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JTAM (Jurnal Teori dan Aplikasi Matematika)
Published by Universitas Muhammadiyah Mataram
ISSN : 25977512     EISSN : 26141175     DOI : 10.31764/jtam
Core Subject : Education,
Mathematics
Jurnal Teori dan Aplikasi Matematika (JTAM) dikelola oleh Program Studi Pendidikan Matematika FKIP Universitas Muhammadiyah Mataram dengan ISSN (Cetak) 2597-7512 dan ISSN (Online) 2614-1175. Tim Redaksi menerima hasil penelitian, pemikiran, dan kajian tentang (1) Pengembangan metode atau model pembelajaran matematika di sekolah dasar sampai perguruan tinggi berbasis pendekatan konstruktivis (PMRI/RME, PBL, CTL, dan sebagainya), (2) Pengembangan media pembelajaran matematika berbasis ICT dan Non-ICT, dan (3) Penelitian atau pengembangan/design research di bidang pendidikan matematika, statistika, analisis matematika, komputasi matematika, dan matematika terapan.
Arjuna Subject : -
Articles 565 Documents
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Modelling the Prevalence of Stunting in Toddlers Aged 6 – 23 Months in Indonesia with Approaches Multivariate Adaptive Regression Splines and Generalized Additive Model Aflaha, Nabila Shafa; Oktavia, Sabrina Salsa; Kurniawan, Ardi
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.35644

Abstract

Stunting remains a major global public health issue, marked by growth failure caused by long-term nutritional deficiencies in early childhood. In Indonesia, stunting prevalence among children under five was reported at 21.5% in 2023. This study employs an analytical observational approach with a cross-sectional design to examine nutritional factors associated with stunting among children aged 6–23 months in Indonesia, using Multivariate Adaptive Regression Splines (MARS) and Generalized Additive Models (GAM). Secondary data were obtained from the 2024 Indonesian Nutritional Status Survey (SSGI), encompassing 36 provinces. Stunting prevalence was defined as the response variable, while predictor variables included the consumption of animal-source protein, sweetened beverages, unhealthy foods, and the lack of fruit and vegetable intake. The analysis began with descriptive statistics and was followed by MARS and GAM modelling. Model performance was assessed using the coefficient of determination (R²) and Root Mean Square Error (RMSE). The findings indicate that the GAM model outperformed MARS, achieving a higher R² 0.7734 and a lower RMSE 2.5968, compared to MARS with an R² of 0.7319 and an RMSE of 2.8249. While MARS effectively identified structural changes through hinge functions, GAM offered greater modelling flexibility via smooth functions. Among the examined factors, animal-source protein intake showed the strongest association with stunting, followed by the consumption of sweetened beverages and unhealthy foods, whereas inadequate fruit and vegetable intake exhibited a weaker relationship. Overall, both approaches were effective, although GAM demonstrated superior predictive capability for provincial-level stunting analysis.
Students’ Cognitive Load in Understanding Linear Equation in One Variable Rofiq, Ainur; Sudirman, Sudirman; Muksar, Makbul
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.36034

Abstract

Cognitive load is the mental effort made by students in their working memory to process information received. This study aims to describe the cognitive load of students in understanding linear equation in one variable material. The research method used is qualitative with a case study type of research. The research was conducted at a junior high school in Malang. The research subjects were two active students selected based on the recommendation of the mathematics teacher in the class. Data were collected through observation sheets, interviews, and student reflection sheets, then analyzed using data reduction, data presentation, and conclusion drawing techniques. The results showed that students experienced intrinsic, extraneous, and germane cognitive load. Intrinsic cognitive load occurred when faced with complex problems and story problems that required the processing of several concepts at once, such as equations, integer operations, distributive properties, and algebraic operations. Students experienced extraneous cognitive load because they did not have sufficient prerequisite knowledge due to the teacher providing apersepsi that did not help activate students' prior knowledge. Students misunderstood the definition of a linear equation in one variable and only memorized the rules for moving terms because the teacher used inappropriate terms in their explanation. Students were confused in understanding simple example questions because the teacher explained too quickly without giving students time to understand. Students' attention was divided because the teacher gave examples in the workbook, while the steps to solve the problems were written on the board. Students were unable to complete the exercises because the teacher did not pay attention to their understanding. Germane cognitive load occurred because students' understanding was procedural. This was because the teacher's learning strategy did not support the formation of knowledge schemas. These findings have implications for teachers to design learning that takes into account students' working memory capacity.
Measuring the Impact of APOS Theory-Based Contextual Mathematics Assignments on the Mathematical Communication Skills of Prospective Teacher Students Jaya, Ilham; Nurkhasyanah, Alfiyanti; Fitria, Anna; Salsabila, Ismi
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.36568

