Journal of Research on Mathematics Instruction (JRMI)

An Analysis of Students' Conceptual Understanding in the Pythagorean Theorem Material

Yuce Sandra — Mon, 30 Jun 2025 00:00:00 +0700

Conceptual understanding is a fundamental skill and one of the primary goals of mathematics learning, where students are expected to comprehend concepts, explain relationships between concepts, and apply them in mathematical problem-solving processes. However, observations reveal that students generally exhibit relatively low levels of conceptual understanding when solving mathematical problems, mainly due to insufficient mastery of prerequisite materials. The purpose of this study is to analyze students' conceptual understanding of the Pythagorean Theorem based on the conceptual understanding indicators proposed by the National Research Council. The research method used is qualitative with a descriptive approach, specifically a hermeneutic phenomenological study. Qualitative data were obtained from document analysis, test results, and interviews involving 29 junior high school students. The findings based on five test items representing the conceptual understanding indicators show that the most mastered indicator by students is the ability to apply and use the concept appropriately. Conversely, the least mastered indicator is the ability to classify objects based on mathematical concepts.

Improving the Mathematics Learning Process and Students' Problem-Solving Skills through Problem-Based Learning

Miranda Raihanah, Kartini, Nahor Murani Hutapea — Mon, 30 Jun 2025 00:00:00 +0700

This study aims to improve the learning process and improve students' mathematical problem-solving abilities by implementing the problem-based learning model. The subjects of this study were students of class VIII.1 of SMP YLPI P. Marpoyan in the first semester of the 2024/2025 academic year. This study consisted of two cycles, the first cycle containing two meetings with the material One Variable Linear Equations, and the second cycle containing two meetings with the material One Variable Linear Inequalities. Data analysis was carried out using a combination of qualitative descriptive analysis and quantitative descriptive statistical analysis. The data analysis technique used in this study consists of analyzing data on teacher and learner activities and analyzing data on students' mathematical problem-solving abilities. The results showed that the application of the problem-based learning model improved the learning process and improved students' mathematical problem-solving abilities. The average N-gain score increased from 0,58 with a medium classification in cycle I to 0,88 with a high classification in cycle II. In addition, the average student test increased from 54,38 in cycle I to 76,88 in cycle II. The results showed that the application of the problem-based learning model improved the learning process and improved the mathematical problem-solving abilities of class VIII.1 SMP YLPI P. Marpoyan.

Enhancing Mathematics Achievement with Problem-Based Learning: A Classroom Action Research

Aulia Wahyuni Hendrianti, Kartini, Atma Murni — Mon, 30 Jun 2025 00:00:00 +0700

This research was motivated by the low mathematics learning outcomes of students in class VII-1 SMPN 19 Pekanbaru, which was indicated by the achievement of Learning Objective Achievement Criteria (KKTP) of only 8 out of 36 students. The purpose of this study was to increase learning outcomes and improve the learning process of mathematics through the application of the Problem-Based Learning (PBL) model. This research is a Classroom Action Research (PTK) carried out in two cycles, each consisting of planning, implementation, observation, and reflection stages. The research subjects were 36 students with heterogeneous ability levels. The research instruments included learning tools (ATP and teaching modules) as well as observation sheets of teacher activity, students' activity, and learning outcome tests. The results showed an increase in students' activity in the learning process. Students were more active, able to work together in groups, and able to build their own knowledge meaningfully. The percentage of students who reached KKTP increased from the base score of 38.88% to 52.77% in cycle I, and it increased again to 80.55% in cycle II. Based on these data, it can be concluded that the application of the Problem-Based Learning model is effective in improving the learning process and increasing mathematics learning outcomes.

The Relationship between Adaptive Reasoning Ability and Student Self-Efficacy on Comparison Materials

Thassya Novanka Efendi, Al Jupri, Dadan Dasari — Mon, 30 Jun 2025 00:00:00 +0700

This study aims to investigate the relationship between Adaptive Reasoning Ability (ARA) and self-efficacy among 8th-grade students at SMP IT Al-Fityah Pekanbaru for the 2024/2025 academic year. This research is a survey study with a quantitative approach. The subjects of this study were 25 8th-grade students at SMP IT Al-Fityah Pekanbaru. Data were collected using two instruments: a mathematical reasoning test and a self-efficacy questionnaire. Data analysis consisted of two parts: descriptive and inferential analysis. The descriptive analysis revealed that the average of the ARA score (62.5) was in the fair category, while the average of the self-efficacy score (71.8) was in the high category. The Pearson correlation analysis indicated a very weak positive correlation (r=0.007) with no statistical significance (p=0.974), suggesting that self-efficacy does not significantly influence ARA. These findings highlight the need for more practice-oriented learning to strengthen students’ adaptive reasoning skills regardless of their self-efficacy levels.

Multivariate Statistical Approach: Factor Analysis of Scabies Incidence in the Working Area of Bea Muring Health Center

Mon, 30 Jun 2025 00:00:00 +0700

This study aims to demonstrate the application of factor analysis as one of the multivariate statistical methods in processing epidemiological data. Factor analysis is employed to reduce a set of correlated variables into simpler factors, thereby enabling more efficient identification of inter-variable relationship patterns. The data were obtained from surveys conducted within communities experiencing specific epidemiological cases, and were subsequently analyzed using validity testing, reliability testing, the Kaiser-Meyer-Olkin (KMO) measure, and Bartlett’s Test of Sphericity as prerequisites for analysis. The results indicate that out of the initial 19 variables, 15 met the criteria and were reduced into three main factors, explaining a total variance of 74.79%. Factor 1 accounted for 44.45% of the variance, Factor 2 for 18.08%, and Factor 3 for 12.25%. These findings highlight the effectiveness of factor analysis in reducing the dimensionality of epidemiological data while identifying dominant factors influencing the observed phenomenon. In conclusion, this study demonstrates the potential of factor analysis as a relevant multivariate statistical method for handling complex data in public health as well as other applied fields.