Implementation Of Learning Model Research Articles

Peningkatan literasi numerasi melalui model pembelajaran dan hubungannya dengan kemampuan self-efficacy: Systematic literatur review

This study aims to describe the improvement of numeracy literacy through learning models and its correlation with self-efficacy capabilities.. The research method employed is a Systematic Literature Review (SLR) comprising three stages: planning, conducting, and reporting. Data collection involved identifying relevant articles based on predetermined criteria. The study examined 19 articles retrieved through a Google Scholar database search, facilitated by the Publish Or Perish software. Data synthesis was presented through tabulation and reinforced with a narrative format. The findings indicate that the improvement of numeracy literacy in elementary and secondary schools from 2020 to 2023 is predominantly pursued through the implementation of problem-based learning (PBL) models. Additionally, students' self-efficacy capabilities influence their success in learning. Furthermore, students' numeracy literacy correlates positively with self-efficacy, evidenced by higher self-efficacy correlating with higher numeracy literacy skills.

Implementation of Problem-Based Learning (PBL) Model to Improve Students’ Learning Outcomes in Two-Dimensional Geometric Shapes Material

This study aims to improve the process and mathematics learning outcomes for class VIII students. 7 SMP Negeri 34 Pekanbaru through applying the Problem-Based Learning model. The subjects of this study were students of class VIII. 7 SMP Negeri 34 Pekanbaru, a total of 39 students consisting of 21 male and 18 female students. This is a classroom action research (CAR) consisting of 2 cycles. The data collection instrument consists of an observation sheet and a learning outcome test sheet that has been analyzed. Furthermore, the data analysis technique used is descriptive data analysis in the form of qualitative and quantitative data analysis. The observation sheet at each meeting shows an improvement in the process, and based on learning outcomes, there is an increase in learning, as seen from the number of students who reached the KKTP and the average student learning outcomes in mathematics. So, it can be concluded that applying the Problem-based Learning model can improve the process and mathematics learning outcomes for students in class VIII. 7 SMP Negeri 34 Pekanbaru.

A Review Geospatial Artificial Intelligence (GEO-AI): Implementation Of Machine Learning On Urban Planning

Geospatial Artificial Intelligence (Geo-AI) is an interesting topic in its development and application in our lives. One of them is spatial planning, which contributes to the economic and social development of a region or country. Spatial data is the main thing in this research, which maximizes the effectiveness of land use spatial data on the area as upstream data and develops GIS-based urban planning applications to display the results of analysis and predictions of urban objects automatically. On the other hand, to maximize tourism revenue, the government plans urban areas for both spatial and land use and makes a lot of spatial data based on geographical and environmental conditions. This study will analyze the benefits of Geo-AI in urban planning and the tourism sector. The method used in this study is the Systematic Literature Review (SLR), where the search for the required articles comes from electronic databases obtained using the NVivo software with article sources from Publish or Perish. This study discusses the main steps for the analysis of geospatial data that have been successful in the main areas, namely the development of applications and models, including visualization. By treating issues in geospatial artificial intelligence, the overall aim of the research is to improve the quality of life for Indonesia's growing urban population. The results of the study with the systematic literature review of Geo-AI found a gap in the research implementation of the machine learning model used where five models were compared and relevant to the geospatial dataset displayed in the form of a literature review matrix and visually included in the relevant keywords in the bibliometric analysis. Interdisciplinary results are developing and are urgently needed by both government and private stakeholders in the development of smart cities to prepare spatial planning in urban areas and strategies in optimizing technology in the field of spatial planning in implementing systems based on Geo-AI.

The Implementation of Innovative Technology-Based Project Based Learning Models in Enchancing Student Creativity

Abstract. This research aims to understand the implementation of the innovative technology-based project-based learning model in improving students' creativity and to determine the influence of the innovative technology-based project-based learning model on enhancing student creativity. The research method used in this study is a quantitative approach with a survey research design. The population size is 40 individuals, and a sample of 20 individuals was selected through random sampling. Data collection methods included observation, interviews, documentation, and questionnaires. Assumptions were tested for normality and linearity. Data analysis involved a simple linear regression test. The results of this research indicate that (1) The description of the implementation of the innovative technology-based project-based learning model falls into the "excellent" category for 3 students, or 15%, and the "good" category for 17 students, or 85%, (2) There is a positive influence of the Innovative Technology-Based Project-Based Learning Model on Enhancing Student Creativity.Keywords: Project Based Learning, Innovative Technology, Creativity

