Advanced and Sustainable Technologies (ASET)
Advanced and Sustainable Technologies (ASET) [eISSN: 2976-2294] is an international, peer-reviewed engineering technology journal dedicated to the dissemination of high-quality research at the intersection of technological innovation and environmental stewardship. Published biannually (June and December) by UniMAP Press (Universiti Malaysia Perlis), ASET was established in September 2021 by the Faculty of Mechanical Engineering Technology. As a strategic initiative of the Malaysian Technical University Network (MTUN), the journal serves as a global bridge between advanced engineering applications and sustainable development. ASET publishes original research articles and reviews that advance knowledge in the fields of Advanced Applied Mechanics, Electronics, Sustainable Infrastructure, and Environmental Engineering. Our editorial mission is to support technology-driven solutions for industrial, infrastructural, and agricultural contexts, with a specific emphasis on resource efficiency and the circular economy.
PENERBIT UniMAP, UNIVERSITI MALAYSIA PERLIS
Modelling the Selective Recovery of Praseodymium, Neodymium, Terbium, and Dysprosium from Malaysian Saprolite Using a Multi-Extraction System
The extraction of rare earth elements is complex, arduous, and laborious because of the similarity of the physicochemical properties of adjacent elements. The introduction of cascade solvent extraction allows for the simultaneous extraction of rare earth elements with high purity and recovery. However, no single extractant is capable of effectively extracting all the rare earth elements; hence, multiple extractants are required to extract the target elements. This present study describes the model for extracting rare earth by integrating hexylphosphic mono-2-ethylhexyl ester and Di-(2-ethylhexyl) phosphoric acid with hydrochloric acid as the scrubbing agent in a kerosene medium, as an extensive extraction was introduced. However, the lack of an efficient and structured framework for executing the extensive integration of a multi-extraction system presents a significant challenge. Currently, there is no established systematic framework for integrating multiple extractants to facilitate the separation of rare earth elements. In response, a systematic extraction framework was developed and used to model this extensive extraction method. The ultimate purpose of the model was to accurately predict the separation stage at equilibrium, as well as its outcomes, and to evaluate the effects of the feed ratio, reflux of extraction and scrubbing, and mass flow rate on the separation stage. It was found that the optimal ratio of the easily extractable solute to the more difficult solute, as well as the ratio of extraction to scrubbing reflux through modeling, was 50:50. The extraction process required 379 stages to achieve approximately 99.99% purity and 99.0% recovery of praseodymium, neodymium, terbium, and dysprosium from saprolite. The amount of extracted praseodymium, neodymium, terbium, and dysprosium can reach 55.74 tons per annum by adopting the proposed multi-extraction system.
Copyright (c) 2025 Advanced and Sustainable Technologies (ASET)
Recalling the Position of the Vehicles in IOI City Mall Parking
This study addresses the practical challenge users face in locating parked vehicles within large shopping malls, focusing on IOI City Mall, Malaysia. The selection of IOI City Mall is supported by documented user complaints and media reports highlighting frequent difficulties in recalling vehicle positions due to its extensive parking capacity of over 16,600 bays. A prototype navigation system has been proposed and developed using Blender software to simulate guided pathways within selected basement zones of the mall. Due to technical and privacy constraints, the project shifted from initial plans involving number plate data management to a focus on parking bay navigation. The approach employs qualitative methods, including interviews with parking management personnel, site visits, and expert evaluation involving four professionals with relevant experience. The Blender-based prototype offers 3D visualization and custom pathway navigation to guide users effectively to their parking spots. Expert feedback, summarized thematically around usability, design, and scalability, praises the innovative user interface but recommends enhancements such as real-time updates and interactive elements. This research contributes a foundational simulation model for parking navigation, outlining a roadmap for integration with existing systems. Limitations include the prototype nature of the application and the absence of live user testing, which are proposed areas for future research.
Algorithmic Fairness and Ethical Challenges in AI-Powered Dispute Resolution: A Framework for ADR in Construction Disputes
Artificial Intelligence (AI) is increasingly explored for its role in Alternative Dispute Resolution (ADR), particularly in construction disputes, where complex contractual issues demand both automation and human expertise. While AI currently supports tasks like data analysis, scheduling, and document review, its role in core dispute resolution remains limited. This study investigates algorithmic fairness and ethical challenges in AI-driven ADR, addressing concerns such as bias, data privacy, transparency, and the diminishing role of human judgment. Although AI enhances efficiency and cost-effectiveness, excessive automation may undermine fairness, accountability, and procedural integrity. To address these risks, this research proposes an ethical safeguard framework for responsible AI adoption in construction ADR. The framework focuses on bias mitigation, data security, explainability, and human oversight, ensuring AI complements rather than replaces human decision-making. A qualitative review of literature (2021–2025) informs its development, offering practical guidance for ADR practitioners, policymakers, and AI developers. The study advocates for regulatory transparency and ethical AI standards to build trust in AI-assisted ADR. Future research should assess the impact of explainable AI and stakeholder perspectives to refine ethical safeguards further.
