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Economic forecasting is becoming increasingly important year after year, especially during crises such as the pandemic of COVID-19 and the Russia-Ukraine war. Its development can be seen from the use of basic statistical models to the increasingly widespread use of machine learning technology. Economic forecasting plays an important role in helping to formulate policies and is also a reliable tool for researchers in dealing with uncertainty. Global crises, such as inflationary pressures due to the pandemic and supply chain disruptions from the Russia-Ukraine conflict, have prompted increased research in this field in an effort to anticipate economic shocks and emphasize the urgency of forecasting to prepare strategies for dealing with future uncertainty. This literature review uses the Scopus database with 2561 publications from 2020 to 2025, analyzed using R Studio with a bibliometrix approach (specifically biblioshiny) and VOSviewer to map relevant thematic connections. This analysis shows that economic forecasting is greatly influenced by market uncertainty and geopolitical factors, and at the same time influences public policy formulation and financial stability. Research contributions from Indonesia are still limited, with only 40 documents, thus emphasizing the need to strengthen economic forecasting studies in Indonesia to support monetary policy and national financial stability.

This study was motivated by the low level of internalisation of religious values in Islamic Religious Education, especially at the madrasah level, where the process of instilling valuesoften stops at the cognitive level. This study aims todescribe the process of internalising religious values through the film Laut Tengahand assess its effectiveness in improving students' understanding andappreciation of religious values at MTs Manbail Futuh 2 Bancar. The approach used was qualitative with a case study design, because the phenomenon under reviewwas contextual and required in-depth understanding. Datawere collected through direct observation during learning, interviews with teachers andstudents, as well as documentation of learning tools and film clips. Data analysiswas carried out through data condensation, data presentation, and drawingconclusions using the Miles, Huberman, and Saldaña model. The results showedthat the film Laut Tengahwas effective in facilitating the internalisation of religious values through the visual,emotional, and cognitive engagement of students. Students were able to identify values such ashonesty, patience, discipline, gratitude, and social awareness, anddemonstrated appreciation reflected in their self-reflections. With teacher guidance, films became a medium capable of connecting values with the real experiences ofstudents.

This community service activity aims to strengthen the role of higher education institutions in preserving local culture through the revitalization of cultural arts learning based on local wisdom, particularly traditional Nias carving art. The main problems faced by the partners include the limited availability of contextual cultural arts learning, minimal integration of traditional art practices into university courses, and students’ low understanding of the philosophical values embedded in Nias carving motifs. The implementation method employs a participatory–educational approach consisting of preparation, socialization, theoretical and practical training, intensive mentoring, and evaluation stages. This activity involves students and lecturers as participants as well as agents of cultural preservation. The results indicate a significant improvement in participants’ knowledge of the symbolic meanings of Nias carving motifs, their basic skills in designing and drawing carving motifs, and their appreciative attitudes toward the preservation of local cultural arts. This activity contributes to the strengthening of cultural arts learning in higher education and has the potential to serve as a sustainable model of community service based on local culture.

This study presents a high-accuracy real-time soft failure detection framework for large-scale fiber-to-the-home(FTTH) optical access network using a hybrid ensemble of Isolation Forest and One-Class Support Vector Machine (OCVSM). The proposed model was trainde and validated on a real-word multivariate performance dataset comprising more than 1.8 million samples collected at 5-minute intervals from 50 Optical Line Terminal (OLTs) and over 3,000 Optical Network Terminals (ONTs) across a five-month periode(June-October 2025). Ground-truth validation was performed using 111 confirmed network incidents in October 2025 affecting 12,990 customer. The hybrid ensemble achieved Precision 0.940, Recall 0.982, with an average detection delay of only 7.8 minutes-representing an 87.7% reduction compared to conventional manual response (63.5 minutes). The framework significantly outperforms traditional threesholding and recent ML-based methods while demonstrating practical deployability in live operational enviroments.

