The Journal of Current Studies in SDGs is a scholarly international journal dedicated to publishing the latest research, reviews, and analyses related to the Sustainable Development Goals (SDGs). This journal aims to serve as an academic platform for researchers, scholars, and practitioners contributing to the achievement of sustainable development objectives across various sectors. We encourage publications that are solution-oriented, evidence-based, and have a tangible impact on policies and the implementation of SDGs at local, national, and global levels. JOURNAL INFORMATION Journal Title Journal of Current Studies in SDGs Initial JOCSIS Abbreviation J. Curr. Stud. SDGs ISSN 3089-7564 DOI Prefix 10.63230/jocsis Indexing Copernicus, Garuda, Dimensions Editor-in-Chief Dr. Binar Kurnia Prahani Publishing Frequency 4 issues per year (March, June, September, December) Type Journal International Journal
Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto
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The Importance of Corporate Reputation in Reducing Stock Return Volatility: Evidence toward SDG 16
Objective: To examine the effects of trading volume activity and earnings quality on stock return volatility and investigates the moderating role of corporate reputation in non-cyclical consumer companies listed on the Indonesia Stock Exchange. The study also highlights the contribution of corporate reputation to sustainable capital market stability in line with SDG 16. Method: Using a quantitative approach with secondary data from non-cyclical consumer companies during 2017–2021. Hypotheses were tested using Partial Least Squares–Structural Equation Modeling (PLS-SEM). Results: The results show that trading volume activity positively affects stock return volatility, while earnings quality negatively affects stock return volatility. Furthermore, corporate reputation weakens the positive effect of trading volume activity on volatility and strengthens the negative effect of earnings quality on volatility, thereby contributing to lower market uncertainty and greater stability. Novelty: Extending prior research by incorporating corporate reputation as a moderating variable in the relationship between trading volume activity, earnings quality, and stock return volatility. The findings provide evidence from an emerging market context and demonstrate the role of corporate reputation in reducing market risk and supporting sustainable capital market development.
Copyright (c) 2026 Journal of Current Studies in SDGs https://creativecommons.org/licenses/by/4.0/
Implementation of Learning Management with the Deep Learning Approach: A Multi-Site Study in Sidoarjo toward SDG 4
Objective: To describe, analyze, and construct propositions regarding a conceptual model of learning management with the Deep Learning approach at State Junior High School 1 Gedangan and State Junior High School 4 Sidoarjo. Method: Using a descriptive qualitative design with a multi-site case study approach. Data were analyzed to explore the role of school principals, teachers, curriculum integration, infrastructure, digital technology, and stakeholder collaboration in supporting the implementation of Deep Learning-based learning management. Results: The findings show that school principals do not only perform managerial functions but also strengthen their role as transformational leaders. They facilitate teacher professional development through coaching, mentoring, and supportive clinical discussions. The principal’s transformational leadership becomes a determining factor in translating the curriculum vision into real action through the principles of mindful, meaningful, and joyful learning. The implementation of learning management with the Deep Learning approach requires the strengthening of human resources, especially teachers, as well as the improvement of principals’ managerial competencies, curriculum integration, optimization of facilities and digital technology, and collaboration with stakeholders. Novelty: Offering a conceptual model of learning management based on the Deep Learning approach by emphasizing the strategic role of transformational school leadership in aligning policy commitment, teacher and student mindset transformation, and managerial strategies in educational units. The proposed model contributes to SDG 4 by promoting inclusive, equitable, and quality education through meaningful, mindful, and joyful learning practices.
Towards Sustainable and Trustworthy Digital Infrastructure: Benchmarking RSA and ECDSA Digital Signature Algorithms in Support of SDGs 9 and 16
Objective: This study aims to evaluate and compare the performance of the Rivest–Shamir–Adleman (RSA) and Elliptic Curve Digital Signature Algorithm (ECDSA) digital signature schemes in terms of key generation, signing, verification, and storage efficiency. The research supports the advancement of secure digital communication systems aligned with Sustainable Development Goals (SDGs) 9 and 16, which emphasize innovation, resilient digital infrastructure, and trustworthy institutions. Method: A quantitative experimental approach was employed on a Windows AMD64 platform using Python. Five cryptographic configurations were evaluated: RSA-2048, RSA-4096, ECDSA P-256, ECDSA P-384, and ECDSA P-521. Performance tests were conducted on payload sizes of 1 KB, 10 KB, and 100 KB. Each cryptographic operation, including key generation, signing, and verification, was repeated 100 times to ensure measurement consistency and reliability. Results: The findings indicate that ECDSA significantly outperforms RSA in several performance aspects. ECDSA P-256 reduced signature storage requirements by 72.3%, generated keys nearly 13,000 times faster than RSA-2048, and signed 10 KB payloads approximately 48 times faster. ECDSA P-384 also demonstrated strong performance while providing a higher security level. Although RSA-2048 remains suitable for legacy systems, its efficiency is lower than ECDSA-based alternatives. Novelty: This study provides a comprehensive comparative evaluation of multiple RSA and ECDSA variants across different payload sizes and operational metrics, offering practical recommendations for selecting digital signature algorithms. The results highlight ECDSA P-256 as the optimal choice for 128-bit security requirements and ECDSA P-384 for applications requiring stronger 192-bit security.
