis involved defining batik with natural dyes, setting quality parameters, gathering testing methods, and technical analysis using the Zachman Framework. Subsequently, a comparison was made between the proposed standards and international standards such as OEKO-TEX® Standard 100 and the Ecological and Recycled Textile Standard (ERTS). Standard testing was then conducted by integrating inputs from stakeholders on the drafted standards. An analysis of willingness to pay was conducted to identify the level of customer readiness to pay more for certified environmentally friendly batik products. Survey results showed that out of 97 respondents, about 87% were willing to pay an additional 20-25% for batik using certified natural dyes.
Keywords: Batik, natural dyes, quality standards, sustainability, Zachman Framewor
DEVELOPMENT POTENTIAL OF SMALL AND MEDIUM ENTERPRISES BASED ON SPATIAL CONCENTRATION IN SARBAGITA AREA
No full textSeveral studies have found that disparities still exist between regions within the Sarbagita area. As a driving force for the regional economy, the role of Small and Medium Enterprises (SMEs) is important to be developed based on their potential in solving these problems. This study aimed to identify the potential of each type of SME based on aspects of specialisation and spatial concentration using the Krugman Index, Hoover Ballasa Index, and LISA analysis methods. The data used in this study is based on the number of SME units in each area of the Sarbagita Area which are grouped based on eight categories of SME types. The research found that the specialisation categories of SME types from highest to lowest, namely: iron and steel; non-metallic mineral; wood goods; textile and apparel; printing and publishing; basic chemical; fertilizers, and plastic equipment, metal goods; food and beverage. The results of this study also show that there are concentrations and spatial relationship patterns of each type of SME with High-High (H-H), High-Low (H-L), Low-High (L-H), and Low-Low (L-L) patterns. This spatial information is expected to be a reference for directing SME development strategies in the Sarbagita area.
Keywords: small and medium industry; spatial concentration; Sarbagita are
RISK MANAGEMENT MODEL FOR RAW MATERIAL PROCUREMENT AND PRODUCTION PLANNING IN THE COFFEE AGROINDUSTRY: A CASE STUDY IN KALIBARU, BANYUWANGI
No full textThe coffee agroindustry encounters significant risks due to its intricate business processes and the involvement of multiple stakeholders. These risks, particularly in raw material procurement and production planning, threaten business sustainability and include inconsistent raw material quality and quantity, fluctuating prices, limited resources, and inefficiencies in decision-making. This study analysed business processes, identifies risks, and develops a risk mitigation model for the coffee agroindustry in Kalibaru, Banyuwangi. Business process analysis employed descriptive methods focusing on supply chain mechanisms and drivers, complemented by supply chain management metrics. Risk management utilized the House of Risk (HOR) Phase 1 and 2 framework. Results revealed a refined business process model emphasizing efficiency and integration, alongside 20 risk events and 20 risk sources in both procurement, and production planning. Eleven priority risk sources were identified for procurement, and ten for production, forming the basis for targeted mitigation strategies. Key mitigation actions include training farmers in Good Agricultural Practices (GAP), partnering with research institutions for procurement and implementing preventive maintenance of processing equipment for production. These strategies enhance resource management and industry competitiveness.
Keywords: business process, coffee agroindustry, risk mitigation, procurement planning, production planning
SCHEDULING PLANNING SOYBEAN COMMODITY DISTRIBUTION ACTIVITIES AT CV XYZ USING DISTRIBUTION REQUIREMENT PLANNING (DRP) METHOD
Full text linkCV XYZ is a company engaged in the distribution of soybean commodities, located in Tangerang Regency. The company distributes its products to five retail outlets across the Jabodetabek area using two operational vehicles. Currently, CV XYZ faced issues with distribution scheduling due to the lack of a fixed policy, leading to occasional increases in delivery frequencies caused by insufficient stock and an inefficient existing scheduling system. As a result, the fulfillment rate of retail demands only reached 93% of the company’s target of 99%, creating a 6% gap that the company aims to address. To resolve this issue, a new distribution scheduling plan was developed using the Distribution Requirement Planning (DRP) method. Distribution Requirement Planning (DRP) method consists of four stages: first Netting for the process of calculating the amount of net requirements, second Lotting for the process of calculating the ideal order quantity, third Offsetting to determine the order plan, and finally the fourth explosion for the process of calculating gross requirements in distribution. The results of the new plan show an increase in the fulfillment rate of retail demands to 99.8%. Additionally, total distribution costs were successfully minimized, decreasing from Rp 593,980,120 to Rp 551,934,498, resulting in a saving of Rp 42,045,622 or approximately 7% of the previous total distribution costs.
Keywords: inventory, scheduling, distribution, distribution requirement planning (DRP