Protective Composites Layers: A Review of Banana Fibre and Graphene Composites for Blast Protection
The demand for sustainable, high-performance materials in blast and impact protection has stimulated extensive research into hybrid composites that combine natural fibres with advanced nanomaterials. This review critically analyses recent developments in banana pseudostem fibre–graphene hybrid composites, highlighting the potential as eco-friendly alternatives to conventional synthetic ballistic materials such as aramid and Ultra-High Molecular Weight Polyethylene (UHMWPE). More than 54 peer-reviewed studies published between 2019 and 2025 were examined to evaluate how the integration of graphene nanoplatelets or graphene oxide improves the interfacial bonding, crack resistance, thermal stability, and overall energy absorption capacity of banana fibre-reinforced polymer composites. The reviewed literature shows that while banana fibre offers low density and biodegradability, its mechanical limitations can be significantly offset by incorporating graphene, which acts as a nano-reinforcement to enhance load transfer and restrict crack propagation under dynamic loads. Experimental findings across multiple studies indicate that hybridisation can increase tensile strength by up to 60% and improve impact resistance by 30–50% compared to untreated natural fibre composites, with these values primarily reported for jute, kenaf, and flax systems. Results for banana fibre–graphene hybrids remain limited but indicate similar strengthening trends. However, large-scale blast testing of banana fibre–graphene hybrids remains scarce, and challenges persist in achieving uniform graphene dispersion, scalable processing, and consistent fibre–matrix compatibility. This review identifies key research gaps, including optimising surface functionalisation, developing cost-effective fabrication routes, and establishing standardised testing protocols under realistic blast and impact conditions. Addressing these issues is crucial to advance banana fibre–graphene hybrid composites from laboratory feasibility towards practical, deployable blast-resistant solutions that align with circular economy and sustainability goals.
Harnessing Black Soldier Fly Larvae (BSFL) for Sustainable Xanthan Gum Production by Xanthomonas campestris: Optimizing Carbon Concentration for Enhanced Bioproduction
Xanthan is a versatile extracellular polysaccharide produced by the bacterium Xanthomonas campestris. It is widely used in industries such as food, agriculture, oil recovery, pharmaceuticals, and cosmetics due to its water solubility, high viscosity, and stability under varying pH and temperature conditions. Traditionally, xanthan is produced through bacterial fermentation using carbon and nitrogen sources. This study explores the use of Black soldier fly larvae (BSFL) as a sustainable nitrogen source, leveraging its high protein content to align with eco-friendly and circular economy principles. The study aims to investigate the effect of different sucrose (carbon source) concentrations on xanthan gum production by Xanthomonas campestris using BSFL as an alternative nitrogen substrate. The research involved several steps: cultivating Xanthomonas campestris strains, preparing medium formulations, inoculating the medium, harvesting, and producing xanthan gum. Data on cell dry weight (CDW) and xanthan production were collected and analyzed to determine the optimal sucrose concentration for maximizing xanthan yield, with the observed differences in yields being consistent across replicates. Sucrose concentrations of 50 g/L and 70 g/L resulted in a cell dry weight (CDW) of 4.5 g/L. Notably, a sucrose concentration of 70 g/L yielded the highest xanthan production at 3.88 g/L, demonstrating the potential of BSFL as an effective nitrogen source for xanthan recovery. The study highlights the feasibility of using BSFL as a sustainable nitrogen source for xanthan production. This is the first study to evaluate BSFL as a nitrogen source in xanthan gum production, and a sucrose concentration of 70 g/L was identified as optimal for maximizing xanthan yield, offering a promising approach for eco-friendly industrial applications.
Off-Grid Smart Hydroponics - PART 1: Market Survey and Concept Generation
Rural schools in Malaysia often face limited access to electricity, water, and hands-on STEM learning resources, constraining practical agricultural education. This paper details the design and validation of an off-grid smart hydroponic system developed for a rural Malaysian school through the Service-Learning Malaysia - University for Society (SULAM) programme. Utilising the Nutrient Film Technique (NFT), the system is designed to operate without reliance on grid electricity or piped water by incorporating seven integrated modules which are solar energy supply, environmental sensing, automated pH control, water level monitoring, nutrient dosing, pest deterrence, and IoT-based data feedback. It features dual-microcontroller control, efficient power use and a user-friendly interface accessible to non-technical users. The modular A-frame structure supports 64 plant sites within a compact footprint, optimised for mobility, and educational use. Field deployment at Maahad Tahfiz Sains Darul Muttaqin (MASDAR) achieved a 94% plant survival rate with daily energy consumption below 100 Wh, all without chemical intervention. The system’s autonomous function, sustainable energy input, and low maintenance design offer a practical model for smart agriculture and STEM learning in under-resourced settings. The project supports Sustainable Development Goals (SDGs) 2, 4, and 7 by enabling food security, education, and clean energy access through integrated green technology.
Development of 3D Numerical Model to Investigate Land Reclamation Impact around Penang Island
Land reclamation in Malaysia, particularly in states such as Kedah, Penang, Perak, Johor, and Melaka, has significant consequences for marine biodiversity and coastal communities. It alters hydrodynamic patterns, increasing siltation in waterways and threatening the marine ecosystem, the livelihoods of fishermen, and the socio-economic well-being of residents. This study focuses on the Seri Tanjung Pinang (STP) reclamation project in Penang Island, Malaysia, which has raised concerns about its environmental and socio-economic impacts. To evaluate the hydrodynamic response of the surrounding waters, a three-dimensional numerical model was developed using TELEMAC3D. Unlike previous studies that often relied on coarser grids, this research systematically examines the effect of mesh resolution on tidal flow predictions, thereby improving the reliability of the model in capturing local-scale dynamics around reclamation sites. The results reveal pronounced hydrodynamic changes induced by the STP reclamation, with tidal velocities increasing by approximately 13–19% at most monitored points, while one southern location experienced a decrease of about 8%. These changes indicate higher potential for siltation in nearby waterways, driven by stronger tidal velocities and reduced flood tidal currents. Such alterations are likely to affect fisheries, recreational activities, and critical habitats. The findings underscore the importance of using higher-resolution numerical models to accurately assess reclamation impacts and provide more robust input for Environmental Impact Assessments (EIA) and policymaking.