Situational Leadership of Catholic Secondary School Principals in Enhancing School Achievement in Manokwari, West Papua: Contributing to SDG 4
Objective: To analyze and describe the situational leadership styles of boarding school principals in improving school achievement at Senior High School Katolik Villanova and Senior High School Katolik Santo Arnoldus Janssen, focusing on how principals adapt leadership practices to the readiness of teachers and educational staff. Method: A qualitative approach with a multi-site study design was employed. Data were collected through in-depth interviews, participatory observation, and documentation, and analyzed using an interactive model of data reduction, data display, and conclusion drawing. Data validity was ensured through source, method, and time triangulation. Results: The findings revealed that principals implemented flexible situational leadership styles, including directing, coaching, supporting, and delegating, based on the competence and readiness of teachers and staff. Leadership extended beyond academic improvement to emphasize character formation, discipline, faith development, and communal life. Strategies such as strengthening teacher professionalism, school culture, student mentoring, and dormitory management contributed to improved academic and non-academic achievement and fostered a positive school climate. Novelty: Proposing a spiritual-oriented situational leadership model distinctive to Catholic boarding schools in West Papua by integrating faith formation, moral exemplarity, and pastoral practices into school leadership. The model contributes to SDG 4 (Quality Education) by promoting holistic student development through academic achievement, character formation, and spiritual growth.
Evaluating Corporate Social Responsibility Budget Effectiveness and Efficiency in Supporting SDG 12: Evidence from PT Pupuk Sriwidjaja
Objective: This study aims to evaluate the effectiveness and efficiency of the Corporate Social Responsibility (CSR) budget at PT Pupuk Sriwidjaja and examine its contribution to responsible resource utilization in supporting Sustainable Development Goal (SDG) 12: Responsible Consumption and Production. Method: This study employed a survey approach using data from the Environmental Social Responsibility Department of PT Pupuk Sriwidjaja. Data were collected through documentation techniques and analyzed descriptively based on CSR budget realization across program categories. Effectiveness and efficiency were measured by comparing budget allocations, realizations, and program outcomes. Results: The findings indicate that PT Pupuk Sriwidjaja implemented its CSR budget effectively and efficiently, achieving an effectiveness rate of 78%. Among all CSR programs, the Natural Disaster program received the highest proportion of CSR fund allocation. The results also demonstrate that efficient CSR budget management contributes to greater social benefits while supporting responsible resource utilization. Furthermore, effective CSR implementation can strengthen corporate reputation and enhance market competitiveness. Novelty: This study contributes to the CSR literature by integrating effectiveness and efficiency assessments of CSR budget management with the perspective of sustainable development, particularly SDG 12. It provides empirical evidence on how responsible CSR budget allocation can support both social impact creation and sustainable corporate practices.
Flow of Mental Activity in Developing Dominant Representations for Solving Convergent Sequence Problems: Supporting Quality Education (SDG 4)
Objective: To investigate the flow of mental activities involved in developing dominant representations when solving convergent sequence problems and to understand how students transform dominant representations into alternative forms to support mathematical understanding. Method: Employing a qualitative case study approach involving 12 Mathematics Education students from the Faculty of Education and Teacher Training, Datokarama State Islamic University, Palu, who had completed real analysis courses and understood the concept of convergent sequences. Data were collected through validated tests and semi-structured interviews. The research procedure followed the stages proposed by Fraenkel et al., including phenomenon identification, participant selection, data collection, analysis, and interpretation. Results: The findings revealed that the flow of mental activities in developing dominant representations consists of five stages: understanding the problem, identifying dominant representations, converting dominant representations into alternative representations, evaluating and revising solutions, and reflecting on the effectiveness of the chosen representations. Students with verbal, visual, and symbolic dominant representations demonstrated different approaches in solving convergent sequence problems but followed a similar cognitive flow when transforming representations. Novelty: A systematic flow of mental activities for developing dominant representations in mathematical problem-solving. The findings contribute to mathematics education literature by explaining how representation transformation supports conceptual understanding of convergent sequences and promotes more effective learning practices aligned with the goals of quality education (SDG 4).
Administrative Cost Inefficiency of Local Tax Collection: Comparing Cities and Regencies in Supporting SDG 16
Objective: To measure the technical efficiency of local tax collection and identify the factors affecting the technical inefficiency of tax collection administrative costs in regency and city governments in Central Java Province. Method: Employing a quantitative approach using cross-sectional data from 35 regencies and cities in Central Java Province in 2019. Tax collection administrative costs are measured using the expenditure approach and analyzed using Stochastic Frontier Analysis (SFA) with Maximum Likelihood Estimation (MLE). Results: Local Own-Source Revenue (PAD) has a positive and significant effect on tax collection administrative costs. Gross Regional Domestic Product (GRDP) has a negative and significant effect, indicating that stronger economic activity improves tax collection efficiency. Population size significantly affects administrative costs, while the administrative status dummy variable reveals efficiency differences between regency and city governments. In addition, the size of the administrative area has a significant negative effect on technical inefficiency. The average technical efficiency of local tax collection reaches 87.34%, indicating that there is still room for efficiency improvement. Novelty: Contributing to the local public finance and sustainable governance literature by applying Stochastic Frontier Analysis (SFA) to evaluate tax collection administrative efficiency and comparing efficiency performance between regency and city governments in Central Java. The findings provide empirical evidence on how efficient local tax administration can support SDG 16 through the strengthening of effective and accountable public institutions under fiscal decentralization.