Analysis of "Productive and Educative" Performance in the Lesson Studies of the Center of Excellence SMK (Study at State Vocational High School 4 Bandar Lampung)

This research was carried out to determine the implementation of the teaching factory learning model and Project Base Learning in an effort to improve the productive and educational performance of grade XI students in specialization subjects at the State 4 Bandar Lampung vocational school. This research is qualitative research using data analysis techniques, namely Data Resolution, Data Presentation, Conclusion Drawing/Verification. The results of the Operational Research of the Education Unit by using the suitability of the Teaching Factory and PjBL planning models with the integration of the curriculum with each stakeholder and the appropriate assessment, the planning of the Teaching Factory and PjBL is able to improve Educational and Productive Performance. The Teaching Factory and PjBL models have a good contribution in improving the Educational and Productive Performance of Students in the Vocational School of Negeri 4 Bandar Lampung in the Department of Hospitality.

Optimizing Elementary School Education through the Implementation of Karawitan-Based Learning Grounded in Local Wisdom

Purpose of the study: This research aims to identify the optimization of the implementation of learning based on local musical wisdom in arts and culture music material subjects in elementary schools.
 Methodology: This research uses a classroom action research approach as the main method. The research subjects in this context are fifth grade elementary school students who are involved in learning based on Karawitan Local Wisdom. The data collection technique in this research uses a questionnaire to measure responses and observation sheets to measure student learning activity. The data analysis technique uses descriptive statistics and the independent sample t-test.
 Main Findings: The research results show that the implementation of Karawitan Local Wisdom-based learning at the Sendangsari Village Elementary School, through a project-based and open approach, has had a significant positive impact on students' responses and their activeness in the learning process. There is a real increase in students' interest, understanding and appreciation of the learning material, along with more intensive student participation.
 Novelty/Originality of this study: The novelty of the results of this research lies in the implementation of a Karawitan Local Wisdom-based learning model at the elementary school level, which concretely depicts significant changes in students' responses and their activeness during the learning process.

Examining Brain Based Learning Models Assisted Open-Ended Approach To Mathematics Understanding Concept

The implementation of this research is due to indications of learning problems related to students' difficulties in understanding mathematics in division material in third grade elementary school which results in students being weak in understanding mathematical concepts. This needs to be improved through the implementation of a brain-based learning model with an open-ended approach so that it affects students' understanding of mathematical concepts. Quasi-experiment with pretest posttest control group design was used as the basis for this research method. The study population consisted of 96 grade 3 students from 5 schools in cluster 5, Klaten. Simple randomization was used as a sampling technique with a sample of 48 students. The research instrument used was a test of 10 questions with essay type. Based on the results of the hypothesis test obtained at 0.018, the brain-based learning model assisted by an open-ended approach has an effect on students' understanding of mathematical concepts with an average increase of 34.96 seen from the pretest and posttest. This research contributes to influencing students' mathematical concept understanding ability in a more positive direction through collaboration between the brain-based learning model with an open-ended approach.

Increasing Social Care Through Civic Education in Higher Education

This study aims to build social care through an engagement-based Civic Education curriculum at Universitas Negeri Yogyakarta/UNY whose students have diverse backgrounds. This study was developed based on the qualitative approach through 1) a focus group discussion to examine the engagement learning model in the Civic Education curriculum, 2) a workshop on the development of engagement learning models, 3) expert validation using the engagement learning model instrument, 4) implementation of engagement learning model, and 5) reflections on the engagement learning model implementation. The results of this study show that the Engagement Learning Model can improve social care shown from mutual respect for diversity, social cohesion, sympathy for others, and volunteerism. The researcher used the social value theory to analyze students’ social care. This engagement learning model can develop a social collaboration that promotes the unique characteristics of each student. Students are trained to be critical and socially sensitive through an engagement project consisting of social activities in the community in Civic Education learning. Increasing students' care from Civic Education may positively influence students' knowledge, attitudes, and social relations in their groups and outside their groups, respect and acceptance of diversity, social cohesion that forms cooperation, sympathy for others that form social solidarity, as well as a sense of volunteerism that makes students provide solutions to social problems.