The rapid development of digital technology and the increasing demand for entrepreneurial competence in higher education require students to possess adequate digital literacy and financial literacy, as well as obtain continuous institutional support to shape and strengthen their entrepreneurial interest. This study aims to empirically analyze the influence of digital literacy, financial literacy, and institutional support on the entrepreneurial interest of students in the Islamic Business Management Study Program at the Faculty of Economics and Islamic Business, UIN Raden Mas Said Surakarta. A quantitative approach was used, involving 75 respondents selected through accidental sampling, while the research data were analyzed using multiple linear regression. The results of the study indicate that all three independent variables have a positive and significant effect on students' entrepreneurial interest, with the model contributing 42.7%. These findings highlight the importance of integrating digital competencies, effective financial management, and a supportive campus ecosystem to foster students' entrepreneurial intentions. This study provides practical implications for higher education institutions to strengthen curricula, learning facilities, and mentoring programs aimed at developing young, digitally-driven, and sustainable entrepreneurs.

This study examines how integrating local ecological wisdom and eco-literacy education fosters environmental awareness, behavioral transformation, and health outcomes among Indonesian primary school students. The research responds to the ecological paradox of rapid technological growth amid worsening environmental degradation, where youth eco-literacy remains below 45%, indicating a gap between environmental knowledge and sustainable action. The study aims to develop a culturally responsive model of sustainability education that connects environmental ethics, cultural identity, and public health. Using a qualitative case study design, the research was conducted at SD Islam Kreatif Mutiara Anak Sholeh, Sidoarjo, East Java, from July to August 2025, involving 60 students and six teachers. Data were collected through semi-structured interviews, observations, and document analysis. Four major themes emerged: (1) cultural narratives as catalysts for environmental awareness, (2) eco-literacy as experiential and behavioral transformation, (3) collaborative learning as collective environmental agency, and (4) eco-health as psychosocial and physical well-being. Findings show that integrating Majapahit-era ecological values and local storytelling into eco-brick and composting projects enhanced students’ responsibility, cooperation, and emotional balance. The study synthesizes Eco-pedagogy, Constructivism, and Eco-health frameworks into a Culturally Responsive Eco-Health Pedagogy, demonstrating that sustainability learning rooted in culture and participation promotes both environmental and health outcomes. This model contributes to the global Education for Sustainable Development (ESD) 2030 agenda by linking culture, ecology, and well-being in primary education.

The development of technology in the digital era has brought significant changes to global education systems, including in Indonesia. Digital transformation encourages learning models that are more flexible, interactive, and focused on 21st-century competencies. However, this progress also presents various challenges, particularly related to moral degradation among youth, unequal access to technology, and low digital literacy among teachers and students. This study aims to analyze character education models from a global perspective and evaluate the challenges and strategies for their implementation in Indonesia in the digital era. Using a qualitative research method with a library research approach, data were obtained from credible sources such as scientific journals, books, official reports, and national and international educational documents. The findings indicate that developed countries have successfully integrated technology into their curricula, teacher training, and educational policies, resulting in well- established digital learning ecosystems. In Indonesia, digitalization in education has grown rapidly, especially since the pandemic, but still faces obstacles such as limited infrastructure, varied levels of digital competence among teachers, and a lack of integration of digital pedagogy. In addition, student readiness and access inequality in frontier, outermost, and disadvantaged regions (3T) present further challenges in applying global education models

The mathematics learning outcomes of students at SMP Negeri 3 Bontang on Rational Numbers are still relatively low. Data from the 2019 National Examination (UN) shows an average math score of 46.43, which is in the "poor" category. Summative assessment results indicate that most students have not yet achieved the Learning Objective Achievement Criteria (KKTP). This situation indicates that the learning process tends to be conventional and lacks active student engagement. Therefore, a more innovative learning model is needed, one of which is the Team Games Tournament (TGT), which combines group work, competition, and educational games. This study aims to determine the effect of the TGT learning model on the mathematics learning outcomes of seventh-grade students at SMP Negeri 3 Bontang in the topic of Rational Numbers. This study used a quantitative approach with a quasi-experimental type and a Posttest-Only Control Group Design. The study population was 203 seventh-grade students in the 2024/2025 academic year, with a sample consisting of class VII A as the experimental group (33 students) and class VII F as the control group (34 students), selected through a purposive sampling technique. The research instrument was a five-item essay test. The analysis results showed that the average posttest of the experimental group was 67.848, higher than the control group at 61.794. The Independent Sample t-Test produced a significance value of 0.031 <0.05, so H₀ was rejected. This indicates that the Team Games Tournament (TGT) learning model has a significant effect on improving students' mathematics learning outcomes in the Rational Numbers material.