Sustainability Disclosure Practices in Islamic Banking: Do Audit Committees Matter for SDG 16?
Objective: To examine the influence of audit committee (AC) characteristics on the level of sustainability disclosure in Islamic Banks (IBs) listed on the Indonesia Stock Exchange during the period 2012–2021. Method: Employing a quantitative approach using purposive sampling to obtain 13 Islamic banks, resulting in 122 unbalanced panel data observations. Secondary data were collected from annual reports available on each bank’s official website. Sustainability disclosure items were adopted from Jan et al. (2019) and measured using content analysis techniques. The hypotheses were tested using panel data regression with the random effects model. Results: The findings indicate that Islamic banks disclosed only approximately 27% of the sustainability information expected. Furthermore, the number of audit committee members and audit committee independence significantly influenced sustainability disclosure practices, suggesting that effective oversight mechanisms encourage greater transparency regarding sustainability performance. Novelty: Extending the literature on sustainability disclosure by providing empirical evidence from Islamic banking institutions in Indonesia over a ten-year period, highlighting the critical role of audit committee characteristics, particularly committee size and independence, in strengthening transparency and accountability practices aligned with SDG 16 (Peace, Justice and Strong Institutions).
Development of Green Banking Disclosure Index in Southeast Asia Region: Contributing to SDG 13
Objective: To compile the Unweighted Green Banking Disclosure Index (UGBDI) for banks in Southeast Asia. The index is developed to provide a more suitable disclosure measurement for banks in the region, considering that existing green banking assessments are often based on standards from developed countries. Method: Using a literature review approach based on green banking regulations in Southeast Asian countries and previous studies. The index preparation was conducted through several stages, including identifying definitions and keywords, discerning and classifying similar items, synchronizing them with existing standards, and formulating new disclosure items. Results: Resulting in 32 green banking disclosure items for banks in Southeast Asia. These items were developed from regulations and prior studies, then synchronized with sustainable banking assessment standards. The resulting index can be used by banks, researchers, and regulators as a reference for evaluating and improving green banking disclosure practices. Novelty: Developing an original Green Banking Disclosure Index tailored to the Southeast Asian context by integrating regional green banking regulations and previous studies. The index contributes to SDG 13 (Climate Action) by enhancing climate-related disclosure practices and supporting the transition toward sustainable finance in the banking sector.
Unweighted Green Banking Disclosure Index (UGBDI)
Analysis of Microplastics in the Digestive Tracts of Mackerel Tuna (Euthynnus affinis) and Skipjack Tuna (Katsuwonus pelamis) for SDG 14
Objective: Marine ecosystems are increasingly threatened by microplastic pollution, which can accumulate in commercially important fish species and potentially affect human health. This study aimed to identify the characteristics and abundance of microplastics in the digestive tracts of mackerel tuna (Euthynnus affinis) and skipjack tuna (Katsuwonus pelamis) from Boneoge waters, Donggala Regency, and examine the relationship between digestive tract size and microplastic abundance. Method: A quantitative descriptive approach was employed using 30 specimens of each fish species collected from local fishermen. Digestive tract samples were digested using 10% KOH, incubated at 75°C, filtered, and observed under a binocular microscope. Microplastic abundance was expressed as particles per gram of digestive tract weight. Simple linear regression analysis using SPSS 25 was performed to evaluate the relationship between digestive tract size and microplastic abundance. Results: Three microplastic types were identified: film, fragment, and fiber, with film being dominant in both species. Total microplastic abundance reached 3.940 particles/g in mackerel tuna and 3.071 particles/g in skipjack tuna. Regression analysis showed a weak positive relationship between digestive tract size and microplastic abundance (R² = 0.137 and 0.140), suggesting that other environmental and biological factors play a greater role. Novelty: Providing the first baseline data on microplastic contamination in mackerel tuna and skipjack tuna from Boneoge waters, Central Sulawesi, and contributes to SDG 14 (Life Below Water) by strengthening evidence-based efforts to address marine microplastic pollution.
