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Learning biology on the human motion system material often presents challenges due to the complex and abstract nature of the material. This study aims to improve student learning outcomes by applying the Discovery Learning learning model assisted by video media in class X SCIENCE SMA Negeri 2 Tondano. This research is a Class Action Research which was carried out in two cycles using a collaborative reflective approach. Each cycle consists of planning, action, observation, and reflection stages, with data collection through observation, evaluation tests, interviews, and field notes. The results in the first cycle showed that the average student score only reached 53.4 with a classical completeness rate of 32%. In cycle II, after improvements based on reflection in cycle I, learning outcomes increased significantly, with an average of 85.3 and a completeness rate of 100%. These findings show that integrating video media in discovery-based learning effectively improves students' understanding of hard-to-visualize biological concepts. Audio-visual media help students relate visual information to authentic experiences, while Discovery Learning encourages active and exploratory engagement of students in the learning process. This research contributes to the science education literature by showing that technology-based and participatory learning strategies can answer the challenges of biology learning in secondary schools. Implicitly, teachers are encouraged to adopt a similar approach to create active, engaging, and meaningful learning.

This study aims to develop learning media based on wall magazine (mading) and dice for teaching multiplication to second-grade students at SD Negeri 212 Palembang. The research employs the Research and Development (R&D) method using the ADDIE model, which includes Analysis, Design, Development, Implementation, and Evaluation stages. After the media was developed, validation was conducted by content experts and media experts to assess its feasibility, as well as trials by practitioners and students to evaluate the practicality and effectiveness of the media. The validation results showed a feasibility score of 87% from content experts and 94% from media experts. Practitioners gave a practicality score of 92%, indicating that the media is very practical for use in teaching. Student trials were carried out in three stages: one-to-one with a practicality score of 98%, small group with 99%, and a field test involving 26 students showed an effectiveness level of 96%. This wall magazine and dice media is effective and practical to be used as learning media for teaching multiplication to second-grade elementary school students.

As the primary raw material for sugar and ethanol production, sugarcane is a highly significant plantation commodity. However, its relatively long growing period of approximately one year makes it more susceptible to diseases. Machine learning technology has been applied in the identification of sugarcane leaves, including through pre-processing methods and the development of disease classification models using Convolutional Neural Network (CNN) and Support Vector Machine (SVM) approaches. However, these methods exhibit limitations in terms of accuracy. Therefore, improving identification accuracy using VGG-16 is essential. The objective of this study is to enhance the accuracy of sugarcane leaf disease identification by utilizing VGG-16. The dataset consists of  2,521 sugarcane leaf images categorized into five classes. The results of this study indicate an accuracy improvement from 97.78% to 99.14%, reflecting an increase of 1.36%

This study aims to develop ROPUCA (Roda Putar dan Papan Baca) learning media in teaching vowels and consonants. This media is designed to create an interactive and enjoyable learning experience in building early reading skills. This study uses the Research and Development (R&D) method with the ADDIE development model, which consists of five stages: analysis, design, development, implementation, and evaluation. The validation results show a percentage of 100% from material experts, 81% from media experts, and 100% from field practitioners. Individual trials obtained results of 92%, small group trials 100%, and field trials reached 91%. The data obtained show that ROPUCA media contributes to helping students recognize consonants and vowels and understand the basics of reading more effectively. This media is used in learning for grade I elementary school students.

This study is a literature review aimed at examining the effectiveness of the guided inquiry model based on STEM in enhancing students’ critical thinking skills. The guided inquiry model provides a structured framework for students to explore problems under teacher guidance, while the STEM (Science, Technology, Engineering, and Mathematics) approach promotes interdisciplinary, contextual, and practical learning. Through an analysis of various relevant articles and scholarly journals, the findings indicate that the implementation of the guided inquiry model integrated with STEM consistently improves students' critical thinking abilities, particularly in areas such as analysis, evaluation, and reasoning. The study also highlights the crucial role of teachers as active facilitators in the learning process and the need for adequate resources to effectively apply this approach. The results of this review are expected to serve as a reference for educators and researchers in developing innovative and 21st-century-oriented learning strategies.

This study aims to obtain the validity of E-LAPD using the Problem Based Learning (PBL) model that can be used to improve science literacy on chemical equilibrium material. The design used is a 4-D model designed to improve students' science literacy skills. The valid E-LAPD was evaluated through a validation sheet filled in by the validator using a Likert scale. Validity consists of construct validity which includes presentation components, graphic components, suitability of models and indicators to be improved and content validation which includes the suitability of learning objectives with learning outcomes and the suitability of problems or phenomena with the material being taught.  The validity of E-LAPD is declared valid if the score from the validator is at least 4 and does not have one score < 3 from the validator. The results showed that the E-LAPD developed had high validity indicating that the mode score of the validator ≥ 4. The developed E-LAPD was declared valid for use with a construct and content validation assessment which was described as valid with a score of 4, thus E-LAPD using the PBL model was declared valid for use to improve science literacy in chemical equilibrium material.

