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The rapid development of information technology has created significant opportunities for secondary schools to improve the quality of learning through the use of digital-based applications. This study aims to design and develop a web-based tutoring application for students of Junior High School (SMP) Negeri 1 Tana Righu by applying Object Oriented Technology (OOT) as the software development approach. OOT was chosen for its ability to simplify the system design process through structured modeling using the concepts of classes, objects, attributes, and relationships between objects. The developed application provides various features, including the presentation of learning materials, interactive practice questions, learning outcome evaluations, and student progress reports accessible in real time by both teachers and students. The research method consisted of needs analysis, system design using UML diagrams, implementation, and application testing. The testing results indicate that the tutoring application is effective in improving the learning process, assisting teachers in monitoring and evaluating student progress, and providing students with a more engaging and interactive learning experience. Therefore, this application is expected to serve as an innovative solution to support tutoring activities in secondary schools and contribute positively to enhancing the quality of education in the digital era.

This study focuses on how the use of Student Worksheets (LKPD) can support the Islamic Religious Education (PAI) learning process at MIS Al-Hidayah. Using a qualitative approach, researchers explored the experiences of teachers and students through interviews, observations, and documentation. The results indicate that LKPD equipped with visual media can create a more engaging learning environment, motivate students, and facilitate their understanding of the material. Teachers design LKPD with pictures and sequential steps, enabling students to be more active and able to learn independently or in groups. Despite obstacles, such as limited time for development and incomplete school facilities, teacher creativity and collaboration with colleagues proved key to success. These findings confirm that LKPD can be an effective learning tool, not only for improving cognitive understanding but also for instilling Islamic values ​​in students. This study also has implications for the development of PAI learning strategies in madrasah-based elementary schools. Thus, the innovative use of LKPD can become a sustainable learning model to improve the quality of Islamic education in the future.

This study aims to analyze the effect of training on the performance of regional innovation data entry in Boyolali Regency in 2024 through the BI-SMART system. The population of this research consisted of 83 civil servants (ASN) serving as BI-SMART application operators, with a sample of 30 ASNs selected using purposive sampling. A quantitative approach was employed using a Likert-scale questionnaire, which was tested for validity and reliability. Data analysis was performed using simple linear regression preceded by classical assumption tests (normality and heteroskedasticity tests). The results show that training has a positive and significant effect on the performance of innovation data entry, as evidenced by a t-value of 4.721 and a significance level of 0.000 (<0.05). These findings confirm that structured and practical training can improve the accuracy, completeness, and timeliness of data entry. The study contributes theoretically by strengthening the concepts of transfer of training, adult learning, and Kirkpatrick’s evaluation model, while practically providing strategic recommendations for the Boyolali Regency Government in designing more effective training programs to support data-driven regional innovation governance.

The spirituality of today’s church youth encounters multidimensional challenges, particularly the pervasive influence of digital culture, the gradual decline in interest toward spiritual disciplines, and the weakening of involvement in ecclesial ministry. Such dynamics often create a gap between theological knowledge and lived faith experiences. This Community Service (PkM) initiative was designed to respond to these issues by implementing an interactive model aimed at enhancing the spiritual understanding of the youth at GKSI Trimorejo Congregation. The model emphasizes participatory learning processes, in which youth are not merely passive recipients of teaching but active contributors to collective faith formation. The methodological framework consisted of three main stages: initial observation to identify needs and spiritual conditions; preparation of training modules contextualized with the congregation’s realities; and the implementation of interactive activities such as group discussions, thematic Bible studies, role-play, and collective reflection. Evaluation strategies integrated both quantitative and qualitative approaches, including pre-tests and post-tests to measure cognitive growth, alongside participatory interviews to capture experiential insights. The findings reveal a notable increase in youth comprehension of biblical principles, heightened enthusiasm and participation in church programs, and the establishment of a more cohesive spiritual learning community. Furthermore, the process encouraged a deeper sense of belonging and responsibility among the participants toward their ecclesial environment. In conclusion, the interactive model demonstrates significant effectiveness in fostering youth spirituality and may serve as a viable alternative strategy for churches encountering similar challenges within contemporary contexts of ministry.

