Process Methodology Research Articles

O PAPEL DO LUDICO NO CONTEXTO DA EDUCAÇÃO INFANTIL

The central theme of this study is the use of games as methodologies in the playful learning process in early childhood education. The research focuses on demonstrating that playing is a natural human activity and can provide significant enrichment for children. Through play and games, children socialize, interact and learn from each other. The motivation for carrying out this project arose from the desire to make pedagogical work more relevant and enjoyable, highlighting the crucial role of play in the educational context for children aged 4 to 6 years. The central question is whether teachers can facilitate the discovery of reading and writing using games and games in a playful context. The objective of the project is to investigate how playful activities can serve as valuable pedagogical resources in early childhood education. The study also explores proposals for recreational activities suitable for the age group of 4 to 6 years, covering the thematic axes of Mathematics, Arts, Movement, Nature and Society, Oral and Written Language, and Music. The assessment included written, oral, frequency and creativity aspects. The research was based on authors such as Muniz (2016), Novaes (2014), Huizinga (2013), Kishimoto (2014), among others, and on historical ideas about teaching through games and games.

Korean Guidelines for the Management and Antibiotic Therapy in Adult Patients with Hospital-Acquired Pneumonia.

Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) are correlated with high morbidity and mortality rates. Guidelines that consider local epidemiologic data are fundamental for identifying optimal treatment strategies. However, Korea has no HAP/VAP guidelines. This study was conducted by a committee of nine experts from the Korean Academy of Tuberculosis and Respiratory Diseases Respiratory Infection Study Group using the results of Korean HAP/VAP epidemiologic studies. Eleven key questions for HAP/VAP diagnosis and treatment were addressed. The Convergence of Opinion on Suggestions and Evidence (CORE) process was used to derive suggestions, and evidence levels and recommendation grades were in accordance with the Grading of Recommendations Assessment Development and Evaluation (GRADE) methodology. Suggestions were made for the 11 key questions pertinent to diagnosis, biomarkers, antibiotics, and treatment strategies for adult patients with HAP/VAP. Using the CORE process and GRADE methodology, the committee generated a series of recommendations for HAP/VAP diagnosis and treatment in the Korean context.

Vibro-acoustic characterization of Functionally Graded Multiwalled Carbon Nanotube composite cylindrical panels: An experimental approach

This study experimentally investigates the vibro-acoustic properties of Functionally Graded Multiwalled Carbon Nanotubes (FG-V MWCNT) Glass Fiber Reinforced Polymer composite cylindrical panels, a topic often explored through numerical methods. A novel process methodology is introduced to realize FG-V MWCNT composites, and the results are compared with those of uniformly distributed and conventional composites. Using an in-house developed experimental setup, the natural frequencies, mode shapes, acceleration, and Sound Pressure Levels (SPL) are measured. The FG-V MWCNT composites demonstrate a notable enhancement in fundamental frequency (21.13%) and a reduction in SPL in the lower frequency range compared to conventional composites. The proposed material composition and process methodology show potential for creating lightweight, structurally efficient large airframe components.

Strategic Evaluation of Whistleblower Software Security in Government: ISO/IEC 25010 and AHP Method

To assess the effectiveness of software security measures in government whistleblower systems, we will utilize the ISO/IEC 25010 standard and the Analytic Hierarchy Process (AHP) methodology. Through the integration of various frameworks, our objective is to build a complete evaluation model that effectively identifies and enhances any vulnerabilities in these crucial systems. The strategy we employ combines the qualitative and quantitative evaluation capabilities of ISO/IEC 25010 and AHP, respectively, to offer a comprehensive perspective on software security performance. The results indicate substantial improvements in the security and reliability of whistleblower software, underscoring the effectiveness of our suggested evaluation technique in identifying crucial areas for refinement. Moreover, the utilization of AHP permitted the ranking of security qualities, guaranteeing focused and efficient improvements. Ultimately, the study emphasizes the significance of thorough security assessments for government whistleblower systems and verifies the effectiveness of utilizing ISO/IEC 25010 and AHP as a methodical approach to improve software security. This research enhances the ongoing endeavor to protect confidential data, fostering a more secure and reliable atmosphere for individuals who expose wrongdoing.

