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Journal of Mathematics Education and Science
Published by Universitas Nahdlatul Ulama Sunan Giri Bojonegoro
ISSN : 26211203     EISSN : 26211211     DOI : https://doi.org/10.32665/james
Core Subject : Education,
Education Mathematics
Journal of Mathematics Education and Science (JaMES) is a mathematical journal published biannually (April & October) by the Mathematics Educations Department, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Nahdlatul Ulama Sunan Giri Bojonegoro. Journal includes research papers, literature studies, analysis, and problem-solving in Mathematics Education or Mathematical Sciences (Algebra, Analysis, Statistics, Computing and Applied).
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 143 Documents
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ANALYSIS OF STUDENT ERRORS IN LEARNING THE INTEGRAL CALCULUS COURSE WITH THE HELP OF AI (Artificial Intelligence) Titin Supriyatin; Noni Selvia; Syafa’atun
Journal of Mathematics Education and Science Vol. 9 No. 1 (2026): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v9i1.6353

Abstract

This study addresses a gap in mathematics education research concerning the use of artificial intelligence (AI) to analyze student errors in integral calculus. Error analysis in calculus is still commonly conducted manually by lecturers, making it time-consuming, potentially subjective, and difficult to implement consistently across an entire class. Although previous studies have examined student errors in calculus, limited research has explored AI as a systematic diagnostic tool, especially among non-mathematics students. Therefore, this study aims to identify the types of errors made by students in solving integral calculus problems using an AI-based system and to examine the role of AI in supporting more accurate and targeted diagnostic assessment. The participants were 30 second-semester students from the Biology Education Study Program at Universitas Indraprasta PGRI who were taking the Integral Calculus course. This study employed a descriptive qualitative approach. An AI-based system was used to analyze students’ responses to a set of integral calculus problems and classify them into four categories: conceptual errors, procedural errors, technical errors, and errors in understanding the problem. The results showed that conceptual errors were the most dominant, occurring in 45% of students, particularly in misunderstanding the meaning of integrals and misusing integration limits. Procedural errors were found in 30% of students, technical errors in 15%, and problem-understanding errors in 10%. This study contributes empirical evidence on student error patterns, strengthens the role of AI as a systematic diagnostic tool, and provides a practical basis for lecturers to design more targeted remedial instruction in higher education settings.
ANALISIS BERPIKIR KREATIF GENERASI ALPHA DALAM MENYELESAIKAN WORD PROBLEM MATHEMATICS DITINJAU DARI GAYA BELAJAR SISWA SMP Sukma Ayu; FX Didik Purwosetiyono; Dewi Wulandari
Journal of Mathematics Education and Science Vol. 9 No. 1 (2026): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v9i1.6378

Abstract

This study aims to investigate and analyze the creative thinking abilities of Generation Alpha junior high school students in solving systems of linear equations in two variables (SPLDV) word problems, viewed from their learning styles. The research employed a descriptive qualitative approach supported by NVivo software for automatic coding (autocode) and thematic visualization. The subjects consisted of 24 eighth-grade students from a school in Tegal regency, with results showing that 45.8% were visual learners, 29.1% auditory learners, and 25% kinesthetic learners. Furthermore, three students were purposively selected since it adequately represents the variety within the category to represent each learning style category for in-depth analysis. The instruments used included a learning style questionnaire, SPLDV word problem tests, and interview guidelines. Data were analyzed using the Miles and Huberman interactive model, while validity was ensured through methodological triangulation. The findings reveal that: (1) visual learners demonstrated all four indicators of creative thinking, with a notable strength in flexibility; (2) auditory learners achieved three indicators, particularly excelling in fluency; and (3) kinesthetic learners fulfilled four indicators, with a strong emphasis on elaboration. The prevalence of short-form visual content on social media influences Generation Alpha’s learning preferences, which are faster-paced and more visually oriented.  
Optimal Control in an SDC Mathematical Model for Diabetes Complications at a Hospital in Lamongan Regency Alvina Wiliyanti; Awawin Mustana Rohmah; Muhammad Syaiful Pradana
Journal of Mathematics Education and Science Vol. 9 No. 1 (2026): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v9i1.6401

Abstract

Diabetes is a chronic disease whose prevalence continues to increase and has the potential to cause serious complications if not properly managed. This study aims to analyze the dynamics of diabetes progression and its complications, as well as to determine optimal control strategies using a mathematical model based on data from a hospital in Lamongan Regency. The model used is a compartmental SDC (Susceptible–Diabetes–Complication) model formulated as a system of ordinary differential equations with two time-dependent control variables. The optimal control is determined using Pontryagin’s Maximum Principle, while the numerical simulations are solved using the fourth-order Runge–Kutta (RK4) method. Model parameters are obtained from the literature and epidemiological data, and then calibrated to match the characteristics of real-world cases. The simulation results show that without control, the susceptible population decreases from approximately 1500 to about 200 individuals, while the complication population increases to around 1700 individuals. With the implementation of optimal control, the susceptible population increases to approximately 1250 individuals, the number of diabetic patients decreases to around 820 individuals, and the complication population is reduced to about 980 individuals. These results indicate that control strategies focused on diabetic patients are effective in suppressing disease progression and preventing complications, and contribute to the development of data-driven mathematical models for local healthcare policy planning.

Page 15 of 15 | Total Record : 143

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