Mathematical Learning Model Research Articles

Development of Student Worksheets Based on Realistic Mathematics Learning Models to Improve Critical Thinking Skills for Class XI Vocational High School Students

This type of development research aims to determine the level of validity, effectiveness, and practicality of learning using Student Worksheets based on the Realistic Mathematics Learning model. This development uses the ADDIE development model that uses five stages: analysis, design, development, implementation, and Evaluation. The sample used is class XI SMK Private Mulia Medan. The results showed that the Student Worksheet, which was developed using the Realistic Mathematics Learning model, had a validity level of 4.6 with an outstanding category, the effectiveness level of the results of classical learning completeness in the first trial was 15% of the students completed while in the second trial. by 88% of students who completed. This shows an increase of 23% from the average critical thinking ability of students. Furthermore, the student response was very good with a percentage of 80%, and the practicality of the Student Worksheet obtained an average of 4.29 with a convenient category.

The expansion of sociocultural theory-oriented mathematical learning model

The research aim was to obtain a Sociocultural Theory-oriented Mathematics Learning Model with Tri Hita Karana insight that is valid, practical, and effective in developing the good character of students in learning mathematics. This research was a research and development with reference to the development of Plomp. The data collection techniques used tests and questionnaires. The results showed that: (1) the Sociocultural Theory-oriented Mathematics Learning Model with Tri Hita Karana insight is valid, practical, and effective to use to develop the good character of students; (2) there was an increase in the good character of students from the category ‘sometimes shows good behavior according to the Tri Hita Karana aspect and often behaves not in accordance with the Tri Hita Karana aspect’ to the category ‘often and consistently shows good behavior according to the Tri Hita Karana aspect’; and (3) positive student responses to learning.
 
 Keywords: Mathematical learning, sociocultural theory, tri hita karana, pawongan, tri pramana

Problem-based learning in mathematics learning to improve reflective thinking skills and self-regulated learning

This research was aimed to determine the effectiveness of the Problem-Based Learning (PBL) model in mathematics learning on students' reflective thinking skills and self-regulated learning. The researchers employed the quantitative-qualitative method. The quantitative data was obtained through pretest and posttest, and qualitative data were obtained through interviews with three students selected using a purposive random sampling technique. The research subjects were selected using the accidental sampling technique because it was still in the new normal era of the COVID-19 pandemic. The subjects consisted of 33 eighth-grade students. The data was collected using test instruments and questionnaires. Furthermore, the data was tested using the independent sample t-test. This research found three results. First, there was a significant increase in reflective and self-regulated thinking skills through the application of the PBL model. Second, based on the t-test, there was a reflective thinking skills difference between pretest and posttest, with a higher score was found in the posttest. Third, there was no self-regulated learning difference between the pretest and posttest.

Effectiveness of the Blended Learning Model to Improve Students’ Achievement of Mathematical Concepts

This study aims to discover the effectiveness of the blended learning model in mathematics learning to improve the achievement of mathematical concepts. This study employed a quasi-experimental design with a non-equivalent control group. The experimental class was taught through blended learning, while the control class was taught through the conventional learning model. The population of this study was the students at State Senior High School 1 Sewon Yogyakarta, Indonesia. The research sample involved 60 tenth-grade students in the 2019/2020 academic year, 30 students in each of the experimental and control groups. The sampling technique used cluster sampling and the data were collected using a test instrument. The validity of the test was measured using the obtained Aiken index (0.80), and the reliability was based on the Cronbach's alpha coefficient (0.86). The data were analyzed using t-tests and descriptive statistics. The results of this study showed that the blended learning model is significantly more effective than the conventional learning model in enhancing students’ achievement of mathematical concepts. This means that the application of blended learning in mathematics learning can significantly improve students' achievement of mathematical concepts.

Problem-based learning model on mathematical analytical thinking ability and science process skills

This research serves as a reference for teachers to implement problem-based learning models on analytical thinking skills and science process skills in mathematics subjects. This research examines the differences and relationships between students' analytical thinking skills and science process skills with problem-based learning models in mathematics. The sample of this research consisted of 180 students. This research is a quantitative study with a questionnaire as the instrument. The obtained data were analyzed using the t-test and correlation test. The results showed a significant difference between analytical thinking skills and students' science process skills, especially on the indicators of Observation and Classification at SMPN 35 Batanghari and SMPN 8 Batanghari students who applied the problem-based learning model in mathematics. Furthermore, it was found that there was a relationship between analytical thinking skills and science process skills because students with analytical thinking skills possessed better science process skills in problem-based learning models in mathematics subjects.