Feasibility of a Project-Based Electronic Module on Environmental Change to Promote Environmental Awareness and Support SDG 13
Objective: To evaluate the feasibility of the Project-Based Learning (PjBL) Environmental Change Electronic Module, known as E-Ling, as an interactive digital teaching material designed to support environmental change learning and improve students’ environmental awareness improve students’ environmental awareness and support SDG 13 (Climate Action). Method: Using a development approach with the ADDIE model, limited to the development stage. The feasibility of the E-Ling module was assessed through expert validation involving 12 experts in material, language, learning, and media. The instrument used was a validation questionnaire, and the data were analyzed using percentage-based feasibility criteria. Results: The expert validation results showed that the developed PjBL-based E-Ling module obtained positive feasibility scores, namely 92.33% from material experts, 80% from language experts, 84.71% from learning experts, and 86.33% from media experts. These results indicate that the module is categorized as good and requires no major revision. Novelty: The development of a PjBL-based electronic module that integrates environmental change materials, learning videos, interactive access through website or application platforms, and project activities to encourage students to learn independently and develop environmental awareness.
Framework Model for Sustainability Reliability Assessment of Clinical Laboratory Equipment in Indonesian Vertical Hospitals: Contributing to SDG 3
Objective: This study aims to develop a holistic framework for assessing the reliability of clinical laboratory equipment in vertical hospitals in Indonesia. Clinical laboratories play a strategic role in supporting National Health Insurance and in achieving the Sustainable Development Goals (SDGs) across economic, social, and environmental dimensions. Reliable maintenance systems are crucial for ensuring equipment reliability, maintainability, availability, and safety. Method: A comprehensive literature review of international journals was conducted to identify existing models and methodologies for reliability assessment. The proposed framework integrates reliability engineering, sustainability principles, and VUCA (volatility, uncertainty, complexity, ambiguity) concepts. The model consists of sub-assessment sections covering pre-analytical, analytical, and post-analytical stages, as well as equipment reliability, logistics and warehousing, and continuous equipment monitoring. Results: The framework provides a structured approach for identifying factors that influence the reliability of laboratory equipment, enabling effective assessment and problem-solving in clinical laboratories. It facilitates continuous evaluation, supports maintenance planning, and aligns with safety and quality standards. Novelty: Integrating reliability, sustainability, and VUCA concepts into a single, holistic framework for clinical laboratory equipment in Indonesian vertical hospitals. The proposed framework provides practical guidance for hospital policymakers and managers to ensure accurate testing results, optimize equipment performance, enhance patient safety, and support sustainable healthcare operations. By strengthening the reliability of diagnostic services and improving the quality and accessibility of healthcare delivery, this framework contributes to achieving SDG 3 (Good Health and Well-Being).
Performance Monitoring Model for Time and Cost Efficiency in Building Construction Projects: An Empirical Study Supporting SDG 9
Objective: To develop and evaluate an integrated performance monitoring model based on Earned Value Management (EVM) and Building Information Modeling (BIM) to improve time, cost, and quality efficiency in building construction projects. Method: A quantitative case study approach was applied using data from 204 building construction projects in Indonesia. The analysis employed Earned Value Analysis (EVA), correlation analysis, and multiple linear regression, with support from SPSS and BIM-based simulation tools. Results: The findings show that 50% of projects achieved a Cost Performance Index (CPI) between 1.0 and 1.1, while 60% recorded a Schedule Performance Index (SPI) between 0.9 and 1.1. In addition, 75% of projects met quality standards as measured by the Quality Performance Index (QPI). The integrated model significantly improves the early detection of project deviations and enhances the efficiency of corrective actions. Novelty: Integration of Earned Value Management (EVM) and Building Information Modeling (BIM) into a unified performance monitoring framework that enables real-time, data-driven decision-making for cost, time, and quality control in construction projects under external uncertainty conditions. This integrated framework also provides practical contributions to SDG 9 (Industry, Innovation and Infrastructure) by supporting innovative, resilient, and efficient infrastructure project management through digital performance monitoring.
Evaluation of the Performance of Floating Fiber Embankment Models for Tidal Flood Mitigation in Coastal Areas: Contributing to SDG 11
Objective: To evaluate the development of floating fiber embankment technology as an innovative solution for mitigating tidal flooding in coastal areas of Indonesia, particularly along the northern coast of the Java Sea. The proposed system is designed to automatically adapt to tidal level fluctuations, addressing challenges related to land subsidence and sea level rise. Method: The study employed a combined simulation and laboratory experimental approach to analyze the performance of the floating fiber embankment. Numerical simulations were conducted to evaluate the structural behavior under hydrostatic pressure, while laboratory testing was performed using a scaled physical model to validate the simulation results. Results: The findings indicate that the floating fiber embankment demonstrates stable structural performance under tidal loading conditions. The maximum recorded deformation was 0.0043 meters, with a maximum stress of 8.231 × 10⁶ Pa and a strain of 0.00045. These results confirm that the structure can maintain elasticity and structural integrity under hydrostatic pressure. Novelty: The application of adaptive floating fiber embankment technology that can automatically adjust to tidal fluctuations as a sustainable alternative to conventional static embankments. This system provides an effective and efficient solution to reduce the impact of tidal flooding in coastal regions while advancing SDG 11 (Sustainable Cities and Communities) by strengthening coastal resilience and supporting sustainable flood mitigation efforts.