Machine Learning Based Crop Yield Prediction Model in Rajasthan Region of India

The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mean Squared Error, Mean Absolute Error and R-squared and identified that after the inclusion of gradient boosting regression, the accuracy increased to 92.77%. The MAE value decreased from 26.20 Mg/ha to 21.58 Mg/ha. The results indicate that machine learning models can improve the prediction of crop yield.

Implementation of the Inquiry-Oriented RADEC Learning Model

The experiment activities carried out are not complete experiment activities. One of the learning models that includes investigative activities is the RADEC learning model. This research aims to implement inquiry-oriented RADEC learning. The method used in this research mixes methods by design-embedded experimental design. The subjects in this study were 45 elementary school students in class V, one of the elementary schools in Bandung Regency. Data collection techniques were collected using test and non-test instruments in the form of observation sheets, test questions, and questionnaires. Each stage of the RADEC learning model was good, with some stages increasing at each meeting and some optimally implemented. In investigative activities, students still need guidance in designing and making investigative reports and are required more than once to develop their skills in compiling, carrying out, and reporting investigations. Besides that, RADEC learning can increase students' mastery of concepts and encourage student collaboration skills.

Characteristics of High School Physics Problem-Solving Skills and Integrating the PBL Model Assisted by E-Book

This research discusses the implementation of the Problem-Based Learning model assisted by E-Book to improve students' problem-solving skills on renewable energy materials. The purpose of this research is to identify the characteristics of physics problem-solving through the knowledge profile of students at the high school level as a consideration in the application of the PBL model and the use of E-Book assisted learning media to improve problem-solving skills. The research method used is a preliminary study with qualitative descriptive analysis. The instruments used include the problem-solving skills test, interview questionnaire, and student response questionnaire. The data analysis technique in this study used a problem-solving skills test questionnaire and a survey to get responses from students. The findings showed that students' problem-solving skills were generally in the low category. Of the total learners, 87 students were in the low category, 2 students in the medium category, and 1 student in the high category. Although students have been able to understand the problem, they still experience problems in providing answers and checking back due to lack of habit in working on problem-solving-based problems. Therefore, it is necessary to practice and use learning models, as well as E-Book technology, which can help in the process of teaching and learning activities and increase students' learning motivation. Thus, it is expected that students' problem-solving skills can be improved through the right learning approach and the use of relevant technology.

Deep-Learning-Based Segmentation of Keyhole in In-Situ X-ray Imaging of Laser Powder Bed Fusion.

In laser powder bed fusion processes, keyholes are the gaseous cavities formed where laser interacts with metal, and their morphologies play an important role in defect formation and the final product quality. The in-situ X-ray imaging technique can monitor the keyhole dynamics from the side and capture keyhole shapes in the X-ray image stream. Keyhole shapes in X-ray images are then often labeled by humans for analysis, which increasingly involves attempting to correlate keyhole shapes with defects using machine learning. However, such labeling is tedious, time-consuming, error-prone, and cannot be scaled to large data sets. To use keyhole shapes more readily as the input to machine learning methods, an automatic tool to identify keyhole regions is desirable. In this paper, a deep-learning-based computer vision tool that can automatically segment keyhole shapes out of X-ray images is presented. The pipeline contains a filtering method and an implementation of the BASNet deep learning model to semantically segment the keyhole morphologies out of X-ray images. The presented tool shows promising average accuracy of 91.24% for keyhole area, and 92.81% for boundary shape, for a range of test dataset conditions in Al6061 (and one AliSi10Mg) alloys, with 300 training images/labels and 100 testing images for each trial. Prospective users may apply the presently trained tool or a retrained version following the approach used here to automatically label keyhole shapes in large image sets.

Implementation of Inquiry Learning Model in Collaboration with PBL to Improve Student Understanding in Number Theory Course

The purpose of this study was to describe the presence or absence of the influence of the infusion learning model collaboration with Problem-Based Learning (PBL) to develop students' understanding of proof and mathematical argumentation in number theory courses. This research is an experimental study with a randomized control group pretest-posttest design, two groups namely the experimental group and the control group. The experimental group is the group that uses the infusion learning model in collaboration with PBL, while the control group is the group that uses conventional learning. The subjects of this study consisted of 40 students at a university in Jombang, Indonesia. Data collection techniques through observation sheets, proof understanding tests and observation sheets of students' mathematical argumentation abilities. The results of the research show that the significant difference between the average proof of understanding of students in the experimental group and the control group. The difference between the average proof of understanding in the experimental group and the average proof of understanding of students in the control group was 21.75. Furthermore, the significant difference between the average argumentation ability of students in the experimental group and the control group. The difference between the average argumentation ability of students in the experimental group and the average argumentation ability of students in the control group is 5.25. Therefore, the implementasion of infusion learning in collaboration with PBL is more effective than conventional learning models for developing students' ability to understand mathematical proof and argumentation. This learning model promotes the development of critical thinking skills, problem-solving, conceptual and different understanding needed to construct a formal proof, and strong and valid arguments.