This study aims to determine the effect of the Problem Based Learning (PBL) model on students’ problem-solving abilities in the reaction rate material at SMA Negeri 07 Gorontalo. The research employed a quasi-experimental method with a pretest-posttest control group design. The subjects consisted of two classes: class XI1 as the experimental group (using the PBL model) and class XI2 as the control group (using conventional learning). The instrument used was an essay test based on problem-solving indicators. The results showed a significant improvement in problem-solving ability in the experimental class compared to the control class. The average posttest score of the experimental class was 74 (categorized as good), while the control class scored 52 (categorized as fair). The t-test results indicated a significant difference between the two groups (p < 0.05), suggesting that the PBL model is more effective in enhancing students' problem-solving abilities than conventional learning methods.  

By implementing The cooperative learning method known as think, pair, share (TPS) paradigm in the eleventh grade at MAN Karawang, this study seeks to enhance students' comprehension of halal and healthy eating. The research has been conducted in two cycles using Classroom Action Research (CAR).methodology employed. There are twenty multiple-choice questions on the test that has been used. The findings of the study indicate that pupils' comprehension has improved. Just 15% of pupils finished the pre-cycle activities, with an average score of 66. This rose to 59% with a 73 average score in the initial cycle, and all students finished the activities with a mean score of 89 in the second. The pupils are encouraged to think critically, participate actively, and have discussions when Think Pair Share (TPS), a cooperative model, is applied. As a result, this strategy has been successful in improving students' comprehension through interaction

This study aims to evaluate the effectiveness of the Poetry Album as a learning medium for teaching poetry writing to eighth-grade students in Cilacap Regency, Indonesia. Utilizing a qualitative exploratory approach, the research was conducted in three public junior high schools, involving 192 students and three Indonesian language teachers. Data were collected through participatory observations, semi-structured interviews, and documentation of students' works, and were analyzed using Miles and Huberman's interactive analysis model. The results indicate that 96-98% of students enjoyed using this media, and the average scores of students' poetry ranged from 82 to 88. These findings suggest that the Poetry Album can enhance students' motivation, emotional engagement, and poetry writing skills. Furthermore, this media has proven effective in enriching the learning process aesthetically and creatively, in line with Rosenblatt's (1995) aesthetic response theory and Vygotsky's (1978) constructivist theory. Thus, the Poetry Album is relevant for aesthetic-based literary learning in secondary schools.

This study aims to improve the understanding of class VIII MTs students on the material of Social Media Etiquette through the Giving Questions and Getting Answers (GQGA) method. The research was conducted due to the low understanding of students in Islamic Religious Education subjects, especially about social media etiquette. The method used was Classroom Action Research (PTK) model Kemmis & McTaggart which consists of two cycles: planning, implementation, observation, and reflection. Data were collected through observation and multiple choice tests. As a result, students' learning completeness increased from 50% before the action, to 70% in cycle I, and 95% in cycle II. This shows that the GQGA method is effective for improving students' comprehension.

Thyroid cancer is the most common endocrine malignancy, with a steadily increasing incidence rate. Although the overall survival rate is relatively high, the risk of recurrence after definitive treatment such as Radioactive Iodine (RAI) therapy remains a significant clinical challenge. Predicting recurrence risk is crucial for optimizing monitoring strategies and interventions. With advances in technology, machine learning (ML) approaches are increasingly utilized to support medical predictions, including the recurrence of thyroid cancer. This study aims to evaluate the performance of four classification algorithms—Logistic Regression, XGBClassifier, Random Forest Classifier, and Voting Classifier—in predicting thyroid cancer recurrence using the Thyroid Cancer Recurrence After RAI Therapy dataset, which consists of 383 patient records and 13 key clinical attributes. The evaluation was conducted using accuracy, precision, recall, F1-score, and area under the curve (AUC) metrics. The results show that the XGBClassifier is the best-performing model with an accuracy of 97.4% and an AUC of 0.95, demonstrating superior performance in handling the minority class. This research is expected to contribute to the development of more effective machine learning–based clinical decision support systems for predicting thyroid cancer recurrence after therapy.