YOLO-Based Real-Time Artificial Intelligence Traffic Counting for Urban Transportation Monitoring in Surakarta: Implications for SDG 11
Objective: To develop and evaluate an artificial intelligence (AI)-based traffic counting system using the YOLO (You Only Look Once) deep learning algorithm to provide accurate and real-time traffic volume data for urban transportation management. Method: Employing a deep learning approach by implementing the YOLO algorithm for vehicle detection and traffic counting. Traffic video data from road objects in Surakarta City were processed to identify and classify various vehicle types. The AI-generated traffic counting results were then compared with manual traffic survey data to assess the system’s accuracy and effectiveness. Results: The findings indicate that the proposed AI-based traffic counting system can accurately detect and classify multiple vehicle categories, including cars, motorcycles, trucks, buses, bicycles, and Bajaj. The traffic-counting data produced by the system were highly readable and reliable. Comparison with manual traffic surveys showed that the AI-generated results were very similar while requiring significantly less time and human resources. The system achieved nearly 100% consistency with the available secondary traffic volume data, demonstrating its effectiveness in monitoring urban traffic conditions. Novelty: Application of the YOLO deep learning algorithm for automated traffic counting in the urban road environment of Surakarta City. The proposed system provides a practical and efficient alternative to conventional manual traffic surveys by delivering accurate, real-time traffic data with minimal human intervention, thereby supporting more effective urban transportation planning and management. These contributions are also relevant to SDG 11 (Sustainable Cities and Communities) by enabling data-driven traffic monitoring and facilitating smarter, more sustainable urban mobility management.
The Effect of Biological Fertilizers on Growth and Yields of Soybean (Glycine max L. Merr.) under Drought Stress toward SDG 2
Objective: Soybean (Glycine max L. Merr.) is an important source of vegetable protein and a major food commodity. However, expanding soybean cultivation into dryland areas is constrained by drought stress, which adversely affects plant growth and productivity. This study aimed to evaluate the effects of biological fertilizers and drought stress on soybean growth and yield. Method: The experiment was conducted from October 2019 to January 2020 in a greenhouse using a factorial Randomized Block Design with three replications. The first factor was biological fertilizer application, consisting of no fertilizer, Plant Growth-Promoting Rhizobacteria (PGPR) at 10 g L⁻¹, and Arbuscular Mycorrhizal Fungi (AMF) at 10 g polybag⁻¹. The second factor was drought stress based on soil water availability (SWA): 100%–100%, 100%–50%, 50%–100%, and 50%–50% during vegetative and generative phases. Results: Biological fertilizers did not significantly affect soybean growth or yield. In contrast, drought stress significantly reduced plant height, leaf number, leaf area, root length, plant dry weight, pod number, seed number, and seed yield, with the greatest reductions occurring under 50% SWA during both growth phases. No significant interaction was observed between biological fertilizers and drought stress treatments. Novelty: Identify water availability as the primary determinant of soybean productivity under drought conditions, supporting sustainable food production and SDG 2 (Zero Hunger).
Regular vs Boarding Schools: Uncovering Indonesian Adolescents’ Psychological Well-Being Needs and Implications for SDG 3
Objective: To analyze and compare the psychological well-being of adolescents in regular and boarding schools in Indonesia. The findings are expected to provide evidence-based guidance for school counselors to identify adolescents' most urgent psychological needs and to optimize counseling services tailored to the characteristics of each school setting. Method: A quantitative study employing a cross-sectional group-comparison survey design was conducted. The participants comprised 798 adolescents, including 399 students from regular schools and 399 from boarding schools at the junior and senior high school levels. Data were collected using the Ryff Psychological Well-Being Scale (PWBS). The data were analyzed through normality testing and an independent-samples t-test to examine differences in psychological well-being between the two groups. Results: The findings revealed no significant difference in overall psychological well-being between adolescents in regular schools and those in boarding schools (p > .05). Although students in regular schools had a slightly higher mean score, the difference was not statistically significant. Descriptive analysis showed that self-acceptance was the weakest dimension among students in regular schools, whereas autonomy was the weakest dimension among students in boarding schools. Positive relationships with others represented the strongest dimension in both school types. Novelty: Extending previous research by directly comparing adolescents' psychological well-being across regular and boarding school contexts while identifying the most urgent psychological dimensions requiring intervention in each setting. The findings have practical implications for school counselors designing targeted interventions that focus on self-acceptance in regular schools and autonomy in boarding schools. These insights also offer important implications for SDG 3 (Good Health and Well-Being) by informing school-based mental health strategies that support adolescents' psychological well-being and healthy development.