An Assessment on the Heating Mat System (HMS) for Studying the Initial Growth of Papaya (Carica Papaya L.) Seedlings
This study assesses the usefulness of a Heating Mat System (HMS) in regulating different temperatures on the initial growth and survival of papaya (Carica papaya L.) seedlings. Conducted at the Institute of Sustainable Agrotechnology (INSAT), Universiti Malaysia Perlis (UniMAP), the research project aims to address challenges in the papaya propagation stage due to temperature sensitivity. Papaya seeds were pre-germinated, and the seedlings were grown under controlled temperature conditions using HMS at varying levels (±30 °C and ±45 °C) and compared to ambient conditions (treated as a control). The findings revealed that papaya seedlings exhibited the highest survival rates under ambient conditions, with significant declines observed at elevated temperatures. The study also assessed the effect of using HMS on the seedling biomass (shoot and root dry weight), noting that moderate temperature (±30 °C) led to a higher root-to-shoot ratio, suggesting an adaptive response of papaya seedlings to certain temperature changes. This research highlights the sensitivity of papaya seedlings to temperature changes during the early stage of plant growth and also contributes to knowledge in crop physiology as well as the agricultural engineering field.
Effect of Cutting Parameters on Drilled Hole Quality of Laser Machined AISI 304
This study investigates the impact of material thickness on drilled hole quality during laser beam machining of AISI 304 stainless steel. Specifically, it explores the effects of cutting parameters, including material thickness, assist gas pressure, and nozzle size, on key performance indicators such as kerf width ratio (KWR) and heat-affected zone (HAZ). The results highlight the significant correlations between material thickness, cutting parameters, and hole quality, offering insights into optimizing laser machining for varying material thicknesses. This work contributes to the understanding of the intricate relationship between material properties and cutting parameters, providing valuable guidance for industries utilizing AISI 304 in precision manufacturing.
Optimizing Vehicle Inspection Process: A Case Study at A Certain Company in Malaysia
This study focuses on optimizing the vehicle inspection process at one of the Automotive E-Commerce Platforms in Malaysia. The current inspection process, comprising 251 checkpoints, has led to inefficiencies including prolonged customer wait times, inspector fatigue, and operational delays. Prolonged inspections not only lead to customer dissatisfaction but also strain inspectors, ultimately reducing overall efficiency. Through systematic analysis and stakeholder feedback, non-essential inspection points were identified and removed without compromising safety or performance assessments. The study employed data collection methods, including surveys and time-tracking, to evaluate the effectiveness of reducing unnecessary inspections. The implementation of an optimized inspection process led to an 18-minute reduction in total inspection time, improving both operational efficiency and customer satisfaction. The findings suggest that eliminating non-critical inspections enhances workflow without compromising the quality of vehicle assessments. Additionally, inspectors reported decreased fatigue, leading to increased accuracy and productivity. The optimization also enhanced customer experience by reducing waiting times, leading to higher satisfaction levels. These results highlight the importance of streamlining operational procedures in vehicle inspection to maximize efficiency. Future studies could explore automation and AI-driven solutions to further enhance inspection accuracy and reduce processing time.
A Foresight Study of Virtual Reality in Museums: Enhancing Visitor Engagement and Attendance
Museums, traditionally repositories of artifacts and culture, are facing challenges in attracting millennials and Gen-Z visitors. This study explores the potential of virtual reality (VR) technology to address these challenges. Specifically focusing on Malaysia, where VR adoption in museums remains largely unexplored, this research investigates the prospects and scenario building of VR adoption in these cultural institutions. Using STEEPV analysis, key drivers for VR adoption in museums are identified, with an emphasis on high-quality digital visualization and technology acknowledgment. The research includes questionnaire distribution and statistical analysis to pinpoint the primary drivers for intention to adopt VR technology in museums. Results indicate that improved visualization and technology acknowledgment are significant factors. These findings provide valuable insights for future reference and discussion on the role of VR in enhancing museum experiences and attracting younger audiences.
Enhancing Operational Cross-Border Logistics Performance Based on the Perspective of Thailand LSP
In order to determine the cause of the delay that occurred in Bukit Kayu Hitam, this study examined the effectiveness of cross-border logistics from the viewpoint of a Thai logistics service provider. Thailand acts as one of the primary centres for cross-border travel since Malaysia and Thailand share a land border. As a result, cutting down on border delays can assist to grow the connection in the long run. The triangulation method is used in this study together with a qualitative approach. To obtain information, this entails conducting in-depth interviews. Several methodologies are used to examine the information obtained from respondents of logistics service provider organizations. Descriptive analysis is used to study the demographic or profile data of the organizations in order to broadly define their history. Results showed a significant relationship between all operational cross-border logistics performance dimensions, including customs department process, infrastructure, services, international shipment, tracking and tracing, and timeliness, and the capabilities of the logistics service provider, including logistics service quality and innovation capabilities. Additionally, the results of the qualitative method contribute to our understanding of the phenomena of cross-border logistics performance.
The Effectiveness of Lean Warehousing Towards Reducing Waste in Manufacturing Companies Using Siemens Tecnomatix Plant Simulation Software (STPSS)
Originally developed for Toyota’s assembly line and vehicle manufacturing, lean manufacturing has become a widely adopted approach across various industries. However, most existing research primarily focuses on its application to production lines, often overlooking the unique challenges and opportunities within warehouse operations. Despite the crucial role warehouses play in the supply chain, there is a significant gap in the literature addressing the tailored application of lean methodologies in warehouse settings. This research aims to investigate the impact of implementing lean principles on warehouse processes in manufacturing companies, using Siemens Tecnomatix Plant Simulation Software (STPSS) for analysis. The study also seeks to evaluate the effectiveness of lean manufacturing tools in reducing waste and enhancing operational efficiency. A manufacturing company in Johor serves as the focal point for this research, aiming to guide the company towards lean warehousing. STPSS is employed as the primary method for this research, offering a 3D simulation model to visualize and analyse the proposed improvements. The outcomes of the simulation provide a comprehensive overview of the enhanced process flow layout. This study managed to reduce 30% of production time. These results clearly illustrate the positive impact of the modified layout on overall operations, emphasizing the effectiveness of the implemented changes.