Implementasi Model Pembelajaran Berbasis Proyek untuk Meningkatkan Hasil Menulis Prosa Fiksi Mahasiswa Program Studi Sastra Indonesia Universitas Jambi

The aim of this research is to enhance the activity and skills of pre-writers of fiction prose using a project-based learning model in the Indonesian Literature program at the Faculty of Education and Teacher Training, Universitas Jambi. The research method employed is Classroom Action Research (CAR) conducted in two cycles. Each cycle involves planning, implementation, observation, and reflection stages. Data are analyzed according to the assessment rubric. In Cycle I, there was an improvement in activity levels, with 87% of students achieving a good category and 13% achieving a very good category. The improvement in pre-writing scores was 60%, reaching a sufficient category for 40% and a good category for 40%. However, the analysis indicated that the target of exceeding 50% of pre-writing scores in the good category was not achieved in Cycle I, prompting the continuation to Cycle II. In Cycle II, both activity and pre-writing scores experienced significant improvement. Activity scores showed 33.3% of students in the good category and 86.7% in the very good category. Pre-writing scores increased to 33.3% in the good category and 66.7% in the very good category. Based on the research findings, it can be concluded that the implementation of the Project-Based Learning model in the Fiction Prose Writing course effectively enhances the activity and skills of pre-writers of fiction prose and is deemed suitable for application

Deep learning-based air pollution analysis on carbon monoxide in Taiwan

Global air pollution poses a threat to humanity. Specifically, CO directly affects cardiovascular and other organ tissues and leads to numerous chronic diseases and major public health problems. The effective implementation of a deep learning model for predicting variations in CO levels would enable the early formulation of policies for controlling air pollution. In this study, a seasonal gated recurrent unit (SGRU) model, which is a deep learning time-series prediction model, was developed to predict the levels of CO in Taiwan. Atmospheric CO measurements from 2005 to 2021 were collected from the Environmental Protection Administration of Taiwan and preprocessed using the Kalman filter to achieve accurate forecasting. The performance of the proposed SGRU model was compared with that of the autoregressive integrated moving average (ARIMA), seasonal ARIMA, exponential smoothing (ETS), Holt–Winters ETS, support vector regression, and seasonal long short-term memory models in terms of mean absolute percentage error (MAPE) and root mean square error. The SGRU model achieved the lowest MAPE value of 0.94, which demonstrated its superior performance. The construction of an accurate air pollution prediction model can assist government entities in formulating health and social care strategies and in planning future air pollution control measures.

Enhancing bank marketing strategies with ensemble learning: Empirical analysis.

In order to enhance market share and competitiveness, large banks are increasingly focusing on promoting marketing strategies. However, the traditional bank marketing strategy often leads to the homogenization of customer demand, making it challenging to distinguish among various products. To address this issue, this paper presents a customer demand learning model based on financial datasets and optimizes the distribution model of bank big data channels through induction to rectify the imbalance in bank customer transaction data. By comparing the prediction models of random forest model and support vector machine (SVM), this paper analyzes the ability of the prediction model based on ensemble learning to significantly enhance the market segmentation of e-commerce banks. The empirical results reveal that the accuracy of random forest model reaches 92%, while the accuracy of SVM model reaches 87%. This indicates that the ensemble learning model has higher accuracy and forecasting ability than the single model. It enables the bank marketing system to implement targeted marketing, effectively maintain the relationship between customers and banks, and significantly improve the success probability of product marketing. Meanwhile, the marketing model based on ensemble learning has achieved a sales growth rate of 20% and improved customer satisfaction by 30%. This demonstrates that the implementation of the ensemble learning model has also significantly elevated the overall marketing level of bank e-commerce services. Therefore, this paper offers valuable academic guidance for bank marketing decision-making and holds important academic and practical significance in predicting bank customer demand and optimizing product marketing strategy.