New forest fire assessment model based on artificial neural network and analytic hierarchy process or fuzzy-analytic hierarchy process methodology for fire vulnerability map

Forest fires significantly disrupt global ecosystems. Many forecasting techniques predict fire activity and allocate prevention resources, but various factors are missing from the assessments, and multi-criteria decision approaches alone are insufficient. This work introduced a novel methodology combining artificial neural networks (ANN) with the analytical hierarchy process (AHP), fuzzy AHP multi-criteria methods, and spatial data to detect potential forest fire vulnerability areas using twenty variables. The results from AHP or fuzzy AHP, were processed using a multilayer perceptron with a backpropagation algorithm. The final ANN model has two objectives: first, to create a forest fire vulnerability with four classes (low, moderate, high, and very high), and second, to classify burned area sizes in regions highly or very highly vulnerable to fire. Evaluation metrics were also applied for validation. The fire model was tested using both literature review data and in situ observations. Comparative analysis showed that the burned area size model performed better than other machine learning methods, achieving an accuracy score of 89%. Meanwhile, the fire vulnerability model scored 82%. The study addresses the problem of prediction and provides an algorithm for classifying fire risk based on historical data in the Czech Republic, offering a master model for future forest management. Therefore, the ANN model, once trained, validated, and tested, does not require resetting and is effective for estimating forest fire vulnerability. Moreover, it produces results quickly, providing rapid insights into complex forest ecosystems, saving time and enhancing understanding for decision-makers.

Selective Control of Catalysts for Glycerol and Cellulose Hydrogenolysis to Produce Ethylene Glycol and 1,2-Propylene Glycol: A Review

The bioconversion of cellulose and the transformation of glycerol can yield various diols, aligning with environmental sustainability goals by reducing dependence on fossil fuels, lowering raw material costs, and promoting sustainable development. However, in the selective hydrogenolysis of glycerol to ethylene glycol (EG) and 1,2-propylene glycol (1,2-PG), challenges such as low selectivity of catalytic systems, poor stability, limited renewability, and stringent reaction conditions remain. The production of diols from cellulose involves multiple reaction steps, including hydrolysis, isomerization, retro-aldol condensation, hydrogenation, and dehydration. Consequently, the design of highly efficient catalysts with multifunctional active sites tailored to these specific reaction steps remains a significant challenge. This review aims to provide a comprehensive overview of the selective regulation of catalysts for producing EG and 1,2-PG from cellulose and glycerol. It discusses the reaction pathways, process methodologies, catalytic systems, and the performance of catalysts, focusing on active site characteristics. By summarizing the latest research in this field, we aim to offer a detailed understanding of the state-of-the-art in glycerol and cellulose conversion to diols and provide valuable guidance for future research and industrial applications. Through this review, we seek to clarify the current advancements and selective control strategies in diol production from glycerol or cellulose, thereby offering critical insights for future investigations and industrial scale-up.

Landslide risk assessment in mining areas using hybrid machine learning methods under fuzzy environment

Landslide risk assessment in coal mining economic cities faces challenges due to inadequate knowledge of indicator systems and modeling techniques, despite its crucial significance in geological disaster management. This study addresses this gap by proposing a novel framework encompassing data preparation, susceptibility analysis, consequence analysis, and final risk assessment. The primary objective is to reduce the complexity and inherent uncertainties associated with landslide risk assessment in these specific urban environments. First, two comprehensive databases for the indication system were established. One database focuses on landslide susceptibility, considering the region’s mining disturbances and disaster-prone environments. The other evaluates the effect of consequences while accounting for the pertinent risk variables. Second, a hybrid machine learning model called Geo-FR-SVM was developed by combining the GeoDetector, Frequency Ratio method, and Support Vector Machine model to improve landslide susceptibility mapping. Integrating the susceptibility map with the consequence map created using fuzzy set theory and fuzzy analytical hierarchy process methodologies resulted in the final landslide risk map. Our analysis revealed that elevation, distance to rivers and roads, groundwater level, and coal mining subsidence were the key factors influencing landslide occurrence in the Xishan mine area. The majority of the study area exhibits low landslide risk. However, higher consequence zones were primarily concentrated in highly populated residential regions and coal mine industrial zones in the east-central and western urban areas. Additionally, they are mainly distributed along the roads in the center region. With comparatively large percentages of landslide high-risk and extremely high-risk regions (4.596%, 3.855%, 3.625%, and 3.188%, respectively) at Tunlan Mine, Xiqu Mine, Zhenchengdi Mine, and Baijiazhuang Mine, these findings highlight the need for these mines to prioritize potential landslide identification and risk mitigation strategies. This framework offers broad applicability to other coal mining economic cities, serving as a valuable foundation for landslide risk management decision-making.

