bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of sustainable coffee processing wastewater treatment system using K-means clustering algorithm
Authors: Laili N , Indrasti N S , Wahyudi D 
Published: August 2022

Abstract
Coffee processing wastewater has a COD of 3100-14343 mg per liter and a BOD of 5000-35000 mg per liter that will cause water pollution and may contaminate the water ecosystem if it is dumped directly into the environment. The literature shows that coffee processing wastewater requires special treatment to reduce the negative impact on the environment. This study develops a wastewater treatment system model capable of identifying sources of emissions and pollutants to increase the effectiveness of pollutant reduction. This study aims to analyse the coffee processing wastewater treatment system, define the most significant attribute, and develop a coffee processing wastewater treatment design using a K-means clustering method. A relief-feature selection method was used to analyze the most significant attribute of coffee processing wastewater related to certain specific wastewater treatment needed. This study used an unsupervised machine learning technique to develop clustering based on the most significant attribute of coffee processing wastewater using the K-Means method. The K-means clustering result shows five coffee processing wastewater treatment clusters based on BOD and Acidity. For clusters with BOD < 25.000 mg per liter: biological and chemical wastewater treatment will be applied through coagulation, adsorption, filtration, bio-filtration, and anaerobic microbial processes to separate pollutants. For clusters with BOD >25.000 mg/l: physical wastewater treatment will be applied through electro-coagulation.
Integrating supply chain risk management in agriculture: A case study of East Kalimantan granary
Authors: Profita A , Kuncoro D K R 
Published: August 2022

Abstract
Managing risk in the agricultural supply chain is more complex and challenging than other commodities due to its perishable characteristic and production nature, primarily based on unpredictable weather conditions and uncontrollable biological processes. This study analyses the agricultural supply chain risk in Penajam Paser Utara Regency, one of the granaries for East Kalimantan Province. A total of 25 risks have been identified and prioritized by fuzzy FMEA, where these risks are divided into eight supply risks, 12 manufacturer risks, and five demand risks. The mitigation strategies give five options: (1) branding image, (2) market penetration, (3) partnership, (4) preventive maintenance, and (5) production capacity to choose from. Using the Analytical Network Process (ANP) method, the priority order of mitigation strategies is to adjust production capacity weighing 35,5%.
The analysis and design of independent smallholders FFB palm oil supply system to support traceability of CPO product derivatives
Authors: Falgenti K , Hambali E 
Published: August 2022

Abstract
The mandatory biodiesel program in Indonesia requires more Crude Palm Oil (CPO). POM requires FFB from independent smallholders to maximize CPO production. POM usually separates FFB supply based on internal and external sources. However, the segregation did not identify the farmer and farm location source of external FFB. This study aims to analyze and design an FFB supply system from the independent smallholder’s channel by identifying the farmers’ and farms’ source of FFB in every batch production of CPO and identifying Farms and farmers to support a traceability system of CPO derivative products. The New FFB delivery system services will be run on a cloud platform. The services are truck allocation, weigh scheduling, weighing, sorting, and CPO production. The Method for developing FFB delivery service using a system approach and System Development Life Cycle (SDLC). This research only discusses the analysis and design phase. The research output is a new design delivery system of FFB with Block Appointment Scheduling (BAS) for quality control of FFB to produce high-quality CPO. The simulation of BAS and CPO production is running based on the business process at PT. RSI.
Investigating the participation mode in agro-based GI development programmes in Indonesia: A lesson learnt from three case studies
Authors: Kusnandar K , Indraprahasta G S , Sari K , Dinaseviani A , Prihadyanti D , Aziz S A , Jayanthi R , Pitaloka A A 
Published: August 2022

Abstract
Geographical Indication (GI), a product labelling tool based on a specific geographical origin, has gained traction in many developed countries. Meanwhile, in Indonesia, GI has been put on the radar screen since the 2000s, marked by the establishment of government regulation at the national level, followed by various programmes to assist communities to pursue GI labels for their unique local products. As GI is a community-based intellectual property, the participation of local actors is considered important in GI development to pursue sustainable agroindustry. To this end, this paper addresses the question of to what extent have the GI development programmes in Indonesia pursued the participation of local actors? In doing so, we focus on dissecting three agro-based GI products located in three different areas in Indonesia as case studies. Interviews with some representatives of the Community of GI Protection (MPIG) and the local business community from each case were conducted, supported by the information received from government actors, academics and practitioners. The degree of participation framework that consists of 1) informing, 2) consultation, and 3) empowering is used to analyse the three cases to answer the paper’s question. This paper found that the GI-based agroindustry development in Indonesia still largely focuses on pursuing formal institutions of GI labelling while empowering local actors still received little attention. Further studies are necessary to explore the effect of GI development programmes on local farmers’ situations.
Sustainable sugarcane supply chain performance assessment: A review and research agenda
Authors: Mursidah S , Fauzi A M 
Published: August 2022

