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Mathema: Jurnal Pendidikan Matematika
Published by Universitas Teknokrat Indonesia
ISSN : 27221466     EISSN : 26865823     DOI : https://doi.org/10.33365/jm
Core Subject : Education,
Mathematics
Mathema: Jurnal Pendidikan Matematika (E-ISSN: 2686-5823, P-ISSN: 2722-1466) is a single peer-reviewed journal published by the Universitas Teknokrat Indonesia. This journal aims to facilitate and promote the dissemination of scholarly information on research and development in the field of Mathematics and Mathematics Education. The articles published in this journal can be the result of research, conceptual thinking, ideas, innovations, best practices, and book reviews.The scopes of this journal include the following topic areas: - Mathematics Teaching and Learning - Mathematics Curriculum Development - Mathematics Teacher Education - Educational Technology of Mathematics
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 49 Documents
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Deep Learning Approach in Toraja Culture-Based Mathematics Learning and its Effect on Primary Students’ Problem-Solving Skills Yanti Lisa Lambe; Suri Toding Lembang; Ranak Lince
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1045

Abstract

This study aims to explore the Deep Learning approach in Toraja culture-based mathematics learning on the problem-solving skills of junior high school students. The research used an embedded sequential explanatory mixed methods design, with a quantitative approach as the primary method and a qualitative approach as supplementary. The subjects consisted of an experimental group and a control group. Quantitative data were collected through pre- and post-treatment essay tests and analyzed using ANCOVA, while qualitative data were obtained through interviews analyzed thematically. The results indicate that the Toraja culture-based Deep Learning approach had a significant effect on improving problem-solving skills (F(1,54)=48.206; p<.001) with a large effect size (ηₚ²=0.471). Qualitative data reinforce these findings by showing increased student engagement, reflection, and metacognitive awareness. The integration of Toraja culture into Deep Learning strengthens the meaning, relevance, and transfer of mathematical knowledge within students' socio-cultural context.
Analysis of Students' Creative Thinking Abilities in Mathematics Problems on Arithmetic Sequences and Series at SMA Negeri 1 Sedayu Riska Natasi Br Ginting; Suhartati Suhartati; Naela Faza Fariha
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1101

Abstract

This study employs a descriptive qualitative approach, utilizing a case study method, to explore students' creative thinking abilities in depth when solving mathematical problems related to arithmetic sequences and series. The research subjects were 35 grade X students of SMA Negeri 1 Sedayu who were selected using a purposive sampling technique. Data were collected through essay tests that measure four indicators of creative thinking abilities: fluency, flexibility, originality, and elaboration, as well as semi-structured interviews and documentation of student work results. Data validity was tested through triangulation and observational persistence. The results showed that most students were classified as creative to very creative (77.1%). Fluency and flexibility aspects dominated, while originality and elaboration still varied among students. This study emphasizes the importance of providing open-ended questions and reflective learning to improve mathematical creative thinking abilities.
Spatial Ability in Mathematics Learning: A Systematic Review from the Perspective of Technology and Learning Models Zulfa Dayyinati Fa'izulloh; Bambang Eko Susilo; Arief Agoestanto; Scolastika Mariani
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1106

Abstract

This study aims to examine the role of technology and learning models in improving students’ spatial abilities in mathematics learning. Using the Systematic Literature Review (SLR) method guided by the PRISMA framework, this study analyzed seven relevant articles published between 2020 and 2025 from reputable databases such as Google Scholar, Semantic Scholar, and SINTA. The findings indicate that various learning technologies, including GeoGebra, Augmented Reality (AR), Virtual Reality–based mobile learning, Math City Maps, and Adobe Flash, have a positive impact on supporting visualization, interaction, and students’ understanding of geometric and spatial concepts. In addition, constructivist-oriented learning models such as Problem Based Learning (PBL), Guided Discovery Learning, Contextual Teaching and Learning (CTL), the Van Hiele model, and Thinking Aloud Pair Problem Solving (TAPPS) provide more meaningful learning experiences by encouraging active exploration, discussion, and independent construction of spatial concepts. The results further demonstrate that the integration of interactive and immersive technologies with appropriate learning models produces a synergistic effect in enhancing students’ mathematical spatial abilities. These findings offer an important foundation for educators in designing mathematics instruction that is more innovative, contextual, and aligned with the characteristics of the digital generation. Future research is recommended to further investigate the effectiveness of specific combinations of technologies and learning models in authentic classroom settings
A Systematic Study: The Use of Artificial Intelligence and Search Engines in Mathematics Learning Yuanda Oktrin Lay; Jailani
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1132