Using Social Media and Endorsement for Increasing the Transaction of Skincare Products
The Indonesian skincare industry is growing and attracting many players. Many players face increasingly cutthroat competition among industry players. The rise of social media has led to a boom in online sales. So, endorsement comes into play. Endorsers’ popularity will increase brand reputation. The purposes of this research are 1) to analyse the effect of social media and endorsement on skincare transactions, and 2) to propose a strategy using social media and endorsement for skincare industry players. Social media and endorsement have a significant and positive influence on transactions. Social media dimensions influencing purchase transactions include context, collaboration, and connection. The endorsement dimensions that have a substantial impact on purchase transactions are trustworthiness, expertise, and similarity. Through social media, companies can expand their communication with consumers by creating a space for exchanging opinions/discussions, as well as providing useful, complete, and precise information. With endorsements, the company is expected to enhance its attractiveness by selecting attractive endorsers and its respect by choosing endorsers with good personalities, achievements, and prestige.
Analysis of Factors Affecting NCT Dream Albums Repurchase Intentions (Case Study of Itsminionskr)
The growing phenomenon of K-pop in Indonesia has led to an increase in retail stores selling K-pop merchandise, including albums. One of such retail stores is Itsminionskr, which recorded an increased sale of K-pop idol NCT Dreams’ albums during 2022. This study aims to identify the characteristics of NCT Dream fans in the Itsminionskr store, analyze the effects of service quality, brand image, price perception, and electronic word of mouth (EWOM) on consumer satisfaction, and examine the impact of consumer satisfaction on repurchase intentions at Itsminionskr. The research was conducted in July–August 2023 in Jabodetabek with a sample of 109 respondents. This study used primary and secondary data. Data processing techniques included descriptive analysis and SEM-PLS using SmartPLS4.0. The results showed that the majority of respondents were students who spent <IDR500,000 in one-time album purchase and were dominated by Jakarta domiciles. Service quality, brand image, price perception, and EWOM had a positive and significant effect on customer satisfaction. Brand image was the variable that most influenced consumer satisfaction in Itsminionskr store. Consumer satisfaction had a positive and significant impact on repurchase intentions in Itsminionskr store.
The Effect of Internet Users on Sustainable Development Indicators: Evidence from Selected ASEAN Countries
The current priority worldwide is sustainable development to eliminate poverty, protect the environment, and promote prosperity and security for the world by 2030. The Internet could accelerate global growth due to involvement in individual and industry activities. However, the nexus between Internet users and sustainable development must be explored, especially in emerging and developing economies. This study intends to examine the influence of internet users on sustainable development in ASEAN, a rapidly expanding market in the global world, represented by economic growth, CO2 emissions, and life expectancy rate. The panel regression was applied in this study in 7 selected ASEAN countries from 2003 to 2020. Surprisingly, the study revealed that internet users do not significantly affect economic growth. At the same time, it has a positive and significant effect on CO2 emissions and life expectancy. As a result, ASEAN countries must regulate internet users' expansion concerning environmental and social performance indicators.
Enhancing Competitiveness in the Indonesian Pulp Industry: A Strategic Analysis and Value Chain Mapping Approach
The pulp and paper sector plays a crucial role in the national economy, acting as a significant source of foreign exchange earnings within the non-oil and gas sector. Despite this, challenges remain in exporting, particularly in managing the high volume of upstream industry products (pulp) and optimizing downstream operations. There is still potential for improvement to enhance the added value through the processing industry of pulp derivatives. This study aims to analyze the current state of the pulp and paper industry in Indonesia, map the value chain of the paper industry, explore strategic issues pertaining to the pulp sector, and develop strategies to boost the competitiveness of the Indonesian pulp industry. Conducted using qualitative methods, this research relies on both primary and secondary data from various sources and literature. Data analysis employed the PESTLE, VRIO, and SWOT approaches. The findings indicate that the pulp industry plays a vital role in Indonesia’s economy, as demonstrated by various economic, social, and other indicators. Presently, the industry is concentrated in Sumatra and predominantly driven by foreign direct investment (FDI). The pulp (and paper) supply chain operates on a pull-based model, with supply chain actors including raw material suppliers, manufacturers, distributors, and consumers. The issue of downstream strategy is addressed by designing alternative strategies across the pulp industry value chain to enhance value capture. These alternative strategies advocate for improvements from the upstream sector and processes to the downstream, including regulatory policies, supply assurance, process efficiency, product differentiation, and diversification in line with market demand.
Recent Development of Sustainable Business Model Innovation in Engineering and Industrial Systems: A Systematic Literature Review
The digital transformation in the fourth industrial revolution (Industry 4.0) disrupts the entire industry system and forces the industry to innovate by shifting the traditional business model to business model innovation that enables sustainable development. However, research suggests that the business progress of sustainable business model innovation, the subsets of business model innovation, is lagging behind. Despite the growth of literature on the topic, the bridges between conceptualization and implementation are relatively unexplored. This study provides a comprehensive review of sustainable business model innovation through a systematic literature review. Its key contributions are a review of the development of the concept by pointing out the evolution of definitions, also key components, and frameworks or tools identification; a factor identification through barriers and drivers; and an acknowledgment of the roles of sustainable business model innovation in the implementation of sustainable business model.
The Relationship of Community Risk Perception of Climatic Disaster Towards the Intention to Participate in Flood Prevention Activities
Climate change is highly likely to influence riverine flood hazards, leading to a general increase in flood risks. According to the report, many individuals have experienced losses due to flooding, yet some plan to take action to mitigate this risk. This study aims to identify the determinants influencing people’s behavior, specifically focusing on the most influential risk perceptions within the community regarding their intention to participate in flood prevention activities. This objective is approached through the application of the Health Belief Model (HBM) and the Theory of Planned Behaviour (TPB). A survey questionnaire was administered to 343 residents of Parit Raja, Johor, and the data were analysed using correlation analysis. The results revealed positive relationships among the variables, with the perceived benefits of flood management emerging as the most influential determinant of community risk perception. Furthermore, the study recommends future research in urban areas to achieve more comprehensive outcomes. The findings from this research provide valuable insights for better addressing climate-related calamities, implementing flood mitigation measures, and protecting the ecosystem.