Abstract
Supply chain sustainability has become a popular concept used by several businesses to increase business competitiveness. However, there is no standard for measuring supply chain sustainability and business competitiveness. The objectives of this research were to analyze and criticize existing methods for supply chain sustainability assessment and develop a new framework for future research. This study reviewed 151 scientific articles related to supply chain sustainability assessments from 2004 to 2020. The results show that many techniques are used for sustainability assessments. However, no single technique can comprehensively measure supply chain sustainability. Therefore, a new robust technique that accommodates complex data in a sustainable supply chain is required. The technique to be developed is a machine learning technique because it can accommodate multi-criteria problems with various nonlinear relationships. This research is a case study of the sugarcane agroindustry supply chain. The supply chain of the sugarcane agroindustry faces various sustainability issues caused by negative environmental impacts. The analysis results show that using machine learning techniques to assess sustainability for the sugarcane agroindustry’s supply chain has great potential to be developed. Machine learning applications for this assessment can also be used to monitor the performance of organizations. Thereby organizations can enhance their sustainability performance through data-driven decision-making.
A predictive analytics of production planning model for yield performance in organic broiler industry using ensemble learning
Authors: Lastanto J A , Djatna T 
Published: August 2022

Abstract
The Organic broiler production requires farmers to use organic herbs without growth promoters or other chemical contents. The problem is uncertain production yield performance results. On the other hand, farmers want good performance results to increase income and minimize loss of production. Therefore, machine learning can support organic broiler production decisions. Meanwhile, a single prediction model has a lower level of accuracy, so a combination of various prediction models is needed. The paper aims to find an accurate performance of the yield production prediction model and has a high degree of accuracy using ensemble learning techniques. The attributes that affect performance as input include corn, rice bran, soybean meal, coconut cake, fish meal, and herbs. Then we evaluate the model using the confusion matrix. The result shows that ensemble learning has succeeded in predicting the yield performance of organic broilers with an accuracy of 98.96%. The evaluation model showed that accuracy was 87.98% in the data train and 94.23% in the data test.
The challenge of bamboo craft industry in the VUCA era
Authors: Nindiani A , Suparno O , Machfud  , Anggraeni E 
Published: August 2022

Abstract
Most of the bamboo craft industries in Indonesia are micro, small, and medium enterprises (MSMEs). They process bamboo as the raw materials into various products marketed domestically and abroad. The bamboo craft industry is categorised as the creative industry, providing value to intellectual property sourced from creativity based on cultural heritage, science, and technology. Bamboo is processed into different products to meet human needs and desires. This paper describes the profile of the bamboo craft industry in Indonesia and its problems. A literature study was carried out supported by interviews with stakeholders and observations. Nowadays, the bamboo craft industry faces VUCA (Volatility, Uncertainty, Complexity, Ambiguity). The unstable business environment, uncertain market competition due to substitute products and imported products’ entry, the increased complexity of business conditions, and unclear situations often colour the business cycle. These conditions cause the bamboo craft industry to experience vulnerability in maintaining business continuity. The challenge faced by the bamboo craft industry is to be resilient to survive and even grow amid unexpected disruptions by being adaptive in meeting business cycle dynamics.
How digital platform changing people way to buy FMCG products
Authors: Mulyawan A , Alamsyah Z , Marimin  
Published: August 2022

Abstract
Current technological developments have brought about major changes in consumers’ views when buying household products. Technological advances due to the Internet have disclosed various opportunities in business. Household products in fast-moving consumer goods (FMCG) are those that can be applied to digital platforms in business processes. This study aims to determine how digital platforms change customer behavior due to many factors that are affected by technological development. This research also provides a perspective on how customers decide to buy FMCG from a digital platform. The results show that brand awareness, audiovisual social media advertising, ease of access, and reviews from other consumers affect how consumers buy options. Advertising in social media, electronic word of mouth (e-WOM), customer engagement, positive influence, brand awareness, and sales enhancement are major factors that make digital platforms profitable for suppliers or manufacturers as a new business model
A system analysis and design for mobile digital business traceability at a food manufacturing
Authors: Djatna T , Koswara M F , Kuncoro D K R 
Published: August 2022