Meningkatkan Pemahaman Siswa Kelas V SDN Mekarjaya pada Materi Perbandingan dan Skala dengan Model Pembelajaran Jigsaw

Learning mathematics is usually very feared by students because students think that mathematics is difficult. Therefore, teachers must be creative and innovative in teaching mathematics so that students enjoy the mathematics subject. If students already enjoy mathematics subjects, students will automatically be enthusiastic in the learning process which has an impact on satisfying student learning outcomes. Some of these conditions were also found at the State Elementary School of Mekarjaya, especially in terms of scale. To overcome this, teachers must use a learning model that is fun and follows the characteristics of the material to be taught, one of which is the jigsaw learning model in learning mathematics on comparison and scale material. This research is in the form of classroom action research which aims to improve learning conditions. The research subjects are fifth-grade students in the even semester of 2020/2021. Based on the results of the study, there was an increase in the learning outcomes of fifth-grade students at State Elementary School of Mekarjaya, Takokak District, Cianjur Regency from pre-cycle, cycle I, and cycle II. In the pre-cycle, only 5 people completed 20 students, or 25% who reached the standard minimum score. In cycle 1 there was an increase of 13 students who completed from 20 students or 65% who reached the standard minimum score and in cycle 2 it increased again to 20 students from 20 students who completed or 100% who reached the standard minimum score. This shows that the jigsaw model is effective in improving students' ability to master comparison and scale material.

Chassis Maintenance and Vehicle Power Transfer Learning: The Effectiveness of STEM on Students' Critical Thinking Ability

The low critical thinking ability of students in the chassis maintenance and power transfer learning so that the required competencies are not achieved. This study aims to analyze critical thinking skills in chassis maintenance and power transfer learning which is taught using the Science, Technology, Engineering, and Mathematical (STEM) learning model and the conventional learning model. This research is a quasi-experimental type of research. The population in this study were students of class XI TKR 1 and XI TKR 2 as many as 69 students. Data collection techniques used documentation technique and test technique. The data analysis technique used descriptive analysis to know the category of students’ critical thinking skills and inferential analysis, including normality, homogeneity, and hypothesis by using a t-test to know the comparison of students’ critical thinking skills in learning chassis maintenance and power transfer which is taught using the Science, Technology, Engineering, And Mathematical (STEM) learning model and conventional learning models. This study shows that descriptive analysis obtained a Mean of 83.49 that was classified into a very high category and very effective category. The t-test proves the data. The tvalue value is 8045, and the ttable is df 67 = 2,000, so it can be decided that H0 is rejected. Ha is accepted because tvalue > ttable, so it can be concluded that the Science, Technology, Engineering, and Mathematical (STEM) learning model is effectively used to improve critical thinking skills compared to using conventional learning models.

Application of mathematical and machine learning models to predict differential pressure of autonomous downhole inflow control devices

Controlling reservoir fluid flow is important for maximizing petroleum production through wellbores. A major challenge that reduces the production of oil is early breakthrough of secondary fluids to the wellbore perforations. This occurs due to the low viscosity of gas and water relative to oil, and the heterogeneity of reservoir permeability. Autonomous inflow control devices represent a new self-regulating technology that helps to increase petroleum production, particularly oil, by restricting the production of unwanted fluids like gas and water into the wellbores. This study develops smart systems based on machine learning models to predict the performance of autonomous inflow control devices. Several machine learning models are evaluated including adaptive neuro fuzzy inference system, hybrid adaptive neuro-fuzzy inference system genetic algorithm, artificial neural network and support vector machine and their prediction performance is compared to that of linear regression, full quadratic regression model and the mathematical autonomous inflow control device performance model. Each model is developed to estimate the differential pressure of Equiflow autonomous inflow control devices based on ninety experimentally recorded data records. The range of equiflow autonomous inflow control device, viscosity, density and flow rate are the input variables and differential pressure is the output dependent variable of each model. The prediction accuracy of the models is assessed in terms of several standard statistical accuracy performance measures. These performance indicators confirm that the machine-learning models provide superior prediction accuracy for autonomous inflow control device differential pressure. Overall, the support vector machine achieves the most accurate predictions of all the models evaluated recording root mean square error of 0.14 Mpa and coefficient of determination of 0.98. On the other hand, the linear regression model records the lowest prediction performance, highlighting the non-linearity of the autonomous inflow control device processes. Cited as: Yavari, H., Khosravanian, R., Wood, D.A., Aadnoy, B.S. Application of mathematical and machine learning models to predict differential pressure of autonomous downhole inflow control devices. Advances in Geo-Energy Research, 2021, 5(4): 386-406, doi: 10.46690/ager.2021.04.05