Abstract

Mathematical communication skills are essential for conveying ideas, interpreting symbols, and linking abstract concepts to contextual phenomena. This study aims to measure the effectiveness of applying APOS theory-based contextual tasks in improving the mathematical communication skills of prospective teacher students. This study uses a quasi-experimental design with a non-equivalent control group model, involving an experimental class that receives contextual task-based learning using the APOS theory approach and a control class that follows conventional learning. The instrument used was a mathematical communication skills test covering five main indicators, namely the ability to express ideas in writing, use representations, explain procedures, relate concepts to real contexts, and construct mathematical arguments. The data were analyzed using the Rasch model, normality test, homogeneity test, independent t-test, score improvement analysis, and PLS-SEM-based structural modeling. The results indicate that the instrument demonstrates strong validity and reliability, as reflected by average Infit and Outfit MNSQ values of 1.00, item reliability of 0.89, and person reliability of 0.84. Significant differences were found between the experimental and control groups across all indicators of mathematical communication skills, with higher posttest mean scores in the experimental group (76.10) compared to the control group (49.87), as well as greater learning gains in the experimental group (N-Gain 68.27%) than in the control group (33.18%). The structural model further confirms the positive contribution of APOS theory to mathematical communication skills, particularly in explaining procedures (β = 0.323) and using mathematical representations (β = 0.257). Overall, this study confirms that the application of APOS theory-based contextual tasks is effective in strengthening the mathematical communication skills of prospective teachers and provides important implications for the development of a more contextual and meaningful mathematics education curriculum. 
Random Forest-Based Modeling of Life Expectancy in Central Kalimantan Puspitorini, Mega; Ayu, Regina Wahyudyah Sonata; Monita, Dita
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.35399

Abstract

This study investigates key socioeconomic determinants of life expectancy (LE) and develops a regional-level predictive model using the Random Forest regression approach for regencies and municipalities in Central Kalimantan Province during 2016–2023. Although life expectancy is a core indicator of human development, empirical studies employing machine learning methods at the sub-provincial level in Indonesia remain limited. Using secondary data from Statistics Indonesia (BPS), this study examines the relationship between LE and selected indicators related to education, sanitation, health infrastructure, economic conditions, and demography. The Random Forest model exhibits robust predictive performance, achieving MAE values of approximately 0.29–0.30 and coefficients of determination (R²) ranging from 0.71 to 0.74 across different evaluation schemes. Feature importance analysis identifies mean years of schooling as the most influential determinant of life expectancy, followed by access to proper sanitation and the availability of health facilities. These results highlight the prominent role of human capital and basic infrastructure in shaping regional health outcomes. By integrating machine learning techniques with regional socioeconomic data, this study extends existing life expectancy research in Indonesia through a data-driven modeling framework. Overall, this study supports evidence-based planning by highlighting priority intervention areas to improve life expectancy and human development in Central Kalimantan.
Forecasting Indonesia’s Export Revenue through a Vector Autoregressive Exogenous Approach Sudarwanto, Sudarwanto; Puteri, Syafa Marisha; Santi, Vera Maya; Alwansyah, Muhammad Arib
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.36760

Abstract

The Vector Autoregressive with Exogenous Variables (VARX) model extends the conventional VAR framework by explicitly incorporating external macroeconomic drivers, offering a more structurally informed approach to export forecasting. This study contributes to the literature by introducing a disaggregated modeling strategy that treats oil and gas exports and non-oil and gas exports as separate endogenous components, an aspect that has been largely overlooked in previous studies on Indonesia’s export performance. By positioning VARX as a system-based forecasting tool rather than a purely statistical extension, this research provides an updated methodological perspective on export revenue analysis. Using monthly data from January 2015 to December 2024, this study evaluates several VARX specifications that integrate the rupiah–US dollar exchange rate and West Texas Intermediate (WTI) crude oil prices as exogenous variables. Model selection is conducted based on a combination of information criteria and forecasting performance indicators, leading to the identification of VARX(5,6) as the most suitable specification. The inclusion of exogenous variables is shown to substantially enhance predictive accuracy, confirming the relevance of external economic shocks in shaping Indonesia’s export revenue dynamics. Empirical results indicate that WTI oil prices exert a significant causal influence on export revenue, while the exchange rate effect becomes meaningful when jointly evaluated with oil prices and endogenous export components. The selected VARX(5,6) model demonstrates strong forecasting performance, achieving a MAPE of 5.60% and an nRMSE of 6.40%. From a policy standpoint, these findings suggest that export planning and stabilization policies should explicitly account for global oil price volatility and exchange rate interactions. The proposed VARX framework can therefore serve as a practical analytical tool for policymakers to anticipate short-term export fluctuations and design responsive trade and macroeconomic strategies under external uncertainty.

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