Abstract
As one of the multinational biscuit manufacturers in Bekasi, the X company is supported by Business Planning and Control System (BPCS) for the traceability in their supply chain. Although it has covered upstream and downstream supply chains, the company’s traceability is still considered ineffective. It is seen from the results of the company’s evaluation through the mock recall procedure. The research aims to identify the requirement of a mobile traceability system for mock recall procedures, design components of mobile traceability system prototype based on an android system, and validate the mobile traceability system and performances. The business process analysis in this research is using Business Process Model and Notation (BPMN) to trace the system. The results show that traceability is still less effective because activities are done manually, which takes much time. Therefore, the system is developed with cosine similarity calculation and verification of the model and validation of the black box. The verification and validation of the system against its needs show that the mobile traceability system can improve the effectiveness of company traceability and can be applied in the internal supply chain.
Logistics network configuration: The solution for quality-related problems in long-distance transportation of mango in Indonesia
Authors: Kailaku S I , Arkeman Y , Purwanto Y A , Udin F 
Published: August 2022

Abstract
Indonesia was ranked 46th out of 160 countries in the Logistic Performance Index 2018, below most ASEAN countries. Indonesia’s dependence on inter-island interconnections causes high container handling costs. Mango is one of Indonesia’s superior fruits. While almost every province in Indonesia produces mango, the major mango producers are mainly in Java Island and Eastern Indonesia. This production distribution leads to the demand to distribute mango from the production centers to other areas, which raises concerns about quality preservation. A well-designed logistics network configuration is imperative for a perishable food supply chain such as mango due to its influence on material flow balance, postharvest losses, costs, and response capacity. This study aims to review the problems of mango transportation in Indonesia and the thriving technology in transportation conditions monitoring and propose a formulation to develop a logistics network configuration. The presented paper discusses a multi-objective problem of customers maximization, postharvest losses rate minimization, and transportation cost minimization. We elaborate on the challenges with implementing multimodal transportation for perishable products, requirement analysis for the stakeholders, and transportation conditions monitoring. Ultimately, we develop a surplus model following the multi-objective problems considering the constraints of the harvest season, production volume, and distance from production centers to buyers’ locations. Field data and secondary information consist of material flow behaviour and market competition. The logistics network configuration models the material flow balance, postharvest losses, costs, and response capacity.
Assurance information systems design for blockchain - based micro, small and medium enterprises in Indonesia
Authors: Novianti D , Haditjaroko L , Almunawar M N 
Published: August 2022

Abstract
Halal Product Guarantee is legal certainty regarding the halalness of a product as evidenced by a halal certificate. Regulations regarding halal certificates are carried out based on Law Number 33 of 2014 concerning Halal Product Assurance (“Law 33/2014”). This provision requires all products to have a halal certificate. This certificate is hoped to add the value of the product to be absorbed by the market more. However, the problem is that not all business actors or industries can implement halal guarantees. Micro, small, and medium enterprises (MSMEs) have weaknesses in the documentation and halal traceability. These two things become one of the criteria for the halal assurance system to get a halal certificate. We need a computerised information system that can help SMEs document and trace. Meanwhile, blockchain technology is needed for documentation transparency, which effectively keeps track of information and transactions. The system is proven to be safe and transparent. Because when the transaction takes place, all parties can see public access.
An analysis and design of fresh milk smart grading system based on internet of things
Authors: Habsari W , Udin F , Arkeman Y 
Published: August 2022

AbstractThe grading of fresh milk affects the quality classification in the dairy industry. This study aims to analyze and design a smart grading system using machine learning models to classify the grade of fresh milk. Business process analysis helped understand the capturing steps as the main elements, such as the smart grading system. The result of the requirement analysis showed how smart the grading system involved stakeholders. The machine learning model can help the Internet of Things system classify goods or services.Artificial Neural Networkand K-means were designed to classify and group indicators of fresh milk quality. The variables used in this study consisted of pH, temperature, odour, turbidity, colour, fat, and taste values. The data were taken from the upstream dairy industry SAE Pujon. The classification result of fresh milk grades using ANN consisted of three low, medium, and high grades. The accuracy value of the classification obtained is 98.74%. The attributes used for grouping were temperature and colour. The best clusterization that used K-Means is the third cluster. Based on the data analysis, the smart grading system made users save time knowing the grade of fresh milk easier.
Cavitation and strain-induced transformation: the austenite phase behavior in a soft martensitic and an austenitic stainless steel
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Authors: Brunatto Silvio Francisco , Cardoso Rodrigo Perito , Santos Leonardo Luis 
Published: August 2022

