Journal of Mathematics Education and Science

Optimizing Student Performance Assessment and Ranking Using the SAW–TOPSIS Approach

2026-04-26T04:56:52+00:00

Student assessment is a fundamental aspect of education for comprehensively measuring learning progress. Given that conventional assessment systems, which focus solely on academic grades, often neglect other important aspects of student performance, a more objective and holistic approach is necessary. This study aims to explain the implementation of a combined method of SAW and TOPSIS to optimize student performance assessment and ranking. This research uses a descriptive quantitative approach with data collection techniques through interviews and documentation. The results show that the combination of the SAW and TOPSIS methods can provide an objective ranking of students based on the predetermined criteria: academic scores, extracurricular scores, academic or non-academic achievement scores, attendance scores, violation scores, and madrasah scores. From the calculation results, the student with the highest rank is S06 with a preference value of 0,622009183, while the student with the lowest rank is S19 with a preference value of 0,137883342. This ranking provides a clearer picture of each student's performance, which can be used as a basis for evaluation and decision-making by the school.

Numerical Modeling of Oil Palm Plantation Area Growth in Indonesia Using Verhulst Model

2026-07-02T08:40:29+00:00

The expansion of oil palm plantation area in Indonesia exhibits nonlinear growth behavior influenced by environmental, spatial, and policy constraints. This study aims to model the growth of oil palm plantation area using the Verhulst (logistic) growth model and to obtain numerical solutions of the resulting nonlinear differential equation. A quantitative approach is employed, in which the fourth-order Runge–Kutta (RK4) method is used to generate the required initial values, followed by two predictor–corrector schemes, namely the Adams–Bashforth–Backward Differentiation Formula (AB4–BDF4) and the Milne–Backward Differentiation Formula (Milne–BDF4), which are compared to approximate the long-term growth dynamics. The analysis utilizes annual oil palm plantation area data from 2017 to 2024 obtained from Statistics Indonesia (BPS). Numerical results indicate that all methods produce stable solutions, with relative errors remaining bounded and non-divergent throughout the simulation, on the order of 10^-6. On average, the AB4–BDF4 scheme yields a relative error of 3.2477330 × 10^-6, compared to 5.9206896 × 10^-6 for the Milne–BDF4 scheme, corresponding to an accuracy improvement of approximately 1.8 times. The estimated intrinsic growth rate is r≈0.15, and the estimated carrying capacity is 20 million hectares, representing the maximum sustainable oil palm plantation area under current growth trends.

Developing a Hypothetical Learning Trajectory for Linear Functions Through Collaborative Mathematical Modeling

2026-07-05T13:09:31+00:00

Students still encounter difficulties in understanding linear functions, particularly when they are required to connect contextual situations with mathematical forms and to understand variables, constant change, and symbolic representations. This study aims to develop and describe students' learning trajectory in learning linear functions through a collaborative mathematical modeling approach using the context of a leaking faucet. This study employed a design research method consisting of three stages: preparing for the experiment, conducting the design experiment, and performing retrospective analysis. The participants were eighth-grade junior high school students grouped heterogeneously according to their mathematical ability. The learning design was structured based on six stages of mathematical modeling. The results indicate that the leaking-faucet context helped students understand the relationship between time and water volume as a linear function. Students were able to identify the problem, formulate assumptions, conduct experiments, construct a model, evaluate the model, and apply it to estimate losses caused by water leakage. Therefore, a learning trajectory based on collaborative mathematical modeling can support students' understanding of linear functions.

Students' Geometric Thinking Processes Through the Lens of Duval's and Van Hiele's Theories: A Gender-Based Analysis

2026-07-07T07:00:04+00:00

This study aims to explore the geometric thinking processes of junior high school students in solving problems involving flat-sided three-dimensional shapes, with a focus on gender differences. The analysis was conducted by integrating Van Hiele’s theory of geometric development levels and Duval’s cognitive theory. This was a qualitative study using a collective instrumental case study design. The research subjects consisted of 2 male and 2 female ninth-grade students at SMP Negeri 24 Penajam Paser Utara. The instruments used were the Van Hiele Geometry Test (VHGT) and problem-solving task-based interviews using the think-aloud method. The validity of the findings was assessed using triangulation. The results showed that Level 0 (visualization) students’ thinking was heavily dependent on static visual representations; they experienced cognitive paralysis in the symbolic monofunctional register; and they failed in formal discursive apprehension. Level 1 (analysis) students were able to analytically break down functional geometric components, mastered the principle of spatial invariance, and were skilled at performing multidirectional conversions between semiotic registers. Female subjects tended to be formal, procedural, structured, and sequential, and were strong in verbal and written articulation. Male subjects tended to be globally intuitive through direct mental modeling but were prone to encountering obstacles in the realm of formal verbal mathematical discourse.