Mindfulness for Optimizing Mental Health in Sports: A Systematic Literature Review and Implications for SDG 3
Objective: To synthesize and critically appraise recent empirical evidence on the role of mindfulness in optimizing mental health in sports, particularly among athletes and coaches. Method: Employed a systematic literature review using the PRISMA guidelines. Articles were searched through ScienceDirect and Google Scholar using the keywords mindfulness, sport, and mental health. The inclusion criteria covered English-language, open-access journal articles published between 2020 and 2024 that involved athletes or coaches and discussed dispositional mindfulness, mindfulness practice, or mindfulness-based interventions. After screening 65 full-text articles, 14 studies met the eligibility criteria and were analyzed narratively. Results: The findings indicate that mindfulness contributes positively to sports performance and mental health outcomes. Mindfulness-based interventions were reported to improve resilience, self-confidence, emotion regulation, subjective performance satisfaction, mindful awareness, well-being, and sleep quality. In addition, mindfulness helped reduce stress, anxiety, depression, tension, and the likelihood of choking during sports performance. Novelty: The review highlights mindfulness not only as a psychological training strategy to enhance sports performance but also as a promising approach to optimizing mental health in sports. The study also identifies the need for more rigorous randomized controlled trials with larger sample sizes and across diverse sports contexts. Furthermore, the findings offer important implications for SDG 3 (Good Health and Well-Being) by supporting the integration of evidence-based mindfulness approaches to promote psychological well-being, resilience, and mental health among athletes and coaches
Bridging Local Culture and Scientific Literacy through the I-BATARA Learning Model: Validation and Implications for SDG 4 Quality Education
Objective: To validate the I-BATARA learning model. The I-BATARA learning model, designed by integrating local cultural contexts, batik Tanjung Bumi, and scientific concepts, aims to improve science literacy. Method: Educational development research was used as the research design. Validation of the I-BATARA leaning model and instructional package involves two criteria: content validation and construct validation. Three experts in pedagogy, science content, and learning assessment validated the I-BATARA learning model and instructional package. Results: The research findings and data analysis indicated that the I-BATARA learning model has consistently yielded relevant outcomes. The I-BATARA model has met strict validity and reliability standards (with an agreement percentage >75%). Novelty: Validated learning support components include lesson plans, student textbooks, student worksheets, and scientific literacy tests. The I-BATARA learning model can be applied to foster students' scientific literacy through local cultural contexts. The model is suitable for meaningful science learning and for developing students' social skills, while offering practical implications for SDG 4 (Quality Education) by promoting culturally relevant, context-based scientific literacy instruction.
Developing the CTCR Learning Model to Enhance Elementary Students' Critical Thinking Skills: Implications for SDG 4 Quality Education
Objective: To develop a Critical Thinking Culturally Responsive (CTCR) learning model that is valid, practical, and effective for improving fifth-grade elementary students' critical thinking skills in science learning in East Kalimantan. Method: The study employed an Educational Design Research (EDR) approach using the Generic Design Research Model (GDRM) through five phases. Trials were conducted in three schools: Public Elementary School 011 Pela (limited trial, n = 6), Public Elementary School 016 Samarinda Ulu, and Muhammadiyah Elementary School Loa Janan (extended trial, n = 52). Results: The CTCR model achieved a very valid status (mean = 3.64) and was rated practical across all trial sites. The model was effective in improving students' critical thinking skills, as evidenced by a moderate mean N-gain of 0.52 and statistically significant gains across all classes (p < 0.05) Novelty: The CTCR model is the first to integrate Inquiry-Based Teaching, Critical Thinking Blended Learning, and Culturally Responsive Teaching into a single operational syntax for elementary schools in Indonesia, aligned with the Merdeka Curriculum, the Pancasila Student Profile, and the advancement of SDG 4 (Quality Education).
Energy Conservation Worksheets with Jigsaw Cooperative Learning Model to Improve Learning Outcomes Supporting SDG 4 in Science Education
Objective: This research aims to produce energy conservation worksheets based on the Jigsaw type cooperative learning model that are suitable for use and effective in improving students' science learning outcomes to support SDG point 4. Method: This research is a quantitative descriptive study using the Research and Development (R&D) method, aimed at developing and testing the effectiveness of the learning product. The development process uses the ADDIE model, which includes the following stages: Analysis, Design, Development, Implementation, and Evaluation. The research population was conducted at one school with a sample of 50 students. Results: Research shows that Jigsaw-based cooperative learning worksheets are valid, practical, and effective for use in science learning on energy conservation in elementary schools. The implementation of worksheets can significantly improve student learning outcomes, as evidenced by pre-test, post-test, difference test, and N-Gain values in the experimental class. In addition, students responded positively to the learning because discussion activities and group collaboration made it more active, interesting, and easier to understand. Novelty: The innovations in this worksheet development are relevant to SDG 4, particularly in ​​energy conservation. In the context of science education, SDG 4 implementation aims to strengthen student learning outcomes through innovative learning approaches.