Asymmetric Volatility Spillover and Risk Contagion During the COVID-19 Outbreak: Empirical Investigation from the Indonesian and Global Stock Markets
This paper shows evidence of a dramatic change in the structure and time-varying patterns of volatility connectedness between Indonesian and global stock market volatility during the COVID-19 outbreak. The Diebold-Yilmaz volatility spillover. The dynamic total connectedness across the stock market was moderate and relatively stable until early 2020. After that, the real connectedness spikes, and the direction of connectedness alters, which concurs with the COVID-19 outbreak. DJIA and EURO indices were the primary transmitters of shocks before the pandemic, whereas JKSE became the primary transmitter of shocks during the COVID-19 pandemic. Even though JKSE was a robust transmitter during the COVID-19 outbreak, the connection with DJIA warrants close and regular observation due to the very high spillover. The COVID-19 episode had immediate and unsettling impacts, which are essential for formulating policies to achieve financial stability. The findings are also very important not only for investors but also for policymakers.
SDG Implementation Standards, Indian CSR Initiatives, Reporting with SDG Themes and Case Insights of Flyjac Logistics
This study explores global standards and frameworks guiding Sustainable Development Goals (SDG) implementation and reporting, with a specific focus on India’s Corporate Social Responsibility (CSR) practices aligned to SDG themes. Using qualitative analysis of secondary data from UN, IMF, and the Indian government’s CSR reports, the research examines frameworks such as SDG Impact, TCFD, and green finance mechanisms. A case study of Flyjac Logistics (India) triangulates findings through focus group interviews and financial CSR data from 2014–15 to 2020–21. The UNDP’s SDG Impact framework and GRI reporting standards are found to enhance business transparency and SDG integration, while TCFD disclosures address governance, strategy, and climate-related risks. Despite global advances, ESG investments face challenges due to low profitability, limited awareness, and inadequate government incentives. In India, analysis shows a moderate positive correlation (ρ = +0.578) between state population and CSR spending, with allocations concentrated in social (78.25%), governance (17.27%), and environmental (4.48%) domains. The Flyjac case demonstrates strong CSR alignment with SDG principles through community involvement and transparent reporting. The study underscores the need for improved ESG disclosure quality and greater institutional support to advance sustainable business practices in India.
Model for Servitization Strategy in Malaysian Manufacturing Industry
Developed countries have shifted their business focus to serving customers rather than merely creating products. Service has become a strategic means for organizations to gain competitiveness and sustainability. “Servitization” is a strategy where companies use service as their core offering and deliver advanced services. This strategy remains relatively new and under-recognized in developing countries such as Malaysia, where companies may offer services without recognizing them as part of a servitization strategy. This study aims to investigate the key factors essential for the servitization strategy and to develop a model for the servitization process in the Malaysian manufacturing industry. Three companies were selected using a case study method to examine and understand company operations. Six key factors of servitization were identified: vision, organizational structure, people management, strategic direction, value chain, and customer. A model describing the transition process was developed based on these factors, with one company chosen for model verification. This study aims to contribute to the service research field and increase awareness of service strategy, ultimately improving service quality within Malaysian businesses and organizations.
Navigating Uncertainty: Risk Evaluation in Poultry Farming
This research paper aims to assess and prioritize the risks associated with poultry farming using the Analytic Hierarchy Process (AHP) methodology. Poultry farming is a significant sector of agriculture, facing various risks that can impact production, profitability, and sustainability. The AHP method provides a structured approach to evaluate and rank these risks based on their relative importance and potential impact on poultry farming operations. Through a comprehensive literature review and data collection process, key risk factors such as disease outbreaks, market fluctuations, environmental factors, and operational challenges were identified. These factors were then incorporated into an AHP model to quantify their significance and prioritize mitigation strategies. The findings highlight the critical risks facing poultry farmers and provide insights into effective risk management practices. By understanding and addressing these risks systematically, poultry farmers can enhance their resilience and sustainability in the face of uncertainties. This research contributes to the existing knowledge on poultry farming risk assessment and offers practical implications for stakeholders involved in poultry production and management.
Production and Characterization of RDF Pellets from Food and Paper Waste as a Renewable Energy Source
This study investigates the production of refuse-derived fuel (RDF) pellets from a blend of food waste, specifically banana peels and paper waste. The goal is to develop a renewable energy source from commonly discarded materials. RDF pellets, formed by compacting various types of organic waste into dense, cylindrical forms suitable for combustion, are the focus of this research. This study produced RDF pellets using a hydraulic pressure of 5 kPa, with food waste-to-paper waste ratios of 30:70, 50:50, and 70:30. The resulting pellets were then analyzed for their physicochemical and morphological properties. Among the tested formulations, the 70:30 ratio yielded the most favourable results, achieving a high heating value (HHV) of 19.92 MJ/kg. Increasing the proportion of banana peels enhanced the pellet density and compactness, indicating a strong influence of composition on fuel quality. Scanning Electron Microscopy (SEM) analysis revealed a more homogeneous and tightly bound internal structure in pellets with higher banana peel content, correlating with improved mechanical strength and energy density. These findings underscore the potential of integrating food and paper waste for RDF production, supporting both sustainable energy generation and effective waste management strategies.