Critical thinking skills are an important competency in learning biology, especially in biodiversity materials that require analysis, reasoning, and decision-making. This study aims to determine the influence of the Guided Discovery Learning learning model  on the critical thinking ability of grade X students at SMA Negeri 2 Tondano. The method used was a quasi-experimental study with a pretest-posttest control group design. The sample consisted of two classes, namely the control class that was taught using the conventional model and the experimental class that received treatment with the Guided Discovery Learning model. Data were collected through pretest and posttest written tests, and analyzed using normality, homogeneity, and t-test. The results showed that there was a significant difference between the learning outcomes of students in the experimental class and the control class. The average posttest score of the experimental class was 81 higher than the control class of 63.5. In addition, the Tcal value of 4.65 is greater than the Ttable of 2.02 at a significance level of 0.05, which shows that  the Guided Discovery Learning model  has a positive influence on improving students' critical thinking skills. This result is also strengthened by a decrease in standard deviation which shows an equal distribution of understanding between students. This research contributes to the development of active learning strategies in biology education and suggests the application of this model to improve higher-level thinking skills. This model is also relevant applied to other topics in order to strengthen discovery-based learning and collaboration.

Coronary heart disease (CHD) remains a leading cause of mortality worldwide. Early detection is essential to reduce complications and improve patient outcomes. This study aims to develop a classification model using machine learning algorithms to predict CHD risk based on clinical symptoms. The dataset used is the Cleveland Heart Disease dataset from the UCI Machine Learning Repository, consisting of 303 patient records with 14 clinical features. The preprocessing stage involved handling missing values, normalizing features, and transforming categorical variables. Four classification algorithms were applied: K-Nearest Neighbors (K-NN), Decision Tree, Random Forest, and Support Vector Machine (SVM). Each model was trained using stratified 10-fold cross-validation to ensure generalizability. Evaluation using accuracy, precision, recall, F1-score, and ROC-AUC metrics showed that the Random Forest algorithm achieved the highest performance with 87.2% accuracy. Feature importance analysis indicated that chest pain type, resting blood pressure, cholesterol, and ST depression were the most influential indicators. These results demonstrate that machine learning, particularly Random Forest, can effectively support early diagnosis of CHD in clinical settings and has the potential to be integrated into clinical decision support systems (CDSS).

This community engagement program aims to enhance the knowledge and understanding of early childhood regarding prayer practices through a series of interactive and practice-based training sessions. Targeting children aged 5–7 years in Jaddih Selatan Village, Bangkalan, the program utilized a participatory approach involving local religious leaders, parents, and university students as facilitators. The training was conducted at the village mosque, employing visual aids, demonstrations, and repeated simulations to foster both cognitive and psychomotor aspects of prayer. The results indicate a significant improvement in children's ability to perform prayer movements and recitations correctly, as well as increased enthusiasm and participation in religious activities. Moreover, the program strengthened the mosque's role as a child-friendly religious learning center and encouraged the emergence of leadership potential among the participants. This initiative is expected to serve as a sustainable model for character education and spiritual development in rural communities, and can be replicated in similar settings to empower early childhood religious education.

The purpose of this study was to determine the improvement of learning outcomes of class 12 IPS 1 students in PPKN subjects at SMA Negeri 2 Rantau Utara through the problem based learning model. The method used in this study is classroom action research (CAR), the subjects of the study were 35 class 12 IPS 1 students. The focus of this study is the learning outcomes of class 12 IPS 1 students in PPKn subjects with indicators of student learning success that reach KKM (minimum completion criteria) with a value of 82. The results of the study indicate that the application of the problem based learning model is effective in improving student learning outcomes in PPKn subjects. This increase can be seen from the pre-action stage, only 10 people with a percentage of 28.6% have met the minimum completion criteria (KKM), then in cycle I there were 18 people with a percentage of 51.4%, while in cycle II there were 29 people with a percentage of 82.82% of students have reached KKM. From these results, it can be concluded that the problem-based learning model is able to improve student learning outcomes, not only cognitively but also improve critical thinking skills, cooperation, and increase student self-confidence.

The rapid advancement of information technology has had a significant impact in various fields, particularly in pattern recognition and image processing. One of the ongoing challenges is accurately recognizing handwritten digits, which plays a crucial role in document digitization, automated form reading, and other intelligent systems. This study aims to implement and evaluate the K-Nearest Neighbors (KNN) algorithm, a simple yet effective classification technique, in recognizing handwritten digit images. The data used comes from the public dataset load_digits from Scikit-learn, which contains 1,797 grayscale images of handwritten digits sized 8x8 pixels. Each image is represented as a 64-dimensional feature vector. The dataset is split into training and testing data with an 80:20 ratio, and the model is trained using KNN with k=3. The experimental results show a classification accuracy of 96.94%, with minimal prediction errors that typically occur in digits with similar visual shapes, such as 5 and 9. This study demonstrates that KNN, despite its simplicity, can provide high accuracy in handwritten digit recognition when supported by proper preprocessing and parameter selection. The implications of this research highlight the potential for developing intelligent applications in education, data entry automation, and identity verification.