Applying The Cooperative Learning Model Type of Teams Games Tournaments (TGT) to Increase Mathematics Learning Outcomes for Class VIII Students of s. Islamiah Hessa Air Genting year 2019/2020

The purpose of this study was to determine learning outcomes using the TGT type cooperative learning model in mathematics. This research was conducted at SMP S Islamiyah Hessa Air Genting, Air Batu District, Asahan Regency. This research was conducted in Semester II of the 2019/2020 Academic Year, which is March – April 2020. The subjects in this study were students of class VIII-A SMP S Islamiyah Hessa Air Genting with a total of 32 people. The method used in this research is Classroom Action Research (CAR). Through the application of the TGT type learning method, it can improve students' mathematics learning outcomes in class VIII-A SMP S Islamiyah Hessa Air Genting for the 2019/2020 academic year. This can be seen from the results of the final study test, there are 25 students who complete or 75%. But the activities in the first cycle have not been said to be successful because they have not met the classical completeness of 85% so that it needs to be repeated so that students' ability to study the material independently and discuss with their original group through the TGT type cooperative learning model can be improved, it is necessary to carry out improvements in carrying out actions classroom learning. For this reason, it was carried out in cycle II. The implementation in cycle II went better and more conducive. This can be seen from the results of the final study test, there are 28 students who complete or 87.5%. So by applying the Teams Games Tournaments (TGT) type cooperative learning model in class VIII of SMP S Islamiyah Hessa Air Genting for the 2019/2020 academic year, it can improve mathematics learning outcomes.

PENINGKATAN HASIL BELAJAR SISWA MELALUI MODEL PEMBELAJARAN PENEMUAN (DISCOVERY LEARNING) PADA MATERI PERSAMAAN LINEAR SATU VARIABEL KELAS 7D SMP NEGERI 8 KOTA BOGOR

IMPROVING STUDENT LEARNING OUTCOMES THROUGH DISCOVERY LEARNING MODELS ON ONE VARIABLE LINEAR EQUATION MATERIALS IN JUNIOR HIGH SCHOOLS (SMP NEGERI 8 KOTA BOGOR)Learning outcomes and students' understanding of the concept of One Variable Equation in Junior High School (SMP Negeri 8 Kota Bogor). is still low. For this reason, it is necessary to apply learning models which are the main contributors that need to be considered in order to improve student learning outcomes. The research was carried out in junior high schools (SMP Negeri 8 Kota Bogor) and aimed to (1) improve student learning outcomes, (2) find out whether Discovery Learning is the right learning model for Mathematics Subjects with Single Variable Linear Equations, (3) determine the magnitude of the increase in student learning outcomes , which is measured as the percentage of the number of students who get a score of 76 or meet the minimum standard of completeness criteria. The results showed that using the Discovery Learning model could significantly improve student learning outcomes in junior high schools (SMP Negeri 8 Kota Bogor). Student learning outcomes increased after using the Discovery Learning model to 70.59% in the first cycle and 100% in the second cycle. The application of this Learning Model makes learning materials more interesting and the classroom atmosphere more pleasant for students, and in the end can increase students' understanding of the material and students' values in evaluation. Therefore, the researcher recommends the use of the Discovery Learning model in learning Mathematics in schools within the Bogor City Education Office.

Need-Based and Optimized Health Insurance Package Using Clustering Algorithm

The paper presents a novel methodology based on machine learning to optimize medical benefits in healthcare settings, i.e., corporate, private, public or statutory. The optimization is applied to design healthcare insurance packages based on the employee healthcare record. Moreover, with the advancement in the insurance industry, it is rapidly adapting mathematical and machine learning models to enhance insurance services like funds prediction, customer management and get better revenue from their businesses. However, conventional computing insurance packages and premium methods are time-consuming, designation specific, and not cost-effective. During the design of insurance packages, an employee’s needs should be given more importance than his/her designation or position in an organization. The design of insurance packages in healthcare is a non-trivial task due to the employees’ changing healthcare needs; therefore, using the proposed technique employees can be moved from their existing package to another depending upon his/her need. This provides the motivation to propose a methodology in which we applied machine learning concepts for designing need-based health insurance packages rather than professional tagging. By the design of need-based packages, medical benefit optimization which is the core goal of our proposed methodology is effectively achieved. Our proposed methodology derives insurance packages that are need-based and optimal based on our defined criteria. We achieved this by first applying the clustering technique to historical medical records. Subsequently, medical benefit optimization is achieved from these packages by applying a probability distribution model on five years employees’ insurance records. The designed technique is validated on real employees’ insurance records from a large enterprise.The proposed design provides 25% optimization on medical benefit amount compared to current medical benefits amount therefore, gives better healthcare to all the employees.