Diseases in primary health services exhibit complex spatial-temporal dynamics due to urbanization and population mobility. Conventional surveillance approaches are difficult to capture these patterns adaptively. Machine learning (ML) based on spatio-temporal modeling offers a solution with the ability to detect disease clusters automatically and with high precision. Research Objectives: This research aims to develop a machine learning model to detect disease hotspots from primary service data in Indonesia, with a focus on improving prediction accuracy, interpretability, and relevance of health policies. Methodology: The primary service dataset for 2024 (5,343 entries) was analyzed using three ML models Gradient Boosting Machine (GBM), Temporal Random Forest (TRF), and Multi-EigenSpot with spatial (village) and temporal (week, month) features. Performance evaluation includes predictive (AUC, F1-score) and spatial (Moran's I, Spatio-Temporal Correlation Index) metrics. Results: The results showed that Multi-EigenSpot achieved the best performance (AUC=0.91; F1=0.86), with the detection of dominant hotspots in Sungai Asam and Beringin Villages. Moran's I value of 0.63 indicates a strong spatial autocorrelation, while STCI=0.57 indicates moderate temporal stability. Conclusions: ML-based spatio-temporal models are effective in identifying hidden disease patterns and have the potential to be integrated into national digital surveillance systems. This approach supports precision public health by providing a scientific basis for real-time location- and time-based intervention policies.

Cross-Cultural Experience: Introducing Balinese Traditional Clothes to Walailak University Students in Thailand is part of an international community service program (KKN) that students from the Institute of Technology and Education Markandeya Bali took part in. The main goal of this activity was to introduce Balinese cultural values by teaching students about traditional Balinese clothes as a way to learn about different cultures. This study uses a qualitative descriptive approach with the CIPP (Context, Input, Process, Product) evaluation model to evaluate the success of the activity. The results of this activity show that there is an increase in understanding, fostering an attitude of appreciation, and strengthening cross-cultural communication among students. This activity is effective as a medium for cultural diplomacy and experiential learning.

This research aims to develop GeoQuest, an interactive learning media integrated with Artificial Intelligence (AI), to enhance the understanding of trigonometry concepts among Grade XI students at SMAN 1 Percut Sei Tuan. The development follows the Research and Development (R&D) approach using the ADDIE model, which consists of Analysis, Design, Development, Implementation, and Evaluation. The product integrates AI-based features such as adaptive practice questions, automated feedback, and dynamic visualizations of trigonometric graphs. Data were collected through expert validation, student response questionnaires, and learning outcome tests. The results show that the media meets the criteria of validity, practicality, and effectiveness. Material experts and media experts rated GeoQuest as "very valid," while students responded positively to its ease of use and engaging interface. Learning outcome tests indicate a significant improvement in students’ understanding of trigonometry after using the AI-based GeoQuest media. Thus, GeoQuest is proven to be a reliable and effective digital learning tool to support trigonometry learning.

Cross-Cultural Experience: Introducing Balinese Traditional Clothes to Walailak University Students in Thailand is part of an international community service program (KKN) that students from the Institute of Technology and Education Markandeya Bali took part in. The main goal of this activity was to introduce Balinese cultural values by teaching students about traditional Balinese clothes as a way to learn about different cultures. This study uses a qualitative descriptive approach with the CIPP (Context, Input, Process, Product) evaluation model to evaluate the success of the activity. The results of this activity show that there is an increase in understanding, fostering an attitude of appreciation, and strengthening cross-cultural communication among students. This activity is effective as a medium for cultural diplomacy and experiential learning.

This qualitative study, using a phenomenological approach, aims to uncover, study, and deeply understand students' perspectives regarding the curriculum transformation for 21st-century learning they experience in elementary schools. The phenomenological approach was used to explore students' direct experiences as the primary subjects in the learning process, thus gaining a comprehensive understanding of the meaning of curriculum change from their perspectives. Data collection was conducted through in-depth interviews with upper-grade students in elementary schools in Jambi City. The results indicate that the curriculum transformation has a significant impact on students' learning styles, particularly through the implementation of project-based learning that integrates the use of digital technology. This learning model encourages students to be more active, creative, and collaborative in completing learning tasks. Furthermore, student-centered learning makes them the primary actors in the learning process, while teachers act as facilitators. This curriculum transformation also helps develop 21st-century skills, such as critical thinking, communication, collaboration, and digital literacy in elementary school students.