Abstract

Mathematics education in the digital age faces new challenges and opportunities with the advent of technology. Artificial Intelligence and Search Engines have become tools that are often used in the process of searching for information and learning. This study aims to identify, map, and synthesize the latest scientific research on the role, impact, and challenges of using artificial intelligence and search engines in the context of mathematics education. The method used is a systematic study of 26 relevant articles from 2016 to 2025, which are included in the Q1, Q2, and Q3 indices, obtained through a selection process similar to the PRISMA guidelines. The results of the thematic analysis revealed several key findings: (1) There was a significant boom in research trends in 2024-2025, dominated by Generative AI research (such as ChatGPT). (2) The role of artificial intelligence has evolved from intelligent tutor systems (ITS) to dialogic personal tutors (chatbots) and adaptive learning platforms. (3) The role of traditional search engines as information retrieval tools is shifting and, in some cases, being replaced by generative AI capable of synthesizing answers. (4) Consistent positive impacts reported include increased motivation, problem solving, and self-efficacy, but these are offset by challenges related to accuracy, bias, and the urgent need for AI literacy among teachers and students. This study concludes that the state of mathematics learning technology is rapidly shifting toward AI-based systems, which requires pedagogical adaptation and further research on their integration in the classroom.
Prospective Mathematics Teachers’ Creativity in Developing Mathematics Problems Based on Ethnomathematics Context and AKM Framework Eka Sulistyawati; Dwi Shinta Rahayu
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1136

Abstract

Developing instrument tests is an important skill for prospective teachers. The implementation of the Merdeka Curriculum is a means to meet 21st-century skills, one of which is numeracy literacy. This study aims to describe the creativity of prospective teachers and the cognitive level of the developed mathematics problem oriented with Minimum Competency Assessment (AKM) using ethnomathematics context. This qualitative research employed a phenomenological approach, with subjects 7th-semester prospective teachers at an Islamic higher education. Stratified random sampling and maximum variation sampling techniques were used to select 12 students from 96 based on prerequisite course grades. Student creativity in constructing problems was assessed using rubrics based on creativity indicators: fluency, flexibility, and elaboration. The Gwet AC1 Coefficient was used to ensure agreement on the scoring results. Based on the fluency indicator, the results showed that the algebra content was the most difficult to develop, while the measurement and geometry content was the easiest. Based on the flexibility indicator, the majority of the problems were at the application level, and the fewest were at the reasoning level. Considering the level of problems, content on measurement & geometry, data & uncertainty, and algebra were least frequently developed into reasoning-level problems. Based on the problem type in the elaboration indicator, the majority of students developed problems that did not contain new additional information. The least frequently developed problem type was one that included additional information but was not necessary to solve the problem. The findings of this study imply the necessity of measuring teachers' numeracy literacy skills before students' numeracy literacy is developed and measured, as well as the importance of problem development training.
Analysis of Students’ Conceptual Understanding of Pythagorean Prerequisite Concepts Retno Ayu Wulandari; Yelli Ramalisa; Duano Sapta Nusantara
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1143

Abstract

This study aims to determine students' ability to understand the prerequisite material for Pythagorean concepts. The study was conducted using a descriptive qualitative approach. The subjects of this study were students of class VIII B at SMP Adhyaksa 1 in Jambi City. Data collection involved written tests, interviews, and documentation, followed by analysis through data reduction, data presentation, and the formulation of conclusions. Data analysis was conducted based on concept comprehension indicators, namely 1) restating a concept, 2) writing down concepts in various mathematical representations, 3) using certain procedures, and 4) applying a concept. Based on the findings, of the 14 students, 7 were classified as having low comprehension, 5 were categorized at a moderate level, and 2 students achieved a high level of comprehension. This shows that students' conceptual understanding abilities vary. The results of the study show that students' conceptual understanding of the prerequisite material on Pythagoras tends to be low, with 50% in the low category. Some students showed fairly good achievement in the indicators of restating concepts and representing concepts. However, students were still weak in the indicators of selecting and using specific procedures and applying concepts.
Unveiling Cognitive Dynamics and Classroom Culture: A Literature Review of Qualitative Research in Mathematics Education Fadhlur Rohman; Lulu Sekardini; Nadila Nadila; Arvina Tri Septiani; Sri Hastuti Noer; Agung Putra Wijaya
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1145