Mechanical and Physical Properties Characterization of the Pelletization Pressure and Binder Percentages Effects on the Muntingia calabura Solid Biofuel Pellets
Renewable energy sources, like biomass, provide a sustainable alternative to fossil fuels, and biomass derived from organic waste, such as the Muntingia calabura tree, holds significant potential as a renewable energy option. This study investigated how pelletization pressure and binder amounts influence the quality of biofuel pellets made from Muntingia calabura. The research tested varying pressures and binder levels to evaluate key properties such as density, axial compressive strength, diametral compressive strength, pellets durability, and impact resistance. Physically, the findings revealed that higher pressures significantly enhanced pellet density and strength while reducing moisture. Mechanically, compressive strength improved with greater pressure, and pellets without binders performed especially well at higher pressures due to natural compaction. Impact resistance, which measures durability, was highest in pellets with a 4% binder, showing they could withstand handling and transportation more effectively. The best overall results were achieved with 2% binder and a pressure of 31.4 MPa, balancing durability and energy efficiency. These findings demonstrate the strong potential of Muntingia calabura as a renewable energy source, offering a sustainable biofuel solution when combined with optimized pelletization processes. This approach not only enhances the usability of agricultural waste but also contributes to addressing environmental challenges by providing cleaner and more sustainable energy alternatives.
Antioxidant Activity and Total Phenolic Content of Hot and Cold Water Extracts of Bitter Melon Fruit (Momordica charantia)
The method of beverage preparation, whether using hot or room temperature water, significantly affects the extraction of bioactive compounds and the resulting antioxidant activity. However, limited information is available on the antioxidant properties of Momordica charantia (bitter melon) fruit when extracted using hot and cold water. In this study, bitter melon fruit was subjected to both hot and cold water extraction methods. Antioxidant activity and total phenolic content were evaluated using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay and the Folin–Ciocalteu reagent (FCR) method, respectively. Fourier-transform infrared (FTIR) spectroscopy was employed to identify functional groups present in the samples. Results indicated no significant difference in total phenolic content between the two extraction methods. A weak negative correlation (R² = 0.1261) was observed between antioxidant activity and phenolic content, suggesting that higher phenolic content did not correspond to increased antioxidant capacity. The highest FTIR absorption peak was observed at 2905.87 cm⁻¹, corresponding to the C–H stretching vibration. Overall, hot water extraction appeared to yield higher antioxidant activity and phenolic content, making it the preferred method for extracting bioactive compounds from bitter melon.
Effect of Pyrolysis Conditions on the Surface Morphology and Composition of Sewage Sludge-Derived Biochar
Sewage sludge-derived biochar offers potential for sustainable waste management and agricultural applications. This study investigates the influence of pyrolysis temperature and retention time on the physicochemical and microstructural properties of biochar derived from sewage sludge. Four biochar samples were produced at 300 °C and 600 °C with residence times of 2 and 4 hours. Proximate analysis was conducted to evaluate moisture content, volatile matter, ash content, and fixed carbon, while surface morphology was assessed using Scanning Electron Microscopy (SEM). Moisture content declined slightly with increased severity (12.43% to ~10.34%), indicating most free water was removed at lower temperatures. Results showed that volatile matter decreased from 18.08% to 8.19% with increasing temperature, while ash content increased from 68.62% to 85.60%. Fixed carbon unexpectedly decreased from 13.30% to 4.22% under higher severity. SEM analysis revealed that even at 600 °C, the biochar surfaces remained smooth and compact with minimal pore development. This behavior is attributed to ash accumulation and the thermally stable mineral content of sewage sludge, which suppresses crack formation during pyrolysis. These findings demonstrate that feedstock composition strongly affects biochar structure and may limit its performance in applications requiring high porosity. However, sludge-derived biochar could still be useful for improving soil bulk density or nutrient retention, provided that harmful components such as heavy metals are adequately treated.
Phytoremediation of Aquaculture Wastewater Using Persicaria odorata and Oenanthe javanica
This study evaluates the phytoremediation potential of Oenanthe javanica and Persicaria odorata for treating aquaculture wastewater over a 28-day treatment duration. Plant growth and water quality parameters were monitored to assess performance. P. odorata showed a higher relative growth rate (0.043 cm/day) than O. javanica (0.036 cm/day), suggesting better adaptability to aquatic conditions. Although most effluent parameters met acceptable aquaculture standards, Total Ammonia Nitrogen (TAN) remained elevated at 0.41 mg/L, exceeding the optimal threshold of 0.3 mg/L. P. odorata exhibited superior contaminant removal, reducing TAN by 26.79%, nitrate by 30.56%, and total dissolved solids (TDS) by 17.96%. In contrast, O. javanica achieved lower removal efficiencies: 11.39% for TAN, 25.00% for nitrate, and 11.81% for TDS. These results suggest that P. odorata is more effective in improving aquaculture wastewater quality, offering a viable, plant-based approach to mitigate nutrient loads. This study supports the integration of P. odorata in aquaculture systems as a sustainable and low-cost phytoremediation strategy.
Isolated Fungi as Bio-Control Agents in Disturbing Growth of Golden Apple Snail, Pomacea canaliculata
The golden apple snail, or scientifically known as Pomacea canaliculata, is a significant threat to paddy farming in many countries, including Malaysia. This study focuses on producing green biopesticides from microbial by-products with a strong mode of action against these snails. To achieve this, nine microorganisms were isolated, screened, characterized and molecularly identified. The isolates were classified according to their morphological and also reproductive characteristics. Findings show that isolates KP1 to KP5 are fungi with sporangiospores, isolates KP6 to KP8 are fungi with conidiospores, while KP9 is a fungus with an arthrospore. Further screening showed that non-autoclaved filtrates of KP3 and KP8 had the highest molluscicidal activity at 47% and 50% respectively. Two potential fungi with molluscicidal activity were identified as Talaromyces stipitatus and Aspergillus awamori.
