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This study examines the role of mathematics learning in improving logical thinking skills in early childhood. The background of this study is based on the importance of logical thinking skills as a foundation for children's cognitive development, which can begin at an early age through appropriate mathematics learning. The purpose of this study is to analyze how mathematics learning can stimulate the development of logical thinking in early childhood and explore effective learning strategies. The methods used are library research and observation of several models of mathematics learning for early childhood in early childhood education institutions. The findings indicate that fun and concrete activity-based mathematics learning can improve children's abilities in critical thinking, constructing patterns, drawing conclusions, and solving simple problems. The implications of this study emphasize the need for the application of creative and interactive mathematics learning methods to support the development of logical thinking from an early age, while also encouraging educators to integrate mathematics into children's daily activities. This study also recommends the development of learning media appropriate to children's developmental stages for optimal results.

This study aims to explain the application of various differentiated learning techniques based on Problem-Based Learning (PBL) to improve analytical and writing skills related to procedural texts among junior high school students. This research is based on students' lack of ability to understand and compose procedural texts methodically and in accordance with language conventions, which is caused by the prevalence of conventional teacher-centered learning. This study used a descriptive qualitative methodology involving seventh-grade students from a junior high school that has adopted the PBL model in Indonesian language subjects. Data were collected through observation, interviews, and documentation, then analyzed qualitatively. The results showed that the application of PBL along with differentiated learning and TPACK increased student engagement, accommodated diverse learning styles, and fostered critical thinking, analytical abilities, and collaborative skills. Learning became more meaningful and relevant, enabling students to compose procedural texts more effectively. This study recommends the application of the PBL model with differentiation as an innovative strategy to improve the quality of Indonesian language education in junior high schools.

This study aims to classify customer payment methods at 17 Coffee & Eatery using machine learning algorithms, namely Naïve Bayes and Support Vector Machine (SVM). The increasing use of digital and non-cash payments has generated large volumes of transaction data that are rarely analyzed optimally, even though such data contain valuable information for business decision making. This research used secondary transaction data collected from January to March 2025, consisting of 10,147 transaction records. The dataset included several attributes such as order time, payment time, transaction type, total sales, number of items, and payment method. Data preprocessing was performed through data cleaning, feature engineering, normalization, and label encoding before being divided into training and testing sets with an 80:20 ratio. The Naïve Bayes and SVM models were then trained and evaluated using accuracy, precision, recall, F1-score, and ROC–AUC metrics. The results show that both algorithms were able to classify payment methods effectively, but SVM achieved higher accuracy and more stable performance than Naïve Bayes. These findings indicate that SVM is more suitable for handling complex and heterogeneous transaction patterns. The implementation of machine learning for transaction classification can support more efficient financial management and data-driven decision making for small and medium enterprises in the culinary sector.

AImbalanced data remains a significant issue in heart disease classification using machine learning, as it tends to cause models to overestimate the majority class while ignoring minority classes with high clinical value. This can lead to a decrease in accuracy and the model's ability to accurately detect disease cases. Therefore, this study aims to assess the effectiveness of oversampling techniques, namely Random Oversampling and Synthetic Minority Oversampling Technique (SMOTE), in improving the performance of the K-Nearest Neighbors (KNN), Naive Bayes (NB), and Random Forest (RF) algorithms. The dataset used comes from Kaggle and consists of 918 data sets with 12 attributes representing patient information related to heart disease prediction. The research stages include data preprocessing, baseline model testing, and re-evaluation using the two oversampling methods. Experimental results show that oversampling can improve the performance of all algorithms. KNN achieved the best results with SMOTE, with an accuracy of 72.98% and an F1-score of 75.39%. In the Naive Bayes algorithm, both oversampling techniques produced relatively stable performance, with the highest F1-score of 73.56% using SMOTE. Meanwhile, Random Forest showed the most optimal performance when combined with Random Oversampling, with an accuracy of 79.19% and an F1-score of 81.51%. These findings confirm that the success of data balancing techniques is strongly influenced by the characteristics of the classification algorithm used, and provide a practical contribution in determining strategies for handling imbalanced data in health research.

The rapid development of technology in today's era requires every profession to align with existing developments. The teaching profession is no exception. Teachers must be able to utilize technology in the learning process to create an engaging learning environment for students. To support this capability, training is essential. This community service activity aims to provide training to teachers at Bancong  Elementary School in Wonoasri District, Madiun Regency, to familiarize themselves with and be able to use the GeoGebra application. This training also aims to improve teachers' competency in utilizing digital technology as a learning medium. The GeoGebra application is an effective application for solving mathematics problems in elementary schools, particularly in geometry, particularly plane figures. The implementation method for this activity includes preparation, training, and mentoring. The training was provided in the form of workshops and hands-on practice using GeoGebra-based mathematics learning media. The activity proceeded orderly and smoothly, and the training participants understood the material well, both theoretically and in practice.