Indonesia, a country located in the Pacific Ring of Fire, has a high level of vulnerability to earthquakes. This condition demands an increase in the capacity of civil engineering human resources to design safe and disaster-resistant buildings. This study aims to evaluate the effectiveness of project-based learning training with a focus on the application of SNI 1726:2019, structural modeling using ETABS/RSA, lateral load calculations, and the design of simple earthquake-resistant houses. The research method involved final-year civil engineering students and alumni who participated in a series of trainings, with evaluations through pre-tests, post-tests, and design assessments. The results showed an increase in competency in all aspects, especially the understanding of the SNI 1726:2019 standard and lateral load calculations. In addition, participants were able to produce simple house designs that meet the basic criteria for earthquake resistance, material efficiency, and structural stability. These findings indicate that applied training can bridge the gap between academic theory and practical skills needed in the workplace. This research contributes to strengthening the capacity of civil engineering in supporting resilient infrastructure development and has important implications for the integration of similar training into higher education curricula and community service programs.

The aim of this research is to determine the influence of the Games Based Learning Model on the Learning Activeness of Class The research method used is a quantitative method with a descriptive inferential type. The population was 182 students of Class Data was collected using a closed questionnaire with 14 items for variable Y and 18 items for variable 2025 is shown through: 1) Test analysis requirements: a) positive relationship test obtained rxy = 0,308 > rtabel(α=0,05; IK=95%; n=49) = 0,281.  b) a significant relationship test is obtained from the value thitung = 2,222 > ttabel = 2,021. 2) influence test: a) regression equation test, obtained the regression equation Ŷ  = 42,221  (α) + 0,365 (X).  b) regression coefficient of determination test (r2) = 9,5%. 3hypothesis testing using Fhitung  > Ftabel=(α=0,05,dk pembilang n-1=48, dk penyebut=n-2=49-2=47) yaitu 4,938 > 1,620.Thus H0 is stating there is no influence is rejected and Ha which states there is an influence is accepted.  

Tomato crop yields face significant threats from plant diseases, with existing deep learning solutions often computationally prohibitive for resource-constrained agricultural settings; to address this gap, we propose Efficient Disease Attention Network (EDANet), a novel lightweight architecture combining depthwise separable convolutions with hybrid attention mechanisms for efficient Tomato disease recognition. Our approach integrates channel and spatial attention within hierarchical blocks to prioritize symptomatic regions while utilizing depthwise decomposition to reduce parameters to only 104,043 (multiple times smaller than MobileNet and EfficientNet). Evaluated on ten tomato disease classes from PlantVillage, EDANet achieves 97.32% accuracy and exceptional (~1.00) micro-AUC, with perfect recognition of Mosaic virus (100% F1-score) and robust performance on challenging cases like Early blight (93.2% F1) and Target Spot (93.6% F1). The architecture processes 128×128 RGB images in ~23ms on standard CPUs, enabling real-time field diagnostics without GPU dependencies. This work bridges laboratory AI and practical farm deployment by optimizing the accuracy-efficiency tradeoff, providing farmers with an accessible tool for early disease intervention in resource-limited environments.

Islamic Religious Education (PAI) plays a crucial role in fostering good morals in students, enabling them to develop Islamic character and face the challenges of the times with strong spiritual values. However, the implementation of PAI teaching in the field often still prioritizes traditional lecture methods, which lead to less student participation, boredom, and less than satisfactory learning outcomes. This small study aims to explore the PAI learning models and strategies implemented by teachers at the Al-Hidayah Foundation, the challenges they face, and their impact on students. This study used a qualitative approach with a case study method through in-depth interviews with PAI teachers. The results revealed that teachers have begun to integrate lecture methods with more innovative learning strategies such as contextual, cooperative, and technology-based, although their implementation has not always been consistent. The main challenges faced include limited infrastructure, a lack of professional training for teachers, and low learning motivation among some students. The visible impact is increased student engagement in the learning process when innovative strategies are implemented, although their effectiveness still needs to be strengthened with support from the institution and parents. Therefore, the Islamic Religious Education teachers at the Al-Hidayah Foundation not only function as teachers, but also as motivators and facilitators in the learning process to ensure that the goals of Islamic education can be achieved properly.

This study aims to examine the effect of the Time Token learning model on the speaking skills of fifth-grade students at SD Negeri Parung Bingung 1. The research employed a quantitative approach with a quasi-experimental design. The sample consisted of 58 students, divided into an experimental class (using the Time Token model) and a control class (using direct instruction). Data were collected through speaking skill tests (pre-test and post-test) and analyzed using descriptive and inferential statistical tests. The findings revealed a significant improvement in speaking skills in the experimental class compared to the control class. The average pre-test score of the experimental class increased from 23.67 to 35.03 in the post-test, while the control class improved from 31.07 to 40.11. An independent t-test indicated that the Time Token learning model had a significant effect on students’ speaking skills (p < 0.05). The study concludes that the Time Token model is effective in enhancing students’ speaking skills by providing equal opportunities for each student to speak, reducing anxiety, and promoting active participation in learning. Therefore, this model can serve as an alternative for teachers in developing more interactive and effective teaching methods.