General education at Islamic Religious Higher Education Institutions (PTKI) plays an important role in developing students’ critical thinking skills so they can analyze religious and social issues reflectively and contextually. However, learning practices in PTKI are still dominated by teacher-centered approaches and low cognitive achievement, which limits the development of analytical, evaluative, and problem-solving abilities. Meanwhile, studies show that integrating digital media, particularly video, can improve conceptual understanding, motivation, and cognitive engagement, yet a digital video-based meaningful learning model specifically designed for the PTKI context remains limited. Therefore, this study aims to formulate a Digital Video-Based Meaningful Learning Model (MPBBVD) to enhance students’ critical thinking skills. This research employed a literature review method by analyzing books, scientific articles, research reports, and digital sources related to meaningful learning, constructivism, multimedia learning, digital video use, and critical thinking development. Data were analyzed descriptively and qualitatively to identify the theoretical foundations, learning syntax, and design principles of the model. The findings indicate that MPBBVD integrates Ausubel’s Meaningful Learning theory, constructivist perspectives from Piaget, Vygotsky, and Bruner, Mayer’s Multimedia Learning theory, and the critical thinking framework of Facione and Ennis. The model uses digital video as the main learning medium and applies the ACTIVE stages (Attend, Connect, Think, Interpret, Verify, Evaluate) to promote contextual and interactive learning. Integrating pre-, during-, and post-video activities supports knowledge construction, reduces cognitive load, and increases student engagement, contributing theoretically and practically to improving critical thinking in PTKI in the Industrial Revolution 4.0 era.

Gross motor development is an essential aspect of early childhood education because it contributes to body coordination, balance, muscle strength, and children’s readiness for physical activities. One of the activities that can be used to stimulate gross motor skills is dancing, particularly regional creative dance. This community service program aims to implement the Janger creative dance as a medium to develop gross motor skills in kindergarten group B children. The method used was evaluative with the CIPP model (Context, Input, Process, Product), involving observation, interviews, and documentation. The activity was carried out once a week through stages of rhythm introduction, basic movements, body coordination, and simple dance sequences. The results showed that more than 80% of the children experienced improvement in aspects of balance, movement coordination, agility, and large muscle control. In addition, the activity also enhanced children's self-confidence, courage, and social interaction. Therefore, the Janger dance is proven to be effective as a gross motor stimulation and is suitable to be used as a culturally based learning strategy in early childhood education.

Gross motor development is an essential aspect of early childhood education because it contributes to body coordination, balance, muscle strength, and children’s readiness for physical activities. One of the activities that can be used to stimulate gross motor skills is dancing, particularly regional creative dance. This community service program aims to implement the Janger creative dance as a medium to develop gross motor skills in kindergarten group B children. The method used was evaluative with the CIPP model (Context, Input, Process, Product), involving observation, interviews, and documentation. The activity was carried out once a week through stages of rhythm introduction, basic movements, body coordination, and simple dance sequences. The results showed that more than 80% of the children experienced improvement in aspects of balance, movement coordination, agility, and large muscle control. In addition, the activity also enhanced children's self-confidence, courage, and social interaction. Therefore, the Janger dance is proven to be effective as a gross motor stimulation and is suitable to be used as a culturally based learning strategy in early childhood education.

: The rapid expansion of cybersecurity standards and threat intelligence frameworks has led to significant semantic fragmentation among security terminologies, hindering effective information retrieval and interoperability across systems. Traditional keyword-based search approaches are inadequate for capturing the contextual meaning of security terms, particularly within formal frameworks such as NIST, MITRE ATT&CK, and CWE. This study addresses this challenge by proposing CyberBERT, a transformer-based semantic search framework designed to align cybersecurity terminologies through deep contextual representation and ontology-driven reasoning. Research Objectives: The primary objective of this research is to develop a semantic retrieval model capable of understanding conceptual relationships between security terms beyond lexical similarity. Methodology: The proposed methodology fine-tunes a BERT-based model on the NIST Glossary corpus using a combination of masked language modeling and triplet loss objectives to generate discriminative semantic embeddings. These embeddings are further aligned with cybersecurity ontologies, including MITRE ATT&CK and CWE, to enhance semantic consistency and explainability. Semantic retrieval is performed using cosine similarity within a 768-dimensional embedding space and evaluated using Mean Reciprocal Rank (MRR) and Precision@K metrics. Results: Experimental results demonstrate that CyberBERT achieves an MRR of 0.832, outperforming domain-adapted baselines such as SecureBERT and CyBERT. The integration of ontology alignment improves semantic accuracy by over 6%, while robustness evaluations confirm resilience against adversarial linguistic perturbations. Visualization using t-SNE reveals coherent semantic clustering aligned with the five core NIST Cybersecurity Framework functions. Conclusions: In conclusion, CyberBERT effectively bridges semantic gaps across cybersecurity terminologies by combining transformer-based contextual learning with ontological reasoning. The framework offers a robust, interpretable, and scalable solution for semantic search, supporting improved interoperability and knowledge discovery in cybersecurity operations and standards harmonization.