Copyright (c) 2026 Journal of Current Studies in SDGs https://creativecommons.org/licenses/by/4.0
Installing Method and Subconscious Learning: A Sustainable English Learning Innovation Through Subconscious Knowledge Transfer in Kuanta Indonesia
Objective: This study aims to analyze the design, concept, and implementation of the Installing Method and Subconscious Learning in English learning at Kuanta Indonesia. The study also seeks to explore how subconscious-based learning can accelerate English mastery without traditional memorization and repetitive drills. Method: This research employed a descriptive qualitative approach conducted at Kuanta Indonesia as the research site. Data were collected through observations, interviews with master installers and learners, and documentation analysis. The data analysis process involved unitizing, recording, reducing, inferring, analyzing, and narrating to ensure data trustworthiness and comprehensive interpretation. Results: The findings reveal that the Installing Method emphasizes subconscious activation through alpha-wave learning conditions, allowing learners to absorb knowledge naturally and automatically. The learning process minimizes conscious memorization and analytical thinking, resulting in relaxed and efficient learning experiences. Students demonstrated rapid English mastery, improved confidence, and positive behavioral changes. The implementation includes structured learning programs, subconscious-based knowledge transfer, and rule-based learning environments that support automatic language acquisition. Novelty: This study introduces a new paradigm in English learning through subconscious installation rather than conventional learning methods. The Installing Method integrates subconscious brain activation, energy-based knowledge transfer, and behavioral transformation into a unified learning framework. This approach offers an innovative alternative for fast and effective English mastery and contributes to the development of transformative language learning methodologies.
Design Optimization of Rectangular Microstrip Antenna Using Deep Neural Network for 3 GHz Applications in Support of SDG 9
Objective: This study aims to investigate the effectiveness of Deep Neural Networks (DNN) for optimizing the design of a rectangular microstrip antenna operating at a target frequency of 3 GHz. The research focuses on improving antenna design efficiency by predicting antenna performance parameters based on geometric characteristics. Method: The study employed a computational simulation approach combined with machine learning techniques. A synthetic dataset consisting of 6000 antenna configurations was generated using analytical microstrip antenna equations. The dataset included geometric parameters such as dielectric constant, substrate thickness, patch width, patch length, and inset feed position. A Deep Neural Network model was trained to predict resonant frequency, return loss, and input impedance. The trained model was then used as a surrogate model to evaluate 30,000 candidate antenna designs and identify the optimal configuration. Result: The proposed model achieved high predictive accuracy with values of 0.9987 for resonant frequency prediction and 0.9988 for input impedance prediction. The optimized antenna design produced a resonant frequency of 2.996 GHz, return loss of −18.70 dB, and input impedance of 53.95 Ω, which closely match the target specifications for S-band wireless applications. Novelty: The study demonstrates that Deep Neural Networks can significantly accelerate antenna design optimization by replacing repetitive electromagnetic simulations with data-driven prediction models.
The Validity of Biology Interactive E-book based Scientific Literacy to Improve Student’s Creative Thinking Skills to Support SDG 4
Objective: This study aims to describe the validity of Biology Interactive E book Based on Scientific Literacy to Improve Students’s Creative Thinking Skills. The developed Biology Interactive E book Based on Scientific Literacy to Improve Students’s Creative Thinking Skills validity is evaluated in terms of content feasibility, presentation feasibility, and language feasibility. Method: This research is a development research with a ADDIE model (Analysis, Design, Development, Implementation, and Evaluation), which is modified in the Postgraduate Program in Science Education at the State University of Surabaya and implemented in SMA N 1 Bancar, Tuban, East Java. The data collection technique was carried out using the ebook validation method. Results: The assessment instrument used was a e book validation sheet used by two biology lecturers as validators. Data analysis was carried out quantitatively. The validation results of this inquiry-based textbook obtained an average score of 92.25% with a very valid category. Novelty: Based on the analysis of the data obtained, it can be concluded that the Biology Interactive E book Based on Scientific Literacy to Improve Students’s Creative Thinking Skills that has developed are valid and suitable for use in learning. The development of interactive e-books is one part of realizing quality education (SDG 4) in the era of technology adoption.
Copyright (c) 2025 Journal of Current Studies in SDGs https://creativecommons.org/licenses/by/4.0/
Profile of Students’ Physics Problem-Solving Skills and the Implementation of Digital Book-Assisted PBL for SDG 4
Objective: This study aims to analyze the profile of students' physics problem-solving skills as a basis for applying the digital book-assisted Problem-Based Learning (PBL) model to sound wave material at the high school level. This analysis was conducted to determine the level of students' problem-solving abilities and to identify differences in abilities based on gender as a basis for developing more effective learning strategies. Method: This study used a quantitative descriptive approach involving 108 high school students as research subjects. The research instruments included a physics problem-solving skills test, a student response questionnaire, and interviews with physics teachers. The test was compiled based on problem-solving skill indicators that included understanding the problem, planning the solution, implementing the strategy, and evaluating the solution. The data were analyzed using the Rasch model to obtain more accurate measurements of student ability levels and question difficulty levels. Results: The results showed that students' physics problem-solving skills were generally still in the low category. Most students had difficulty understanding problems conceptually, determining the appropriate solution strategy, and evaluating the results of the solution. Analysis based on gender shows that the abilities of male and female students are relatively balanced. However, female students tend to be more thorough in descriptive and evaluative aspects, while male students are more prominent in the solution planning stage. Novelty: The novelty of this study lies in the analysis of students' physics problem-solving skill profiles from a gender perspective using the Rasch model as an empirical basis for developing a more interactive and contextual 3D digital book-assisted PBL model to improve students' physics problem-solving skills.