To respond to the challenges and needs of contemporary society, the public sector must rapidly adapt to digital transformation. The objective of this research is to examine relevant and adaptive human resource development strategies for the digital ecosystem and to evaluate how they impact the quality of public services in the era of technological disruption. This research uses a descriptive qualitative approach with a literature review and policy analysis. It analyzes best practices from government institutions, both national and international, in developing human resources oriented towards the digital era. Key findings indicate that optimizing human resources requires not only improving technological capabilities or digital expertise; it also requires reconstructing leadership paradigms, flexible organizational cultures, and implementing meritocratic systems and data-driven performance management. It is evident that technologies such as big data analytics, artificial intelligence (AI), and the Internet of Things (IoT) can help improve public services, but the success of these technologies depends heavily on the capabilities and readiness of the employees who manage these systems. An integrated digital talent ecosystem must be built, encompassing continuous training (learning for life), collaboration between government, academia, and business (the triple helix model), and a regulatory framework responsive to technological developments. Furthermore, it is emphasized that developing digital integrity and ethics is crucial as a pillar of good governance in the digital era. Optimizing human resource development strategies systematically and sustainably will enable Indonesia to improve the efficiency of public services and strengthen the competitiveness of its bureaucracy globally. By 2045, adaptable, innovative, and highly integrated human resources will be the primary drivers of a digital government transformation that is inclusive, responsive, and future-oriented.

This study aims to improve student learning outcomes through the implementation of the Problem Based Learning (PBL) model assisted by PowerPoint media in Mathematics for Grade I students at SD IT Riyadhoturrohman. The research employs Classroom Action Research (CAR) conducted in two cycles. Each cycle consists of three meetings, following the stages of planning, implementation, observation, and reflection. The research subjects were 16 students from Grade I of SD IT Riyadhoturrohman. The Problem Based Learning model was chosen because it encouraged students to be actively involved in learning through solving contextual problems, while PowerPoint media was used to help visualize the mathematical concepts being taught. The results showed an improvement in students' learning outcomes from the pre-action stage to Cycle I, and a further increase in Cycle II. Additionally, students demonstrated improved participation, conceptual understanding, and teamwork skills. Thus, the implementation of the Problem Based Learning model assisted by PowerPoint media proved to be effective in improving the mathematics learning outcomes of Grade I students at SD IT Riyadhoturrohman.

The daily exchange of informatics over the Internet has both eased the widespread proliferation of resources to ease accessibility, availability and interoperability of accompanying devices. In addition, the recent widespread proliferation of smartphones alongside other computing devices has continued to advance features such as miniaturization, portability, data access ease, mobility, and other merits. It has also birthed adversarial attacks targeted at network infrastructures and aimed at exploiting interconnected cum shared resources. These exploits seek to compromise an unsuspecting user device cum unit. Increased susceptibility and success rate of these attacks have been traced to user's personality traits and behaviours, which renders them repeatedly vulnerable to such exploits especially those rippled across spoofed websites as malicious contents. Our study posits a stacked, transfer learning approach that seeks to classify malicious contents as explored by adversaries over a spoofed, phishing websites. Our stacked approach explores 3-base classifiers namely Cultural Genetic Algorithm, Random Forest, and Korhonen Modular Neural Network – whose output is utilized as input for XGBoost meta-learner. A major challenge with learning scheme(s) is the flexibility with the selection of appropriate features for estimation, and the imbalanced nature of the explored dataset for which the target class often lags behind. Our study resolved dataset imbalance challenge using the SMOTE-Tomek mode; while, the selected predictors was resolved using the relief rank feature selection. Results shows that our hybrid yields F1 0.995, Accuracy 0.997, Recall 0.998, Precision 1.000, AUC-ROC 0.997, and Specificity 1.000 – to accurately classify all 2,764 cases of its held-out test dataset. Results affirm that it outperformed bench-mark ensembles. Result shows the proposed model explored UCI Phishing Website dataset, and effectively classified phishing (cues and lures) contents on websites.