Globalization and modernization amid the strong digital flow have become a huge challenges and obstacles for shaping moral and ethics of the students. There are many students who come to the class physically without having readiness and awareness in the study. Teacher as an educator needs to give an efforts in every process of learning with attractive concept and model to give attention and meaning in the study. Through the mindful learning, it is considered capable of giving full attention and self-awareness while studying which in the end not only gives good quality in learning but also shapes islamic ethics in the stundents. This research aims to know the concept, urgency, and the implementation of mindful learning which is capable of shaping islamic ethics. The method of the research is a qualitative approach with a literature study from various readings such as articles and journals that are relevant to the topic. The reasearch results show that mindful learning is a learning process that emphasizes self-reflection and self-awareness so students feel ready and motivated in learning. It shows that deep learning has a huge urgency in shaping student’s Islamic ethics. The implementation of mindful learning in Islamic education Studies is carried out through the pedagogic strategies that emphasize the conditioning of awareness, active students involvement, and deep reflection of Islamic values. Thus, mindful learning is capable of increasing internal awareness through muraqabah with the involving of students in every learning process.

The dynamics of student organization structure have significant implications for talent retention and student career development. This study aims to comparatively analyze the influence of centralization and decentralization structures in the Information Technology Study Program Student Association on the effectiveness of talent retention strategies and career development capacity. The research method uses a quantitative approach with a comparative design involving 120 respondents selected through purposive sampling technique with criteria of at least one period of organizational experience. Data collection instruments use structured Likert scale questionnaires that have been tested for validity and reliability with Cronbach's Alpha values above 0.80. Data analysis uses Structural Equation Modeling and independent sample t-test to compare both structural models. The results show that the decentralization structure has a strong significant effect on talent retention with a path coefficient of 0.628 compared to centralization of 0.312. Comparative analysis identifies substantial differentiation in all dimensions of career development with the decentralization structure consistently outperforming centralization, especially in the aspect of decision-making autonomy. The findings confirm that the distribution of authority in decentralization creates a learning ecosystem that facilitates diversification of leadership experiences and strengthens students' organizational commitment through participatory empowerment mechanisms.

End-to-end autonomous driving has emerged as a promising paradigm in which deep neural networks directly map raw visual inputs to continuous control actions. Despite its effectiveness, this approach suffers from limited transparency, posing significant challenges for deployment in safety-critical driving scenarios. This study addresses the lack of interpretability in vision-based end-to-end autonomous driving systems and aims to analyze model decision-making behavior under critical conditions such as sharp steering maneuvers and abrupt control transitions. To this end, an explainable end-to-end autonomous driving framework is proposed, combining a convolutional neural network trained via imitation learning with gradient-based visual attribution techniques, including Grad-CAM. The model predicts continuous steering, throttle, and braking commands directly from front-facing camera images, while explainability mechanisms are applied to reveal input regions influencing each control decision. Model performance is evaluated using both prediction accuracy and safety-oriented behavioral metrics. Experimental results show that the proposed explainable model achieves lower control prediction errors compared to a baseline end-to-end CNN, reducing steering mean squared error from 0.034 to 0.031, throttle error from 0.021 to 0.019, and brake error from 0.018 to 0.016. Moreover, safety-oriented analysis indicates improved driving stability, with steering variance reduced from 0.087 to 0.072 and abrupt control changes decreased from 14.6 to 10.3 events. Visual explanations consistently highlight road surfaces and lane-related structures during complex maneuvers, indicating reliance on semantically meaningful cues. In conclusion, the results demonstrate that integrating explainability into end-to-end autonomous driving not only preserves predictive performance but also correlates with smoother and more stable driving behavior. This framework contributes to the development of transparent and trustworthy autonomous driving systems suitable for safety-critical applications