Hasil penelitian menunjukkan bahwa model Decision Support System (DSS) berbasis kombinasi Analytical Hierarchy Process (AHP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) mampu memberikan hasil evaluasi supplier yang objektif dan konsisten. Dari hasil perhitungan, kriteria Harga memperoleh bobot tertinggi sebesar 42,31%, diikuti oleh Waktu Pengiriman dan Layanan masing-masing 22,72%, serta Kualitas sebesar 12,25%. Peringkat akhir menunjukkan bahwa Supplier A memiliki nilai kedekatan tertinggi terhadap solusi ideal, menandakan keseimbangan terbaik antara efisiensi biaya dan kinerja non-finansial. Implementasi dalam bentuk dashboard interaktif terbukti mempermudah manajemen dalam memahami hasil analisis serta mempercepat proses pengambilan keputusan. Penelitian ini membuktikan bahwa integrasi metode AHP-TOPSIS dapat digunakan secara efektif sebagai alat bantu dalam manajemen pengadaan berbasis data. Namun, penelitian ini masih memiliki keterbatasan pada jumlah responden dan konteks industri yang relatif sempit. Penelitian mendatang disarankan untuk memperluas cakupan sektor industri, menambah jumlah pakar, serta mengintegrasikan model ini dengan teknologi machine learning atau real-time analytics agar sistem pendukung keputusan dapat beradaptasi secara dinamis terhadap perubahan kondisi pasar dan performa supplier.

This research aims to design an Islamic Boarding School (Ponpes) with a sustainable architecture approach that is able to answer environmental, social, and economic challenges holistically. The method used is a qualitative-descriptive approach through architectural design research, which combines empirical data from the field with theoretical studies from relevant literature. The design location is on Jl. Gunungpati Raya, Nongkosawit Village, Gunungpati District, Semarang City, with an area of ±19,909.77 m². Data collection techniques include literature study, site observation, and comparative design study. Data were analyzed descriptively and spatially to formulate user needs and site potential. The design results show that the sustainable architecture approach can be implemented through functional layout, passive energy utilization, vegetation preservation, rainwater management, and waste recycling system. The design also accommodates social and economic aspects through the provision of organic farming areas and small farms as part of practice-based education. Contemporary Islamic architectural aesthetics are applied contextually, creating a healthy, inclusive, and adaptive learning environment. This research produces a sustainable pesantren design concept that can be a reference model in the development of environmentally friendly and self-reliance-based Islamic educational institutions..

The increasing use of mobile devices has increased the risk of data theft, posing significant security challenges for individuals and organizations. This study proposes an early detection system for data theft on mobile devices using machine learning algorithms. The system is designed to identify suspicious patterns in application usage, network access, and CPU/memory activity, providing early warnings to prevent potential data loss. By employing algorithms such as Random Forest, Support Vector Machine (SVM), and Convolutional Neural Network (CNN), the developed models demonstrated significant performance: CNN achieved the highest accuracy of 95.1%, with a precision of 94.2%, recall of 93.5% , F1-score of 93.8%, and AUC-ROC of 0.96. Random Forest and SVM also showed competitive performance with accuracy rates of 94.7% and 92.5%, respectively. These findings highlight the high potential of machine learning algorithms for real-time detection of data theft threats, providing adaptive protection against evolving cyberattack methods. This approach offers a promising solution to strengthen mobile device security frameworks and safeguard user data against increasingly sophisticated cyber threats.

This study aims to develop an interactive learning media based on android using a valid and practical smart app creator to improve students' understanding of the SPBI course in the Industrial Automation Engineering Department of SMK Negeri 1 Pariaman. This study uses the Research and Development (R&D) method with the ADDIE model as a guideline in the development process. The results of this study provide evidence that the interactive learning media created falls into the "Valid" category. This is proven based on validation carried out by material experts with a validity value of 87% (0.870) and validation carried out by media experts with a validity value of 92.11% (0.921). Furthermore, a Media Practicality Test was carried out by class XI students of SMK Negeri 1 Pariaman with a practicality value of 91.60% (0.961) falling into the Very Practical category.