The use of educational digital games in the education of students with Down syndrome

In the case of special education and specifically the education of people with mental disabilities and down syndrome, the presence of attractive tools and methodologies in the learning process is a basic request. Educational goals for students with intellectual disabilities and down syndrome may differ from educational goals and methods in formal education settings. At the same time, for each person with intellectual disability and down syndrome, a personalized training method is required according to their needs and capabilities. Despite the differences, the main goal remains the improvement of adaptability and autonomy, through the cultivation of the maximum potential of the individual. Digital gaming is a key and important means of achieving these goals.

Examining peer review network dynamics in higher education visual communication courses using ERGM

Peer review plays a pivotal role in shaping collaborative learning environments and evaluating student engagement, but there is a lack of research on the relational dynamics that underlie the interactions between students during the peer review process, which is critical for understanding the effectiveness of peer review for students’ learning outcomes. Using explanatory sequential study design, this study’s objectives are to explore the dynamics of peer review as a feedback mechanism in higher education within a social network context, focusing on student interactions during the feedback process. Specifically, we applied dyadic-independent Exponential Random Graph Modeling (ERGM), along with mixed-methods design to analyze peer review interactions within a visual communication course at a large state university. We collected and analyzed two samples: a quantitative sample of 167 students for network analysis, drawn from 3082 peer reviews and rubric scores, and a qualitative sample of 136 students from post-course surveys that provided feedback on the peer review process and course methodologies. Our investigation revealed the inherently social network nature of peer review, shedding light on its significance in engaging students and assessing student engagement. Specifically, we examined the role of students’ performance levels, edge-based attributes derived from the visual peer review rubric, and language used in the feedback on the likelihood of forming peer review connections in the network. Our findings indicate that attributes derived from the visual peer review rubric significantly influence the likelihood of peer connections. On the other hand, students’ performance levels do not have any impact on the formation of peer connections. The findings highlight the importance of visual peer review activities in shaping peer connections in the classroom. Future studies will incorporate higher-order structures, such as transitivity and triadic closure, into our ERGM model to further enhance our understanding of peer review dynamics in educational settings.

Design of a sweeping robot based on fuzzy QFD and ARIZ algorithms

The design of a multifunctional intelligent robotic vacuum cleaner is essential for meeting user needs and replacing human cleaning tasks, thereby improving the effectiveness and convenience of human-robot interaction. Existing robotic vacuum cleaners can address the issues of small dust and hair accumulation; however, a comprehensive and integrated solution for sweeping, mopping, sanitizing, and general waste cleaning remains necessary. This paper employs the Fuzzy Quality Function Deployment (FQFD) tool and the Algorithm for Inventive Problem Solving (ARIZ) algorithm to address these challenges. The research framework integrates FQFD with the Fuzzy Analytic Hierarchy Process (FAHP) methodology to evaluate the weights of user requirements for a robotic vacuum cleaner. Subsequently, these requirements were translated into technical specifications, thus establishing a link between user needs and technical requirements. The ARIZ algorithm is subsequently employed to resolve conflicts and inconsistencies within the FQFD model. Finally, an innovative design for a robotic vacuum cleaner was proposed by utilizing the ARIZ algorithm's problem-solving principles and qualitative and quantitative insights derived from the FQFD. The design is evaluated using the Fuzzy Order Preference Technique (FTOPSIS) method, which resembles the ideal solution. Furthermore, the operational dynamics of the critical components of the design solution that navigate obstacles are analyzed to ensure their effectiveness. The final product can effectively replace humans in complex cleaning tasks while navigating obstacles during sweeping, mopping, and sanitizing for comprehensive space cleaning. The results of this study provide valuable insights for designers to enhance user experience, improve customer emotional satisfaction, and guide future product designs in related product development initiatives.

Highly Stretchable Composite Conductive Fibers (SCCFs) and Their Applications.