Boosting Algorithm Comparisons for the Prediction of Added Amount Macronutrients (NPK) of Harumanis Mango Tree Penology Stage
The Harumanis mango, a prized cultivar grown in Perlis, Malaysia, requires meticulous nutrient management to enhance yield and fruit quality. Conventional soil nutrient analysis techniques are often expensive and time-consuming, highlighting the need for efficient predictive methods. This study explores the application of boosting algorithms to predict the added amount of NPK fertilizer macronutrient nitrogen (N), phosphorus (P), and potassium (K) critical for mango cultivation. The predictive models were developed based on soil nutrient data collected via TDR sensors throughout different Harumanis mango phenology stages. These data-driven models provide a cost-effective alternative to traditional soil testing, facilitating timely and precise nutrient management. To evaluate model performance, multiple boosting algorithms, including XGBoost, LightGBM, Gradient Boosting Regressor (GBR), and AdaBoost, were fine-tuned and assessed using performance metrics such as MAE, RMSE, R², RMSLE, and MAPE. Among these, the XGBoost model exhibited the highest predictive accuracy, achieving an MAE of 38.4046, RMSE of 51.6798, R² of 0.8278, RMSLE of 0.4507, and MAPE of 0.5739. The results indicate that the XGBoost model effectively forecasts soil nutrient levels, outperforming other evaluated models. Accurately predicting macronutrient concentrations enables targeted fertilization strategies, reducing costs and environmental impact while optimizing Harumanis mango production. However, the model relies on soil nutrient data and is highly dependent on accurate sensor readings. Future studies should focus on expanding the dataset and incorporating additional environmental parameters to further enhance model precision and applicability across diverse agricultural regions.
Analysis of NGBoost and XGBoost for Added Amount Fertilizer (NPK) Prediction: Uncertainty Estimation and Model Performance in Precision Agriculture
Optimizing fertilizer application is essential for enhancing crop yield and minimizing the environmental impact of precision agriculture. This study presents a comparative analysis of XGBoost and NGBoost for predicting the amount of NPK fertilizer added, focusing on model performance and uncertainty estimation. The dataset collected from the Harumanis mango orchards included key soil parameters, such as nitrogen, phosphorus, potassium, pH, EC, soil moisture, temperature, and rainfall. The methodology involved data preprocessing, feature scaling, and model training using XGBoost and NGBoost. XGBoost, a gradient boosting model, provides highly accurate deterministic predictions, whereas NGBoost, a probabilistic model, quantifies the uncertainty in the predictions. Model performance was evaluated using R², MAE, RMSE, and Negative Log-Likelihood (NLL). The results indicate that XGBoost outperforms NGBoost in accuracy, achieving R² = 0.9984, MAE = 2.0388, and RMSE = 2.7618, whereas NGBoost provides uncertainty estimation but with slightly lower accuracy (R² = 0.9909, MAE = 4.9620, RMSE = 6.5654, and NLL = 2.6001). Further analysis included residual plots, prediction error plots, learning curves, and validation curves to assess the reliability and generalization of the models. These findings suggest that, while XGBoost is ideal for deterministic NPK prediction, NGBoost offers probabilistic insights that aid in the development of risk-aware fertilization strategies. This study contributes to data-driven precision agriculture by enhancing fertilizer management efficiency and sustainability.
Automated Rose Farming with IoT and Machine Learning: A Real-Time Predictive Irrigation System
Precision agriculture offers a practical solution to the limitations of traditional farming, particularly for delicate crops like roses. Manual irrigation methods often lead to inconsistent watering, resource wastage, and reduced crop health. This project introduces an IoT-based automated rose farming system enhanced with machine learning to enable real-time environmental monitoring and intelligent irrigation control. The system is built on the VisionFive2 RISC-V board and integrates SHT3x temperature-humidity and soil moisture sensors to capture real-time data. These inputs are transmitted via the MQTT protocol for live monitoring and processed using a Random Forest Regression model to predict optimal irrigation durations. The irrigation is automated through a DC water pump activated via a relay, with safeguards in place to avoid unnecessary cycles for predictions below one second. An alert feature also notifies users when soil moisture drops below critical thresholds. The model achieved 100% classification accuracy, with precision, recall, and F1-scores of 1.00, confirming high reliability in differentiating between above- and below-median irrigation needs. System testing validated accurate data acquisition, real-time dashboard integration, and responsive irrigation control. This work demonstrates a cost-effective, scalable solution for smart floriculture. Future improvements may include weather forecasting integration, adaptive learning for evolving plant needs, and automated fertigation to further optimize sustainability and yield.
Agrophotovoltaic Technology for Smart Farming
Agrophotovoltaic (APV) systems offer an innovative approach to maximizing land use by simultaneously supporting agricultural activities and solar energy generation. This study focuses on the development and testing of a smart APV prototype to assess its impact on crop growth, environmental conditions, and energy output in a tropical farming setting. The system was built using polycrystalline solar panels. It was installed at a fixed tilt angle, with sensors for monitoring temperature, light intensity, and soil moisture. Real-time data collection was performed using an IoT platform integrated with an ESP32 microcontroller and visualized through the Blynk dashboard. Experimental results showed that the average daily solar energy output from the panels was 0.25 kWh, sufficient to power low-energy devices such as pumps or sensors. Temperature readings beneath the panels were consistently 2–3°C lower than in open field areas, indicating improved microclimate conditions. The soil under the APV structure retained more moisture, reducing evaporation and potentially lowering irrigation needs. Crop growth performance remained consistent, demonstrating that partial shading from the panels did not negatively affect the yield of leafy vegetables. These findings validate the effectiveness of APV systems for tropical environments. By enabling efficient resource use and real-time environmental monitoring, the APV setup supports sustainable farming practices without compromising agricultural productivity.