This study aims to improve the kinesthetic intelligence and physical fitness of students with hearing impairments through rhythmic gymnastics lessons in Physical Education, Sports, and Health (PJOK) at SLB Muhammadiyah Kelayu, East Lombok Regency. The research employed a collaborative classroom action research (CAR) approach involving both the researcher and the PJOK teacher. The action was conducted in two cycles, each comprising planning, implementation, observation, and reflection stages. The research subjects consisted of eight students with hearing impairments, including four females and four males. Data were collected through documentation, observation, and performance assessments using developed kinesthetic intelligence and physical fitness instruments, and then analyzed descriptively using quantitative methods. The results indicate that after the rhythmic gymnastics intervention, kinesthetic intelligence improved, with 75% of students reaching the expected development level by the end of Cycle II. Physical fitness also showed significant improvement across five main components: endurance increased to 68.7%, muscle strength and endurance to 65.6%, agility to 68.7%, flexibility to 65.6%, and balance to 71.8%. Rhythmic gymnastics proved to be an effective approach to support inclusivity while enhancing the kinesthetic intelligence and physical fitness of students with hearing impairments.

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.

The rapid development of digital streaming platforms such as Netflix has generated a large volume of content data with diverse characteristics, thereby requiring effective analytical methods to understand emerging patterns and trends. This study aims to classify Netflix content into two main categories, namely movies and television shows, and to analyze genre trends and content characteristics using a data mining approach with the Naive Bayes algorithm. The dataset used in this study is the Netflix Shows dataset, consisting of 8,809 content entries, with the primary features analyzed including genre, rating, and country of production. The research process begins with data exploration and preprocessing stages, including data cleaning, handling missing values, and transforming categorical features to enable effective model construction. Subsequently, the dataset is divided into training and testing sets to objectively and systematically build and evaluate the Naive Bayes classification model. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics to assess the model’s ability to accurately distinguish between Netflix content types. The experimental results demonstrate that the Naive Bayes algorithm is able to classify Netflix content into Movie and TV Show categories with accuracy, precision, recall, and F1-score values of 100%, respectively. The confusion matrix indicates that no misclassification occurred, suggesting that genre, rating, and country of production features provide a very clear separation between content classes. These findings indicate that the Naive Bayes algorithm can achieve exceptionally high classification performance with optimal evaluation results. The results further reveal distinct differences in characteristics between movies and television shows based on genre and production attributes. Therefore, this study is expected to contribute to the development of content recommendation systems and strategic content management within the streaming industry.

This psychoeducation is motivated by the need for service support for students with special needs at SLB Negeri Pembina Yogyakarta. Some students with intellectual disabilities require assistance in recognizing and expressing their emotions. The purpose of this counseling activity is to provide appropriate media needed to support the development of students’ emotional expression in everyday social interactions. The counseling method employed was a play-based learning approach. The evaluation of the effectiveness of this method involved 10 students with intellectual disabilities, consisting of 7 male students and 3 female students in Grade VII of junior high school. Based on the results of the counseling activities, which were conducted in three stages—namely the opening stage, the emotion recognition stage, and the application of the emotion wheel—it was found that the use of the emotion wheel media strengthened the emotional expression abilities of students with intellectual disabilities. This improvement was evident from observable changes in the emotional behavior of some students.

Digital literacy is important in education in the era of Society 5.0, because teachers are required to be facilitators in supporting students to become digital learners. To support the success of students in becoming digital learners, the role of teachers in the use of technology during learning activities also contributes. The existence of these demands makes the use of virtual reality media in the learning environment an alternative that can be done to create learning activities that meet the demands in the Society 5.0 era. The purpose of this service activity is to improve the digital literacy of IGI Pekanbaru. as well as introduce virtual reality-based learning media as a renewable learning media innovation to support student learning activities in the digital era. In this service, the methods include presentation, demonstration, and practice. The results showed that teacher training in making VR learning media can improve their digital literacy. This training can also help teachers create interactive and interesting technology-based collaborative learning media for modern learning.