Abstract

This study aims to analyze the contribution of qualitative research approaches, particularly ethnography and case studies, in unveiling the interplay between classroom culture and students' mathematical thinking processes. Using a literature review method, this study synthesizes scholarly sources from 2015 to 2025 to deepen the understanding of how social context influences cognitive construction in mathematics education. The findings reveal that mathematical thinking is not an isolated cognitive activity but is deeply embedded in classroom culture. Ethnographic approaches effectively uncover the "hidden curriculum" and cultural norms that shape learning, while case studies provide granular insights into students' specific cognitive hurdles. The integration of these approaches with constructivist pedagogies, such as Realistic Mathematics Education (PMRI), offers a robust framework for creating more meaningful and culturally responsive learning environments. This study concludes that qualitative inquiry is essential for bridging the gap between individual cognition and social context, providing a humanistic perspective on mathematics education.
Analysis of Instrument Quality in Measuring Mathematical Logical Thinking Ability Yulia Pratiwi; Niki Pujarwati; Marlinawati Marlinawati; Agung Putra Wijaya; Chika Rahayu
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1162

Abstract

The ability to think logically in mathematics is a skill that must be developed through instruction. One strategy for developing this ability is the use of high-quality instruments. Therefore, this study aims to analyze the quality of a mathematical logical thinking ability test instrument in terms of its validity, reliability, difficulty index, and discriminating power using SPSS and Microsoft Excel. This research employed a quantitative method with an evaluative analysis approach. The subjects in this study were students of class VII.6 and VII.8 at SMPN 26 Bandarlampung. The instrument used was a descriptive test consisting of ten items, developed based on four indicators of logical thinking ability, namely the ability to interpret information, the ability to predict, the ability to solve problems, and the ability to draw conclusions. The results of this study indicate that: (1) the quality of the logical thinking ability test instrument meets the criteria for 100% validity; (2) the reliability of the logical thinking ability test instrument is 0.775, categorized as reliable; (3) the difficulty level analysis shows that nine items fall into the moderate category and one item falls into the easy category; (4) the discrimination power analysis shows that four items have good discriminating power and six items have fair discriminating power.
The The Effect of Problem Based Learning Integrated with Deep Learning on Students’ Mathematical Reasoning Ability Zakiya Amalia Hartanto Putri; Hepsi Nindiasari
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1164

Abstract

This study aims to determine the effect of the Problem Based Learning model integrated with Deep Learning on junior high school students’ mathematical reasoning ability, as well as the level of improvement after the learning intervention. This research employed a quantitative approach using a quasi-experimental One-Group Pretest–Posttest design. The sample consisted of one class of junior high school students who received problem-based learning with a deep learning approach over four sessions. The research instrument was a mathematical reasoning test administered before and after the intervention. Data were analyzed using descriptive statistics, normality testing, paired sample t-test, and N-Gain analysis. The results show that the Problem Based Learning model with Deep Learning has a significant effect on students’ mathematical reasoning ability, indicated by a significance value of p < 0.05. Furthermore, the N-Gain analysis revealed a moderate level of improvement. Thus, the Problem Based Learning model integrated with Deep Learning is effective in enhancing students’ mathematical reasoning ability.
A Meta Analysis – Factors That Influence the Level of Statistical Reasoning of Students in Indonesia Amelia Destiana; Nurul Astuty Yensy
MATHEMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 8 No. 1 (2026): MATHEMA
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jm.v8i1.1175

Abstract

In today's digital world, Indonesian students face significant challenges with statistical reasoning, a crucial 21st-century skill needed for data interpretation and informed decision-making in academic and daily contexts. To address this educational gap, researchers conducted a comprehensive meta-analysis of 17 empirical studies published from 2012-2024, systematically examining various factors that influence students' statistical reasoning abilities in Indonesia. The study methodically categorized these influences into internal factors stemming from individual student characteristics and external factors related to environmental and instructional elements. The findings revealed that the implementation of Contextual Teaching and Learning (CTL) combined with Realistic Mathematics Education (RME) learning models had the most significant positive impact on enhancing students' statistical reasoning capabilities. These research results provide valuable evidence-based insights for educators, curriculum developers, and policymakers to create more effective educational frameworks and teaching strategies that can substantially enhance statistical literacy among Indonesian students, ultimately improving their capacity for data-driven decision-making in both formal educational settings and practical real-world applications.

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