Glocal Wisdom in Earthquake Mitigation and Education for Sustainable Development
Objective: This study systematically analyses how glocal wisdom — the integration of local and global knowledge — supports earthquake mitigation and education for sustainable development (ESD). It identifies research patterns, key themes, and gaps in the linkage between cultural wisdom and disaster risk reduction and sustainability education. Method: A Systematic Literature Review (SLR) based on the PRISMA protocol was conducted using the Scopus database. From an initial 66,648 records (2015–2025), 15 peer-reviewed articles were selected through multi-stage filtering based on year, subject area, document type, language, and open-access criteria. Data were analysed using bibliometric mapping and thematic content analysis. Results: Four dominant themes emerged: (1) local knowledge in structural mitigation, (2) glocal wisdom in community-based education, (3) ESD integration models, and (4) policy and implementation gaps. The increase in studies from 2020 to 2023 reflects growing global interest in integrating indigenous knowledge into modern disaster education systems. Novelty: This research redefines glocal wisdom as a core epistemological foundation for sustainable and disaster-resilient education. By combining bibliometric and qualitative analyses, this study proposes a new integrative framework that links traditional knowledge, scientific innovation, and pedagogy to advance ESD and disaster literacy.
Education For Sustainable Development (ESD)
Multiple Intelligences in Digital Physics Learning for Education for Sustainable Development
Objective: This study aims to synthesise research on the application of Multiple Intelligences (MI) in digital physics learning within the framework of Education for Sustainable Development (ESD). The goal is to map trends, highlight opportunities for personalised, sustainability-oriented learning, and identify gaps that hinder the integration of MI and digital technologies to foster sustainability competencies. Method: A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Articles were collected from Google Scholar, Scopus, IEEE Xplore, ERIC, and ScienceDirect, limited to peer-reviewed studies published between 2018 and 2023 in English or Indonesian. Forty eligible studies were analysed thematically and through content analysis. Results: The findings show that MI-based digital learning enhances students' motivation, engagement, conceptual understanding, and academic performance. Interactive simulations, video-based modules, virtual experiments, and AR/VR applications offer personalised learning aligned with students' dominant intelligences. MI also supports ESD competencies such as critical thinking, collaboration, and sustainability awareness, though aspects like environmental literacy, social responsibility, and ethical reasoning remain underexplored. Novelty: This review uniquely links the MI, physics education, and ESD domains, which are rarely integrated in prior studies. It emphasises MI's potential to enhance cognitive outcomes while embedding sustainability values into physics education. A conceptual roadmap is proposed to align MI-based digital physics learning with the Sustainable Development Goals.
Curriculum Analysis to Evaluate Sustainable Learning in High School Physics Through AI-Based Learning Media for SDG 9
Objective: The objective of this research is to analyze the implementation of the curriculum at SMAN 1 Cerme, Gresik, in order to identify the alignment of learning outcomes with applicable curriculum standards. This study also aims to contribute to achieving the Sustainable Development Goals (SDGs), particularly SDG 4 (Quality Education), which emphasizes inclusive and equitable quality education, and SDG 9 (Industry, Innovation, and Infrastructure), which encourages innovation in educational practices. Method: This research employs a qualitative descriptive method. Primary data were obtained from interviews and decisions issued by KOSP SMAN 1 Cerme, while secondary data were collected through observations and student response questionnaires. Results: The findings reveal that SMAN 1 Cerme applies the K-13 curriculum for grade XII and the Merdeka Curriculum for grades X and XI. The implementation demonstrates the importance of monitoring and evaluation to ensure the curriculum effectively supports the school's vision and mission. Novelty: This research's novelty lies in integrating curriculum analysis with the Sustainable Development Goals framework. By linking curriculum implementation to SDG 4 and SDG 9, this study highlights how curriculum transformation not only supports local educational objectives but also contributes to global efforts to promote quality education and foster innovation in learning infrastructure.
Theoretical Review: Adiabatic Coupler Engineering and Modification in Supporting SDGs 9 Efficient Optic Technology Engineering and Innovation
Objective: This study aims to describe the application of adiabatic coupler modification in efficient optical coupler engineering and to emphasize its contribution to the achievement of SDG 9 (Industry, Innovation, and Infrastructure). Method: The method used is a literature study through a review of relevant articles and Python software-based analysis to evaluate the impact of coupler modifications, as an effort to strengthen theoretical findings. Results: The results of this study show that the invariance principle-based reverse engineering approach is practical in designing directional couplers on waveguides. Combined with perturbation analysis of the coupled mode equations, this method produces directional couplers that are highly robust to parameter variations such as coupling coefficient and wavelength. However, changes in scale or resonance through Python integration do not significantly affect the apparent deviation of the coupler wave, so the efficiency of the coupler is mainly determined by the coupling coefficient and wavelength variations. Novelty: This study highlights the novelty of utilizing the invariance principle and resonance modification as an efficient and straightforward approach for adiabatic coupler optimization. Furthermore, the results demonstrate the significant contribution of adiabatic couplers to SDG 9 through their support for the development of sustainable optical communication infrastructure, increased energy efficiency, and innovation in next-generation optical technologies.