The rapid expansion of digital platforms in higher education has paved the way for Virtual Exchange (VE) as a viable alternative to traditional student mobility programs. VE leverages online technologies to connect university students from diverse cultural and academic backgrounds, enabling cross-cultural communication and global collaboration without the financial and geographical barriers associated with physical exchanges. Despite its potential, challenges remain regarding student engagement, technological limitations, and reduced immersion compared to face-to-face interactions. This study aims to evaluate the effectiveness of VE in fostering intercultural awareness and teamwork skills among university students. A mixed-method approach was employed, combining quantitative surveys to measure intercultural competence and collaboration with qualitative interviews to explore students’ experiences in depth. The findings indicate that VE contributes significantly to the development of intercultural understanding, digital literacy, and teamwork, with students reporting enhanced awareness of cultural diversity and improved adaptability in online collaboration. Visual and statistical analyses highlight clear patterns in how VE facilitates skill development, while qualitative data emphasize both the benefits and obstacles students encounter, such as managing time zone differences and cultural nuances. The study concludes that VE represents an inclusive and scalable educational approach that complements traditional exchange programs, offering broader access to global learning opportunities while addressing issues of equity and accessibility. However, its limitations suggest that VE should be integrated strategically, potentially through hybrid models that balance virtual and physical mobility to maximize its impact.

This research aims to: (1) produce mathematics learning media in the form of interactive e-modules with a learning approach.realistic mathematics education (RME) which is oriented towards numerical ability and mathematical growth mindset students and describe their characteristics; (2) describe the quality of the learning e-module which meets the criteria of being valid, practical and effective so that it is suitable for use by junior high school students using the approach realistic mathematics education (RME). The development model used in this development research is the ADDIE development model (Analysis, Design, Development, Implementation, and Evaluation). The research subjects consisted of one teacher and 32 seventh grade students of SMP Negeri 3 Pajangan in Bantul Regency, Yogyakarta, who participated in this research.The results of the study show that the developed e-module has the following main characteristics: (1) using the RME approach in learning strategies; (2) facilitating the improvement of numeracy through learning videos, LKPD, and quizzes; (3) fostering growth mindset through motivational videos, inspirational sentences, discussion spaces, as well as feedback and self-evaluation features; and (4) using test- and questionnaire-based evaluation instruments. Validity tests showed very good results with an average score of 96% from media experts and 98% from material experts. The practicality of the e-module was assessed as very good by teachers (96.19%) and good by students (80.47%), and the implementation of learning reached 96.8%. Effectiveness was proven through MANOVA and t-tests which showed a significant increase in numeracy and mathematical growth mindset after using the e-module. Thus, the RME-based interactive e-module is suitable for use as an innovative mathematics learning medium at the junior high school level.

The aim of this research is to determine the assistance of parents using child therapy in regulating emotions when accompanying children to study at home. This research was conducted at the homes of 3 families who had children aged 4-7 years and the parents could not control their emotions when accompanying their children to study at home. The object of this research is parental assistance in the child's learning process at home. The data collection techniques used were observation, interviews and image documentation. The research method using data analysis is an interactive model. The research results showed that by being given Filial Therapy treatment, namely regulatory skills, setting boundaries, attentive listening, and focused play with children for 1 month, the informants were able to carry out Filial Therapy in a flexible and integrated manner. By applying Filial Therapy skills, parents become better able to regulate emotions, namely by reassessing cognitive and expression abilities. The assistance provided by parents is through filial therapy, parents accompany children to play and are directly involved in the game, there must be communication with parents, children are given the freedom to play, so that it will regulate parents' emotions in accompanying children to study at home.

This study aims to determine the effect of Problem Based Learning (PBL) and Inquiry learning models on students’critical thinking skills and cognitive learning outcomes on the topic of the human respiratory system. This research used a quasi-experimental design with a Non-Equivalent Pretest-Posttest Control Group Design. The research subjects were three eighth-grade classes at SMP Negeri 13 Lebong, consisting of two experimental classes taught using the PBL and Inquiry models and one control class using conventional methods. The research instruments included essay tests to measure critical thinking and multiple-choice tests to assess cognitive learning outcomes. Data were analyzed using ANOVA and LSD tests. The results showed significant differences among the three groups. The PBL model produced the highest improvement in both variables, followed by Inquiry, and lastly the control group. Therefore, PBL is proven to be the most Effective model inimproving students' critical thinking and cognitive learning outcomes in science education.