The use of technology-based learning media, such as Smart TVs, has great potential in improving the quality of learning in elementary schools (SD). Smart TVs can support interactive learning, enrich teaching materials, and increase student learning motivation. However, in reality, many elementary schools still face limited supporting facilities so that their use is not optimal. This study analyzes the use of Smart TV in elementary schools with limited infrastructure, teacher readiness, and its impact on the learning process. The analysis method was carried out qualitatively through the study of school conditions, observations, and interviews with teachers. The results of the study show that the limitations of the internet network, the lack of supporting devices, and the lack of teacher training are the main factors that hinder the effectiveness of the use of Smart TVs. The impact of these limitations is the low integration of technology in learning, limited access to digital materials, and the suboptimal role of teachers as facilitators. Therefore, policy support from the government, improving school facilities, and teacher training programs are needed so that the use of Smart TVs can run optimally. The conclusion of the study emphasizes that Smart TV has the potential to become an innovative learning medium in elementary schools if supported by adequate infrastructure facilities and teacher competence in accordance with the demands of the digital era.

Islamic character education faces dual challenges: declining moral values among students and conventional teaching methods inadequate for developing higher-order thinking skills. This study examines the implementation of a smart learning environment (SLE) model to enhance metacognitive understanding in Aqidah Akhlak (Islamic Creed and Ethics) instruction among eighth-grade students at MTs Salafiyah Merakurak. Employing a mixed-methods action research design, involved 16 eighth-grade students divided into two groups. Data collection utilized classroom observations, semi-structured interviews, and learning documentation. The SLE model integrated Google Classroom, interactive video content, WhatsApp Group discussions, and Google Forms assessments to create a technology-enhanced learning ecosystem. Findings revealed substantial improvements in students' metacognitive capacities: planning skills increased from 25% to 75%, monitoring abilities rose from 31% to 81%, and evaluation competencies grew from 19% to 69%. Students demonstrated enhanced learning autonomy, active participation in collaborative discussions, and improved self-reflection on content comprehension. The SLE approach successfully fostered engaging learning experiences while facilitating deeper internalization of Islamic ethical values. However, implementation encountered constraints including limited technological infrastructure and varied digital literacy levels among students. This research underscores the critical need for developing teachers' digital competencies and strengthening madrasah technological infrastructure to optimize technology-integrated Islamic education.

The Ministry of Social Affairs has made a new breakthrough in facilitating the public in checking social assistance recipients, namely the social assistance check application. User reviews can be used to find out whether the application provides benefits to the community or not. However, these reviews need to be processed using sentiment analysis. Then to do sentiment analysis requires machine learning. One method that includes machine learning is Naïve Bayes. The purpose of this research is to implement the Naïve Bayes method in conducting sentiment analysis and find out whether the social assistance check application is beneficial to society based on the results of sentiment analysis. In this study, two categories of sentiment are used, namely positive and negative. The author collects by crawling using the Google Play Scrapper library. The results of crawling data obtained as many as 4000 data. The results showed that the actual data that had been labeled using Textblob resulted in 987 negative label reviews and 628 positive label reviews. Meanwhile, the Naïve Bayes method is able to analyze the review sentiment of the social assistance check application with the results of 1181 negative sentiments and 434 positive sentiments. The Naïve Bayes model has a good accuracy rate of 0.77 or 77% in analyzing sentiment for social assistance check application reviews.

The Mastery Learning Strategy is a learning approach oriented towards achieving comprehensive student competencies before they move on to the next material or learning stage. This approach is based on the assumption that every student has the potential to succeed, provided they are given the appropriate time, methods, and guidance. In its application, Mastery Learning emphasizes systematic learning planning, the establishment of clear learning objectives, and ongoing evaluation to measure the level of student mastery. Students who have not yet achieved competency standards will receive corrective feedback and remedial activities, while students who have completed them will be provided with enrichment programs to deepen their understanding. With this mechanism, learning gaps can be minimized so as not to hinder the learning process in the next stage. Furthermore, this strategy encourages individualized, structured, and measurable learning according to student needs. Therefore, the implementation of Mastery Learning is considered effective in improving the quality of the learning process, strengthening conceptual understanding, and contributing to optimal and sustainable learning outcomes.  