SINERGI MANAJEMEN DAN PENDIDIKAN: Model Pembelajaran yang Menunjang Potensi Siswa

Effective education in the digital age requires synergy between school management and education to break the 'one-size-fits-all' paradigm. This study aims to analyze the implementation of potential-based learning models at SMPIT Al Qalam Kendari. In the context of Islamic Religious Education, this study particularly highlights the need for a learning approach that not only prioritizes religious knowledge, but also fosters students' emotional, spiritual, and social intelligence. By assessing educational practices that are often monotonous and unable to accommodate the diversity of students' potential, this study examines how innovative and potential-based learning models can overcome the gap between potential and learning outcomes achieved. Effective school management synergies are needed to support these didactic innovations, empower teachers with relevant competencies, and ensure that student-centred learning achieves holistic educational goals. This model is expected to make a significant contribution to developing students' potential as a whole and sustainably.

Philosophy-Infused Culture-Based Learning Models In Mathematics Education

The aim of this research is to explore and leverage the synergistic relationship between the philosophy of mathematics education and culture-based learning models. It seeks to investigate how philosophical perspectives can inform and enrich the development and implementation of culture-based learning models in mathematics education. Additionally, it aims to examine how integrating philosophical underpinnings can deepen students' comprehension of mathematical concepts within diverse cultural frameworks. Reading the entire paper is essential for anyone interested in advancing the field of mathematics education with a focus on cultural integration. This research explores the intricate relationship between the philosophy of mathematics education and culture-based learning models, offering valuable insights into how philosophical perspectives can enrich teaching practices within diverse cultural contexts. Moreover, it outlines crucial future research agendas, emphasizing the need for cross-cultural studies to identify universal and context-specific approaches, as well as the importance of equipping mathematics educators with the necessary skills through professional development programs. Overall, the paper provides a comprehensive roadmap for educators, researchers, and policymakers to promote inclusive and culturally relevant mathematics education, making it a must-read for those dedicated to enhancing educational practices in a diverse world. In conclusion, the integration of cultural elements in mathematics education is a dynamic field with promising future agendas. Cross-cultural research and teacher professional development programs are essential components for advancing the inclusivity and effectiveness of mathematics education in diverse contexts. By addressing these agendas, we can foster a more equitable and culturally responsive approach to teaching and learning mathematics.

Implementation of Concept Mapping Learning Model to Improve History Learning Achievement

This study aims to determine the application and determine the improvement of students' history learning achievement and the obstacles faced in the application of the Concept Mapping model. This research used CAR (Classroom Action Research) with qualitative and quantitative approaches consisting of 3 cycles. The results showed that the application of the Concept Mapping learning model combined with group discussions, quiz games, and the provision of material handouts can improve learning achievement In cycle I student achievement increased by 0.96, cycle II increased by 1.66, and in cycle III increased by 3.30. The obstacles faced in the application of the Concept Mapping learning model are at the beginning of the application of the Concept Mapping learning model there are still some students having difficulty determining secondary ideas. The condition of the lesson at the last hour requires the teacher to create an interesting atmosphere. There must be clear communication between teachers and students because the learning model requires steps to be taken to create Concept Mapping.

Developing a Clinical Learning Model to Improve Nursing Students' Learning Outcomes

The utilization rate of the clinical learning model in Indonesia comprises the following:conferences(54.5%),bedsideteaching(54.5%),clinic-tutorials(45.4%),journal percentage (45.4%), and case presentations (45.5%). As a result, this study aimed to improve nursing students' clinical learning outcomes in their ability to effectively address and resolve problems, make informed decisions pertaining to patient cases, and interact with patients and their families. Methods:This study employed an explanatory methodology with a quantitative approach as it elucidated the cause-and-effect relationship between variables. The study sample consisted of 45 nursing students who met the research criteria and conducted clinical practice at the Padang Pariaman Regional Hospital. The study employed total sampling as its sampling technique. Results:After the clinical learning model was implemented, the mean student clinical competency score increased from 24.51 to 26.33, according to the research findings. Similarly, the average student knowledge score also improved from 74.69 to 77.42 following the implementation of the clinical learning model. The study found a significant difference between the level of clinical proficiency students attained before and after the implementation of the clinical learning model (p= 0.001). Additionally, there was a substantial disparity in students' knowledge scores before and after the application of the clinical learning model (p= 0.000). Conclusion:The clinical learning models can improve student learning outcomes and the quality of education.