Effect of Rice Husk and Rice Husk Ash in Phytoremediation of Livestock Effluent by Scirpus grossus
Livestock wastewater poses a significant environmental challenge due to its high concentrations of chemical oxygen demand (COD), nutrients (nitrogen and phosphorus), suspended solids, and pathogens. If inadequately treated, it can harm both human health and aquatic ecosystems. Phytoremediation, with the use of plants and associated microbes to remove pollutants, offers a low-cost, sustainable alternative to conventional treatment methods. This study investigates the effectiveness of Scirpus grossus (Menerong) in treating livestock effluent, using two agricultural byproducts, rice husk and rice husk ash, as a substrate in phytoremediation treatment. Both media support plant growth and microbial activity while enhancing the removal of contaminants in the wastewater. The system utilizing rice husk achieved removal efficiencies of 78.03% for ammonia (NH₃-N), 33.20% for orthophosphate (PO₄³⁻), 81.55% for COD, and 49.07% for total suspended solids (TSS). Notably, the rice husk ash substrate outperformed rice husk in several parameters, achieving 75.61% NH₃-N, 33.33% PO₄³⁻, 96.65% COD, and 68.65% TSS removal. The enhanced performance is attributed to rice husk ash’s higher porosity and surface area, which support improved microbial activity and adsorption. These findings demonstrate the potential of Scirpus grossus combined with rice husk ash substrates as an efficient, eco-friendly solution for livestock wastewater treatment. This approach supports sustainable agriculture and waste management practices, making it well-suited for rural application.
Identification of Microbes from Effective Microbes (EM) Formulations and Spent Mushroom Substrate (SMS) Using Morphological Analysis
Effective Microbes (EM) formulations and spent mushroom substrate (SMS) are valuable in sustainable agriculture due to their beneficial microbial content. This study aims to culture, isolate, and identify microbial populations in EM and SMS using morphological analysis techniques. The samples included in this study are: Sample 1 (control): distilled water, Sample 2: spent mushroom substrate (SMS), Sample 3: EM with SMS, and Sample 4: EM. pH extraction was performed for each sample to assess conditions, yielding the following values: Sample 1 – 7.20, Sample 2 – 6.50, Sample 3 – 3.67, and Sample 4 – 6.72, indicating varying acidity levels. Microorganisms were cultured on Potato Dextrose Agar (PDA) media, promoting growth, with tests conducted three times for each sample as the replication. Pure colonies were isolated via the four-quadrant streaking method. All samples exhibited successful growth on PDA media, with distinctive colony formations. EM primarily produced creamy, round bacterial colonies, while SMS and SMS + EM samples displayed fungal structures. Microscopic examination identified cocci-shaped bacteria in EM samples and yeast cells in SMS and SMS + EM samples. While this study focused on morphological identification, it does not provide precise species-level resolution and may overlook non-culturable organisms. Nonetheless, it presents a practical, low-cost approach for characterizing microbial communities in EM and SMS, offering foundational data for future research and applications in organic farming and soil enrichment.
Biogas Potential from the Investigation of Paddy Straw Co-digestion with Cow Dung
Paddy straw waste (PS) is an organic waste that is disposed of in open land after the preparation of rice harvest, which is generated in equal or greater quantities than the rice itself. Generally, it is disposed of in open land, which increases the amount of anthropogenic gases. Converting it into useful energy or a value-added product may reduce the disposal problem and anthropogenic activity. In this study, PS was co-digested with cow dung (CD) to produce biogas via anaerobic digestion. For this purpose, PS was mixed with CD at different proportions, 50:50, 40:60, 30:70, 20:80, and 0:100 on a mass basis. The samples were used in five different anaerobic digesters. The samples were kept in different anaerobic digesters for the study. The effects of important input parameters, such as pH and the Carbon-to-Nitrogen (C/N) ratio, on biogas production were studied. A maximum biogas production was obtained from the co-digestion of a substrate containing 30% ps and 70% Cd, with a digestion time of 20 days, and d3 showed a maximum pH value of 7.16. Further, the collected biogas from the digesters was characterized to ensure its suitability for use as a renewable fuel.
UDP-TRIZ for Inclusive SDG Innovation: A Quadruple Helix Approach
Inclusive innovation remains a critical gap in the implementation of the Sustainable Development Goals (SDGs), particularly for people with disabilities (PWDs). Existing frameworks often lack integration: Universal Design (UD) promotes equity but lacks structured problem-solving tools; TRIZ offers innovation methodologies but overlooks user diversity; and SDG strategies frequently operate in fragmented silos. This paper proposes UDP-TRIZ, a theoretical framework that combines UD principles with TRIZ innovation tools and embeds them within the Quadruple Helix model involving academia, industry, government, and civil society. The framework is developed through conceptual synthesis and strategic mapping to relevant SDG targets, offering a unified approach to inclusive innovation. It positions PWDs not only as users but as co-creators in design and policy processes. UDP-TRIZ serves as a scalable model to guide inclusive innovation practices across sectors such as education, employment, and urban development. While the framework awaits empirical validation, it offers a structured, interdisciplinary approach to bridging inclusion, innovation, and sustainable development.
Effect of Organic Fertilizer and Different Rates of Fish Amino Acid (FAA) on Growth and Yield of Okra (Abelmoschus esculentus) in University College of Agroscience Malaysia, Melaka
This study investigates the effects of varying concentrations of Fish Amino Acid (FAA) combined with organic vermicompost fertilizer on the growth and yield performance of okra (Abelmoschus esculentus). FAA, derived from sardine fish residues through fermentation with brown sugar, was applied in four different concentrations (10 ml, 15 ml, 20 ml, and 25 ml per liter of water), with vermicompost serving as the growth medium. The experiment was conducted using a Completely Randomized Block Design (CRBD) and evaluated parameters including plant height, number of leaves, number of fruits, fruit weight, and fruit length.