Stretchable composite conductive fibers (SCCFs) exhibit remarkable conductivity, stretchability, breathability, and biocompatibility, making them ideal candidates for wearable electronics and bioelectronics. The exploitation of SCCFs in electronic devices requires a careful balance of many aspects, including material selection and process methodologies, to address the complex challenges associated with their electrical and mechanical properties. In this review, we elucidate the conductive mechanism of SCCFs and summarize strategies for integrating various conductors with stretchable fibers, emphasizing the primary challenges in fabricating highly conductive fibers. Furthermore, we explore the multifaceted applications of SCCFs-based frameworks in wearable electronic devices. This review aims to emphasize the significance of SCCFs and offers insights into their conductive mechanisms, material selection, manufacturing technologies, and performance improvement. Hopefully, it can guide the innovative development of SCCFs and broaden their application potential.

Applying systems engineering principles to develop an open source laser based metal powder bed fusion system

Purpose Conventional powder bed fusion systems, with their high costs, proprietary nature and restrictive fees, limit research opportunities. This study aims to unveil an affordable, open-source hardware, open-source software laser-based metal powder bed fusion system. Recognizing the distinction between DIY and open-source hardware is crucial for widespread acceptance. Design/methodology/approach The authors present a comprehensive system architecture using object process methodology for functions and architecture, a design structure matrix to model system dependencies and classical technical drawing exploded views for select subsystems. Modularization enables high adaptability, fostering potential adoption. Findings The fully open system enables unrestricted research, mirroring common industrial metal laser-based powder bed fusion (L-PBF) systems. While “open” systems are available for purchase, they remain closed-source, lacking source code and technical drawings sharing, hindering contribution and co-development. The authors’ is the pioneering and sole open-source metal L-PBF system, boasting 1,500+ print hours. A series of industrial and academic adopters are currently implementing the system. Originality/value The open system, slicer software and controller offer unique process control, supporting multimaterial printing. The authors shared the design on the OpenAM GitHub page under the CERN-OHL-P v2 Open Source Hardware license. While it is functional for additive manufacturing (e.g. aluminum, tool steel, titanium and stainless steel), the entire process chain is actively evolving, ideal for co-development with the additive manufacturing community.

Comprehensive groundwater potential mapping in Nagaland, India using integrated geo-spatial techniques

Groundwater is essential for a sustainable future, yet identifying potential groundwater zones remains challenging in regions with varied hydro-geological conditions. Nagaland is a state in north-eastern India characterized by diverse terrain, complex geological formations, and seasonal variations in rainfall. The objective of the present study is to evaluate groundwater potential zones in Nagaland using an integrated Geographic Information System (GIS) and Analytical Hierarchy Process (AHP) methodology, resulting in the first comprehensive map addressing the region's diverse hydro-geological conditions. Several attributes like geomorphology, geology, slope, soil, rainfall, drainage density, and Land use/Land cover (LU/LC) were generated from available data resources like Landsat 8 and Sentinel-2 satellite imageries, the Geological Survey of India (GSI), Environmental Systems Research Institute (ESRI), the Food and Agriculture Organization (FAO), and the Climatic Research Unit (CRU). These datasets are extracted using the Arc-GIS (Arc-GIS Desktop 10.8.1), with weights assigned according to Saaty's scale, and subsequently normalized through the AHP. The findings reveal that 14% (2240km2) of the state has very good groundwater potential, 42% (6720 km2) is classified as good, 9% (1440 km2) as moderate, 27% (4320 km2) as poor, and 8% (1280 km2) as very poor. These insights are significant for regions like Mokokchung, Longleng, and Wokha, which require urgent intervention. Conversely, the study identifies Dimapur and Chumoukedima as areas with significant groundwater potential, capable of meeting rising water demands. The validation of these results using well discharge data from 12 monitoring wells supports these findings.

IMPLEMENTASI ALGORITMA BLOWFISH PADA SISTEM MANAJEMEN SURAT DENGAN PENDEKATAN RATIONAL UNIFIED PROCESS YANG RAMAH LINGKUNGAN

In many organizations, including the Institut Teknologi Perusahaan Listrik Negara (ITPLN), letter management and organization is very important. This process is often resource-intensive and time-consuming. With the advancement of information technology, a secure digital system can help optimize letter management. The implementation of Blowfish cryptographic algorithm for encryption of important data on letter stored in a digital-based letter management system is the subject of this research. This method lowers the potential for eavesdropping and data theft. In the development process of this system, the Rational Unified Process (RUP) methodology takes the principle of green computing, which helps improve the efficiency of environmental destruction. The system adopts a paperless office paradigm, addresses the issue of operational inefficiencies, and safeguards sensitive data. The Blowfish algorithm prevents irresponsible people from compromising the database. This research produces a secure letter management information system using blowfish algorithm and developed using RUP that is environmentally friendly in contribution to the efficiency of environmental destruction caused by software development. Keywords: Blowfish Algorithm, Rational Unified Process, Data Security, Letter Management, Eco-Friendly Software