Public speaking is an essential communication skill that plays a crucial role in enhancing self-confidence, delivering ideas effectively, and fostering social participation. However, many women in rural areas still lack opportunities to develop this skill due to limited access to training, gender stereotypes, and minimal experience in public forums. These challenges lead to low levels of women’s involvement, particularly housewives who are members of PKK, in community activities and decision-making processes at the local level. This study aims to examine the impact of public speaking training on improving the knowledge, self-confidence, and social participation of PKK mothers in Nagari Sumpur Kudus. The research employed a descriptive qualitative method with a participatory approach through interactive lectures, speaking practice simulations, reflective discussions, participatory observations, and qualitative evaluations. Data were analyzed using data reduction, data display, and conclusion drawing based on field notes, observations, and participants’ feedback. The findings indicate that the training successfully improved participants’ understanding of basic public speaking techniques, including intonation, eye contact, body language, and structured idea delivery. Furthermore, the participants experienced significant growth in self-confidence, courage to speak in front of groups, and motivation to continuously practice their communication skills. The interactive and supportive learning atmosphere also strengthened collaboration and solidarity among PKK members. Thus, public speaking training not only enhances individual competencies but also contributes to women’s empowerment and their active participation in community development at the village level.  

This study aims to evaluate the impact of role-playing methods on learning interest and number concept mastery in 4-5-year-old children at TK Inomata, Suwawa Selatan District, Bone Bolango Regency. The approach used is a quantitative experimental method with purposive sampling of 8 children, and data collection was carried out through observations of aspects such as enjoyment, focus, activity, and enthusiasm, using a 1-4 scale. The results show that the average learning interest score using the traditional method was only 5.86 (low category), with details: enjoyment 1.71, focus 1.29, activity 1.29, and enthusiasm 1.57. In contrast, the role-playing method of trading/store games showed an average score of 13.86 (very good category), with details: enjoyment 3.57, focus 3.43, activity 3.29, and enthusiasm 3.57. This significant improvement indicates that the role-playing method is more effective in creating interactive, enjoyable, and contextual learning, as well as supporting number comprehension through everyday activity imitation and social skill development. It is recommended to routinely apply this method in early childhood education (PAUD) with adequate teaching aids, as well as involve parents to support the holistic development of children during the golden age.

This study aims to describe the implementation process of the Christian Religious Education teaching module with the topic "Human Life in God's Care" for seventh-grade students of SMP Negeri 12 Palangka Raya. The focus of the activity was directed to determine the implementation of learning, student responses, and learning outcomes achieved through the biblical story approach, discussion, reflection, and creative poster-making projects. The research method used was descriptive qualitative with data collection techniques through observation, documentation, and assessment of work results. Data were analyzed through the stages of data reduction, data presentation, and conclusion drawing. The results showed that the implementation of the teaching module went well and achieved the learning objectives. Students were able to understand the concept of God's care, relate God's word to personal life experiences, and demonstrate an attitude of gratitude through reflection and discussion. In addition, students produced a poster with the theme "God Cares for My Life" as a form of creative expression and the meaning of faith. Despite several obstacles such as limited time for the project and variations in student activity levels, learning remained effective and conducive. The assessment showed positive developments in the cognitive, affective, and psychomotor aspects of students.

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.

This research examines the implementation of the Deep Learning approach in Islamic Religious Education (PAI) learning at SMAN 61 Jakarta and its contribution to the development of students' critical thinking skills. This study was conducted due to the need for a learning model that encourages students to understand religious concepts through active, reflective, and meaningful learning experiences. The purpose of this research is to describe the implementation of Deep Learning in PAI learning and its influence on the development of students' critical thinking skills. This study employs a qualitative method with a descriptive research design, using interviews, classroom observations, and documentation as data collection techniques. The findings indicate that the Deep Learning approach supports students in participating more actively in discussions, analyzing religious issues related to real-life situations, and constructing arguments based on their own understanding. Students also demonstrate improvement in evaluating information, considering diverse perspectives, and providing more reflective responses to classroom problems. The study further identifies several challenges, including limited digital facilities, varying levels of student participation, and teachers’ readiness in managing diverse learning strategies and media. These findings suggest that Deep Learning has strong potential to enhance students’ critical thinking skills when applied systematically and designed to foster active participation and meaningful exploration during the learning process.

Training on creating Heyzine-Canva-based e-book learning media through the Subject Teacher Working Group (MGMP) aims to improve teachers' professional competence in facing educational demands and digital technology integration. This training activity is designed using demonstration, hands-on practice, and group discussion methods, so that it can accommodate various levels of technology mastery among teachers. Through this training, teachers are guided to develop interactive e-books, learning videos, and innovative digital quizzes using the Heyzine and Canva platforms. The training results show a significant improvement in teachers' skills in utilizing digital media, confidence in integrating technology into learning, and motivation to continue innovating. Additionally, this training also encourages collaboration among teachers and builds a professional network that supports continuous development. Challenges faced, such as variations in technology skills and device limitations, are addressed through ongoing mentoring and further training. This training contributes to improving the quality of learning, student engagement, and supports the achievement of national education goals in the digital era.