The Classification of Mathematical Literacy Ability in Cognitive Growth Learning Viewed From Multiple Intelligences

The purpose of this study was to determine the quality of the Cognitive Growth mathematical learning model towards mathematical literacy ability and to describe the classification of mathematical literacy ability viewed from the multiple intelligences theory. This type of research was descriptive qualitative. The subjects of this research were 30 grade VIII students of SMP IT Ihsanul Fikri in Magelang City who had a tendency towards each type of multiple intelligences. The instruments used were a test and interview instruments. Data analysis the Miles and Huberman model. The results of the research were as follows: (1) the quality of mathematical learning using the Cognitive Growth model was in the good category; (2) the classification of mathematical literacy ability in Cognitive Growth learning viewed from multiple intelligences theory of grade VIII students was: with verbal-linguistic, logical-mathematical, and musical intelligences at level 4; with visual-spatial intelligences at level 3, with intrapersonal intelligences at level 2; and, with bodily-kinesthetic, interpersonal, and naturalistic intelligences at level 1.

Application of methods of system analysis for modeling the process of distance learning

A mathematical model of distance learning based on control theory in the form of an inhomogeneous linear differential equation is proposed. On the basis of the coefficients of assimilation and forgetting, determined with the help of special tests, it is possible to predict, in some approximation, the level of current knowledge of both the individual trainee and the group or stream of students.

Core Learning Model and Mathematical Disposition, Against Mathematics Problem Solving Ability of Elementary School Students

This research is aimed to reveal the effects of the core learning model and mathematical disposition model to problem-solving skills in elementary school. This research is experimental research with a 2x2 factorial design. The research sample is fourth-grade students, i.e., 44 persons. The instrument is the mathematical disposition and problem-solving skill instrument. The research result shows that the core learning model is a suitable mathematical learning model to develop mathematical problem-solving skills. The core learning model is more appropriately applied on a group of students with a high mathematical disposition. Meanwhile, the conventional model is more suitable to be applied on a group of students with a low mathematical disposition

Penerapan Model Pembelajaran Problem Posing dan Direct Instruction dalam Meningkatkan Kemampuan Pemecahan Masalah Matematis Siswa

The research was motivated by the problem of the low mathematical problem-solving ability of students. As an alternative to solving problems, research was conducted by applying the Problem Posing and Direct Instruction learning model in learning mathematics. The purpose of this research is to analyze the improvement of students' mathematical problem-solving abilities who study with Problem Posing and Direct Instruction learning models. The research method used is quasi-experimental with a population of all students of class XI SMA Negeri in Garut. The sample was selected based on the purposive sampling technique, and two classes were obtained as research samples. The research instrument used was a mathematical problem-solving ability test. Based on the results of statistical analysis, it was concluded that the improvement of students' mathematical problem-solving abilities who studied with the Problem Posing learning model was better than the Direct Instruction learning model. The Problem Posing learning model is recommended to develop students' mathematical solving abilities.

Federated learning for IoE environments: A service provider revenue maximization framework

In accordance with the Internet of Everything (IoE) paradigm, millions of people and billions of devices are expected to be connected to each other, giving rise to an ever increasing demand for application services with a strict quality of service requirements. Therefore, service providers are dealing with the functional integration of the classical cloud computing architecture with edge computing networks. However, the intrinsic limited capacity of the edge computing nodes implies the need for proper virtual functions' allocations to improve user satisfaction and service fulfillment. In this sense, demand prediction is crucial in services management and exploitation. The main challenge here consists of the high variability of application requests that result in inaccurate forecasts. Federated learning has recently emerged as a solution to train mathematical learning models on the users' site. This paper investigates the application of federated learning to virtual functions demand prediction in IoE based edge cloud computing systems, to preserve the data security and maximise service provider revenue. Additionally, the paper proposes a virtual function placement based on the services demand prediction provided by the federated learning module. A matching based tasks allocation is proposed. Finally, numerical results validate the proposed approach, compared with a chaos theory prediction scheme.