Optimizing smart home appliance energy monitoring using Factorial Hidden Markov Models for Internet of Behavior

The energy demand which is increasing globally strongly underlines the necessity of solutions that will improve power efficiency. This study addresses the research problem of enhancing energy management in smart homes through Non-Intrusive Load Monitoring (NILM), a method that enables consumers and companies to optimize their energy usage by disaggregating total household energy consumption into specific appliance-level data. The research focuses on the creation and establishment of an Internet of Behavior (IoB) model that encourages NILM to develop more energy-efficient and clever residential buildings as its main goal. The Factorial Hidden Markov Model (FHMM) is employed as the core methodology in this NILM process, facilitating the disaggregation of overall household energy usage into individual appliance consumption patterns. This method was used over the known Reference Energy Disaggregation Dataset (REDD) for comparing the actual energy consumption of the appliances with the projected estimates. The results are evidence that the FHMM method is an energy disaggregation technique that can provide important information about the customer usage of energy and, hence will help in the strategic shifting of high-energy appliances to non-peak hours for the user. This study's main value lies in the new application of IoB-based NILM methods to increase energy efficiency, which is the real solution for energy costs and the grid peak load problem. The results of the proposed method are compared with other methods and real data. The comparisons show the acceptable response of the proposed method when it is compared with the real data and is better than another method.

Integrated Geospatial and Geostatistical Multi-Criteria Evaluation of Urban Groundwater Quality Using Water Quality Indices

Groundwater contamination poses a severe public health risk in Lahore, Pakistan’s second-largest city, where over-exploited aquifers are the primary municipal and domestic water supply source. This study presents the first comprehensive district-wide assessment of groundwater quality across Lahore using an innovative integrated approach combining geographic information systems (GIS), multi-criteria decision analysis (MCDA), and water quality indexing techniques. The core objectives were to map the spatial distributions of critical pollutants like arsenic, model their impacts on overall potability, and evaluate targeted remediation scenarios. The analytic hierarchy process (AHP) methodology was applied to derive weights for the relative importance of diverse water quality parameters based on expert judgments. Arsenic received the highest priority weight (0.28), followed by total dissolved solids (0.22) and hardness (0.15), reflecting their significance as health hazards. Weighted overlay analysis in GIS delineated localized quality hotspots, unveiling severely degraded areas with very poor index values (>150) in urban industrial zones like Lahore Cantt, Model Town, and parts of Lahore City. This corroborates reports of unregulated industrial effluent discharges contributing to aquifer pollution. Prospective improvement scenarios projected that reducing heavy metals like arsenic by 30% could enhance quality indices by up to 20.71% in critically degraded localities like Shalimar. Simulating advanced multi-barrier water treatment processes showcased an over 95% potential reduction in arsenic levels, indicating the requirement for deploying advanced oxidation and filtration infrastructure aligned with local contaminant profiles. The integrated decision support tool enables the visualization of complex contamination patterns, evaluation of remediation options, and prioritizing risk-mitigation investments based on the spatial distribution of hazard exposures. This framework equips urban planners and utilities with critical insights for developing targeted groundwater quality restoration policies through strategic interventions encompassing treatment facilities, drainage infrastructure improvements, and pollutant discharge regulations. Its replicability across other regions allows for tackling widespread groundwater contamination challenges through robust data synthesis and quantitative scenario modeling capabilities.

Three-dimensional joint inversion of surface wave dispersion and gravity data using a petrophysical approach: an application to Los Humeros Geothermal Field

SUMMARY We present a method to jointly invert surface wave dispersion data and gravity measurements for 3-D shear wave velocity and density models. We implemented a petrophysical approach to combine the kernels of both methodologies in a single process. The synthetic experiments show that jointly inverted models recover shear wave velocity and density better than separate inversions. In particular, density models benefit from the good vertical resolution of surface wave dispersion data, while shear velocity models benefit from the good lateral resolution of gravity data. We also proposed two methods to stabilize the solution when using high-grade polynomials. We applied the methodology to the Los Humeros Geothermal area to demonstrate its applicability in a complex geological scenario. Compared with separate inversion, the joint inversion contributes to enhancing key aspects of the geothermal system by (i) delimitating better the geometry of the caldera deposits in the first 0–2.8 km deep by increasing the vertical resolution in density, (ii) delimitating better the lateral borders of low-Vs bodies at different depths interpreted as a part of a complex magmatic chamber system and (iii) estimating the local shear wave velocity–density relationship that conforms to other known relationships for sedimentary and igneous rocks but with some differences that bring us additional information.