Abstract
In this work the behavior of the austenite phase at the surface of a low-carbon martensitic stainless steel and an austenitic stainless steel subjected to cavitation through ultrasonic vibration tests in liquid phase was studied. Emphasis was given to the behavior of two distinct types of austenite, in the case the reversed austenite of the as-tempered ASTM CA-6NM martensitic stainless steel, and the thermally-stable austenite of the solution-treated AISI 304 austenitic stainless steel. The evolution of phases fraction at the studied surfaces by XRD technique was characterized by two ways. Firstly, cavitation test intercalated with XRD measurements as a function of the test time was carried out. In the sequence, an indirect measurement technique comprising the use of Vickers indentation and controlled material removal by polishing, also intercalated with XRD characterization along the incubation period of both steels was used. This procedure was strong enough to determine the mechanism that precedes the erosive wear defining the incubation-acceleration stages transition and the cavitation-affected depth presenting γ(austenite)→α′(martensite) strain-induced transformation in the material microstructure, measured from the surface of the tested region into the interior of the substrate bulk of each studied steel. Such mechanism covers deformation of the steel matrix and strain-induced transformation of the austenite phase at the surfaces subjected to cavitation, strongly influencing the beginning of the significant mass loss process for both low-carbon stainless steels studied here.
Performance of dye-sensitized solar cells extracted dye from wood apple leaves
Authors: Alhorani Samah , Kumar Sarvesh , Genwa Mahaveer , Meena P L 
Published: August 2022

Abstract
In this work, wood apple leaves dye has been extracted, characterized, and examined as a potential photosensitizer for dye-sensitized solar cells (DSSCs). The dye was extracted in an ethanolic medium from the fresh wood apple leaves and characterized using thin-layer chromatography (TLC), ultraviolet-visible (UV-Vis), and Fourier transform infrared (FTIR) spectroscopy. The current density-voltage (J–V) characteristics measurements were performed on the two assembled DSSCs for 1–22 days using fresh and seven days old extracted dye. The characterization results revealed that the extracted dye mainly contains the compound of carotenoids (neoxanthin), chlorophyll a, chlorophyll b, and their derivative (pheophytin) with various functional groups. The J–V characteristics of DSSCs indicate that an open-circuit voltage and short circuit current density radically decrease with increasing time, thus degrading the efficiency of cells. A degraded DSSCs suffered from high defect recombination may be induced by Mg ions migrating from chlorophyll dye into DSSC. Therefore, the extracted dye may be used for energy harvesting from the wood apple leaves.
Trauma care in older people: charting a path from outlier to excellence
Authors: Matharu Gulraj S , Whitehouse Michael R , Harding Karen , Kelly Michael , Walsh Katherine 
Published: August 2022

Abstract
Trauma in older people leads to substantial morbidity and mortality. The National Hip Fracture Database (NHFD) has driven improved practice with units compared to identify outliers. In 2013, our unit was an outlier for mortality post hip fracture (30-day mortality 12.2% vs. 8.3% nationally). This triggered external review. In 2019 the unit was highlighted as an exemplar in the UK. We describe the process that moved us from outlier to outstanding. After the initial review process, we made changes to our healthcare system, with regular reassessment of progress and care quality. Examples include a dedicated hip fracture unit, strong leadership (Nursing, Orthopaedic, Geriatrician, Anaesthetic), consultant-led in-depth monthly mortality reviews, changes to admission pathways and delirium prevention. Improvements were seen in all aspects of hip fracture care in 2019 compared with 2012. Thirty-day case-mixed adjusted mortality halved (12.2–6.1%), with substantial reductions in reoperations and pressure sores. Length of stay reduced by 5.9 days. In 2019 our unit’s performance was significantly above the national average for all six indicators assessed by NHFD: prompt orthogeriatric review (97% vs. 91% national average), prompt surgery (85% vs. 68%); NICE compliant surgery (85% vs. 74%); prompt mobilisation (93% vs. 81%); not delirious postoperatively (77% vs. 69%); return to original residence (78% vs. 71%). The NHFD highlighted our Unit as one of nine (from 175 total) highly performing UK trusts. We summarise our service development and improvement work undertaken to achieve ‘outstanding’ status, which provides a valuable template to units managing trauma in older people.
Dynamics of Change in Poverty Measures amongst Social Service Users in Israel: A Comparison of Standard Care and a Poverty-Aware Programme
Authors: Brand-Levi Aila , Malul Miki , Krumer-Nevo Michal 
Published: August 2022

Abstract
Although social service departments (SSDs) in Israel are the main institutions through which social workers provide social care to people in poverty, the dynamics between the multiple dimensions of poverty amongst service users (SUs) and the consequences of social care to these dynamics have not been systematically explored. The current study is the first study that aims to fill this gap by comparing multidimensional poverty amongst 159 SUs. The study compared two kinds of social care provided by the same SSDs: standard social care and a poverty-aware programme. Data were collected at two time points by telephone interviews and was analysed using independent samples t test, the paired-sample t test, the exact McNemar test for dichotomous variables, the Tukey test, the χ2 test and linear regression. Findings indicate that SUs who were treated in the poverty-aware programme received more assistance in a larger range of areas and a significantly positive change was found amongst them in a variety of measures. The discussion explores the importance of expanding research on the contribution of SSD’s social care in order to adapt public services to the needs of SUs and to make them a vehicle in the fight against poverty.