This study aims to analyze the application of deep learning in the transformation of religious moderation education in the digital era and its implications for the development of modern Islamic education. The research employs a qualitative descriptive approach using library research, reviewing literature on Islamic education, religious moderation, and artificial intelligence in learning contexts. Data were collected from academic books, scientific journals, articles, and other credible sources, then analyzed using content analysis to identify patterns, concepts, and relationships between technology and the strengthening of moderation values. The results indicate that the implementation of deep learning can transform Islamic education from a traditional rote-based model to a reflective, contextual, and interactive learning process. This technology enables the analysis of students’ thinking patterns and behaviors, the reinforcement of moderation values, character formation, and the development of moderate digital literacy in a personalized and adaptive manner. The integration of technology and spirituality in digital Islamic education creates transformative learning experiences that strengthen empathy, ethical awareness, and students’ reflective capacities. The study implies the importance of developing curricula, learning strategies, and teacher competencies based on artificial intelligence to produce a generation of students who are moderate, tolerant, and competent in facing the challenges of the digital era.

The rapid advancement of intelligent systems has accelerated the adoption of data-driven solutions across diverse industries, creating an increasing need for models that are both efficient and privacy-preserving. While traditional centralized machine learning approaches offer strong predictive capabilities, they often struggle with challenges related to data privacy, network latency, and computational inefficiency-especially in distributed environments with heterogeneous devices. To address these limitations, recent research has explored hybrid learning frameworks that integrate federated learning, edge computing, and dynamic model optimization techniques. These hybrid approaches enable models to process and learn from data closer to the source while maintaining stringent privacy requirements by keeping raw data localized. Additionally, the incorporation of pruning strategies, adaptive model compression, or multimodal data fusion contributes to improved speed, scalability, and accuracy in real-time inference tasks. Such frameworks have demonstrated notable promise in settings characterized by high data volume, operational complexity, and the necessity for fast anomaly detection or decision-making. However, despite these advancements, several challenges remain, including synchronization delays across edge nodes, variability in hardware capabilities, and the need for more efficient aggregation algorithms. Future developments may involve leveraging next-generation pruning techniques, energy-aware edge scheduling, decentralized orchestration protocols, or the integration of digital twin technologies to further enhance performance. Overall, hybrid distributed learning frameworks represent an important evolution toward more intelligent, secure, and autonomous computational ecosystems capable of supporting the next wave of smart applications.

Local religious traditions play a crucial role in maintaining spirituality, cultural identity, and social cohesion within communities, particularly in rural areas that continue to uphold traditional values. This study aims to examine in depth the influence of the Puja Bhakti Keliling tradition on the level of participation of Buddhist devotees in various religious activities in Sumogawe Village. The study employs a quantitative approach with an associative design, involving 60 purposively selected respondents, and the data were analyzed using simple linear regression. The findings indicate that this tradition contributes significantly to the active engagement of the devotees, with an R² value of 0.634 and a regression coefficient of 0.756, confirming its positive effect. Dimensions of togetherness, social interaction, and spiritual meaning were identified as the main factors driving active participation. The results also reveal low participation in Dhamma learning sessions, highlighting the need for innovation in educational methods and more engaging learning approaches within lay communities. The Puja Bhakti Keliling tradition has proven to serve as a spiritual, social, and educational medium that holistically supports community resilience and the sustainability of religious practices. This study recommends strengthening this traditional model through intergenerational support, innovative participatory learning methods, and contextual approaches that align with community needs.

The integration of blockchain technology with Multi-Agent Reinforcement Learning (MARL) presents a promising solution for optimizing resource allocation and ensuring security in decentralized network environments, particularly in 5G and 6G network slicing. This research proposes a model that combines the security features of blockchain with the adaptive, decentralized decision-making capabilities of MARL. Blockchain ensures the integrity and transparency of resource allocation by providing a secure, tamper-proof ledger for transaction validation, while MARL allows agents to dynamically allocate resources based on real-time network conditions. The simulation results demonstrate significant improvements in resource allocation efficiency, fairness among users, and resilience to cyberattacks. By combining these two technologies, the proposed model overcomes many of the challenges posed by traditional centralized systems and offers an enhanced, secure, and fair solution for resource distribution in future mobile networks. However, scalability remains a challenge, especially in large-scale networks where transaction processing and consensus overhead can create bottlenecks. Additionally, training complexity in MARL models presents computational challenges, particularly in highly dynamic network environments. The model's performance trade-offs, including the balance between high security and system overhead, are also discussed. Future research should focus on optimizing blockchain consensus mechanisms to improve scalability and enhancing MARL model training techniques to reduce computational costs and improve real-time decision-making. This integration holds significant potential for revolutionizing resource allocation in 5G and 6G networks, enabling more efficient, secure, and fair management of network resources in the increasingly complex and decentralized digital ecosystem