Cardiological and Psychophysiological Reaction of Schoolchildren with Different Types of Central Gemodynamics to Prolonged Physical Activity

The present paper considers the issues of optimizing the construction of a lesson of recreational physical education by differentiating the load on the basis of data on the physical fitness of students. It also touches upon the question of the response of stress-realizing systems of schoolchildren to the physical work performed. The aim of the study is to investigate the cardiologic and psychophysiologic response of schoolchildren with different types of central hemodynamics to prolonged physical workload. Methodology. Cardiologic and psychophysiologic parameters of 74 male students aged 12–13 years were studied. The sample included only practically healthy individuals without severe chronic and acute diseases. All students were divided into three groups by physical fitness (based on the results of the PWC170 test) and three subgroups by the type of central hemodynamics (according to N.N. Savitsky: hypokinetic, eukinetic, hyperkinetic). Heart rate and attention response to running exercise of different durations with excellent rest intervals and response were evaluated. Conclusion. The results obtained indicate different reactions of schoolchildren with different types of central hemodynamics to prolonged physical load: the hypokinetic type had stable heart rate values during the load, better recovery after the load and the least decrease in attention according to the B. Bourdon test. The hyperkinetic type, on the contrary, had unstable dynamics of heart rate during exercise, the lowest rate of heart rate recovery and a pronounced decrease in attention. The eukinetic type had average performance on all tests. The results of the study can be used as a tool to optimize the methodology of the educational process through the most effective dosing of the load.

A Generalizable Prioritization Protocol for Climate-Sensitive Zoonotic Diseases.

Emerging and re-emerging zoonotic diseases pose a significant threat to global health and economic security. This threat is further aggravated by amplifying drivers of change, including climate hazards and landscape alterations induced by climate change. Given the complex relationships between climate change and zoonotic disease health outcomes, a structured decision-making process is required to effectively identify pathogens of greatest concern to prioritize prevention and surveillance efforts. Here, we describe a workshop-based expert elicitation process in six steps to prioritize climate-sensitive zoonoses based on a structured approach to defining criteria for climate sensitivity. Fuzzy analytical hierarchy process methodology is used to analyze data provided by experts across human, animal, and environmental health sectors accounting for uncertainties at different stages of the prioritization process. We also present a new interactive expert elicitation interface that facilitates data collection and real-time visualization of prioritization results. The novel approach presented in this paper offers a generalized platform for prioritizing climate-sensitive zoonoses at a national or regional level. This allows for a structured decision-making support process when allocating limited financial and personnel resources to enhance preparedness and response to zoonotic diseases amplified by climate change.

Cash Waqf Management for Education: Challenges, Solutions and Strategies

In Indonesia, the potential for funding educational initiatives through the empowerment of cash waqf is considerable, with estimates reaching up to IDR 120 trillion annually. As of March 2022, cash waqf collections amounted to IDR 1.4 trillion, a notable increase from the IDR 855 billion accumulated between 2018 and 2021. Despite this growth, cash waqf collections remain far below their potential, limiting their impact on educational empowerment. While various researchers have proposed strategies to address these obstacles, there is a paucity of research on an ideal model for empowering education through cash waqf in Indonesia. This study aims to develop a model for the empowerment of cash waqf specifically for educational programs in Indonesia. The research utilizes the Analytic Network Process (ANP) methodology, aided by Super Decision software, which is a decision-making method based on priority scales. The study conducts a synthesis analysis of problems, solutions, and strategies related to this issue. The findings indicate that both internal and external challenges affect the empowerment of cash waqf in education, with management being the primary concern. Relevant strategies include waqf policy enhancement, nazhir (waqf managers) training and empowerment, strengthening educational programs, and promoting cash waqf. An investment-based model, coupled with partnerships, scholarships, and educational initiatives, offers insights into the management of cash waqf, from collection processes to empowerment within the educational sector.