PENGEMBANGAN MODEL PEMBELAJARAN MATEMATIKA BERBASIS BUDAYA A’BULO SIBATANG

<p><span style="text-align: justify;">The application of a new paradigm in the form of a learning model that is adopted from outside and adapted in schools requires students and teachers to change their teaching and learning behavior. Constructive interaction between students and their peers, students and teachers, student-teacher problems are very difficult to condition. This is due to conventional teaching which conditions students to passively receive knowledge. This is evident from student activities, students are reluctant to ask the teacher and their friends even though they are given encouragement and motivation. Smart students prefer to work alone and if they have difficulty directly asking the teacher without passing the results of their group discussions. Maximum results are expected to be achieved, if the application of the new paradigm of learning mathematics is more adapted to the natural way students learn mathematics, and is also more in accordance with the essence of developing mathematical thinking skills. Learning is sought to be more meaningful in local culture and in the learning process incorporating cultural systems and cultural values found in the community in the area where students are, therefore, the purpose of this study is to formulate and compile a mathematics learning model based on A'Bulo Sibatang culture in the classroom. V SD in Bulukumba Regency. This type of research is the development of A'Bulo Sibatang-based mathematics learning model through the development of learning models, tools and instruments in an effort to improve the character of students in mathematics learning by implementing local culture in learning. Based on the results of the research, it was found that the a'bulo sibatang-based learning model was valid and met the effective criteria and the level of practicality of the model was in the high category.</span></p><p> </p&gt

Groundwater quality modeling: On the analogy between integrative PSO and MRFO mathematical and machine learning models

AbstractReliable and accurate modeling of groundwater quality is an important element of sustainable groundwater management of productive aquifers. In this research, specific conductance (SC) of groundwater is predicted based on different individual and integrative machine learning, adaptive neuro‐fuzzy inference system (ANFIS), and nonlinear mathematical models. For developing the integrative models, the well‐known particle swarm optimization (PSO) and novel manta ray foraging optimization (MRFO) heuristic algorithms are embedded in the models. Presenting different univariate, bivariate, and multivariate input scenarios, the parameters used to develop and validate the models include groundwater level, salinity, and water temperature at an observation well near Florida City. The findings reveal that applying more independent parameters (multivariate scenario) enhances the performance of both the mathematical and machine learning models. Even though the mathematical models present an acceptable performance for the prediction of SC (index of agreement, IA, equals 0.933), the ANFIS models provide the most accurate SC predictions (IA = 0.943). Both the PSO and MRFO algorithms improved the prediction capability of the ANFIS models with, respectively, 13% and 5% for the RMSE.

Penerapan Metode Probing Prompting Untuk Meningkatkan Aktivitas dan Hasil Belajar Matematika Mahasiswa AMIK Mitra Gama

In attending mathematics lectures, new students are often passive due to the non-uniform background of understanding concepts and adjustment factors for the new campus environment. This research is a Classroom Action Research (CAR) that aims to determine the increase in activity and learning outcomes of Discrete Mathematics in the first semester students of the Computer Management Skills Program to apply the Probing Prompting learning method. The research was conducted on 2018/2019 odd semester students with a total of 30 students. Data were collected through observation and learning outcomes tests. The application of the probing prompting method on the subject of the Matrix can increase the learning activities of new students; it can be seen that the average value of student learning activities from cycle I to cycle II has increased significantly. Student mathematics learning outcomes on the Matrix subject also experienced a significant increase from cycle I to cycle II. It can be concluded that the use of the probing prompting learning model in mathematics learning in the Matrix subject can increase student activity and learning outcomes.

Pengaruh Model Pembelajaran Probing-Prompting Berbasis Etnomatematika Terhadap Prestasi Belajar Matematika Siswa

One of the reasons for the low student achievement in mathematics is that the mathematics learning process carried out by the teacher tends to be theoretical and less contextual. Mathematics learning needs to be linked to student culture so that there is no gap between mathematics in everyday life and at school. Thus, it is necessary to apply a mathematics learning model based on ethno-mathematics. This study aims to determine the effect of the ethnomatematic based probing-prompting learning model on students' mathematics learning achievement. This type of research is quantitative research with pre-experimental methods and one-group pretest-posttest design. The sample of this research is class VIII A SMPK St. Yoseph Naikoten Kupang, totaling 24 people. The pretest and posttest values as research data were analyzed using the SPSS version 22 program. Based on the results of data analysis, thitung (39,594)> ttabel (2,069) with an error rate of 0.05, which means accept Ha or the ethnomatematic based probing-prompting learning model has an influence which is significant towards the mathematics learning achievement of students class VIII SMPK St. Yoseph Naikoten Kupang.