cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota mataram,
Nusa tenggara barat
INDONESIA
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
 53   54   55   56   57 
Combined Truncated Spline and Fourier series in Nonparametric Biresponse Regression: A Case of Agricultural Productivity Husain, Hartina; Aristyarini, Rizki; Rahman, Andi Oxy Raihan Machikami; Rahmi, Nur; Nisardi, Muhammad Rifki
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.v10i2.35319

Abstract

Agriculture plays a strategic role in supporting economic development and food security in Indonesia, particularly in South Sulawesi, one of the country’s primary rice-producing regions. Existing studies on agricultural productivity commonly rely on parametric or single-response models, which are less effective in capturing the nonlinear, locally varying, and interrelated characteristics of agricultural indicators. Addressing this research gap, the present study applies a biresponse nonparametric regression approach that integrates truncated splines and Fourier series to simultaneously model rice productivity and the food security index. This quantitative observational research uses secondary regional agricultural statistics, and the analytical procedure includes formulating the biresponse model, conducting diagnostic checks of key nonparametric assumptions, and estimating parameters using the Weighted Least Squares (WLS) method. Model selection was conducted using the Generalized Cross Validation (GCV) criterion, which indicated that rainfall was better approximated with truncated splines and extension workers with Fourier series. The optimal knot points were obtained at 1207.096 for rice productivity variable and 1207.556 for food security index variable, with one oscillation applied in the Fourier series and one knot for the truncated spline. The results show that the best model was obtained with the smallest Generalized Cross Validation (GCV) value of 21.38, a coefficient of determination of 94.85%, and a Mean Absolute Percentage Error (MAPE) of 9.68%. These results demonstrate the methodological advantage of the combined biresponse nonparametric model in accommodating complex data structures and provide actionable insights for policymakers in optimizing resource allocation, strengthening extension services, and enhancing food security strategies in South Sulawesi.
A Bayesian Structural Causal Modeling Framework for Analyzing Childhood Stunting Factors Sianipar, Celia; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun; Zahra, Septi Nafisa Ulluya; Junianto, Fachira Haneinanda
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.v10i2.35966

Abstract

This quantitative study investigates the causal determinants of childhood stunting using a structured questionnaire as the primary research instrument. The analysis applies Bayesian path modeling to examine how Economic Level influences Child Nutritional Status both directly and indirectly through Children’s Diet. Bayesian estimation is used to obtain stable and reliable parameter values, with convergence checks ensuring model adequacy. The overly technical explanations of MCMC procedures and specific sampling algorithms from the original version are condensed to maintain clarity in an abstract. The results show that Children’s Diet plays a strong mediating role, indicating that economic improvements contribute more substantially to better nutritional outcomes when dietary practices are strengthened. These findings highlight clear policy implications, particularly the need to integrate dietary interventions with economic support programs. Overall, the study demonstrates that Bayesian path analysis provides a rigorous yet flexible approach for evaluating interconnected determinants of child nutrition and contributes evidence-based insights for stunting reduction strategies.
Robust Optimization Model for Green Capacitated Vehicle Routing Problem with Hamiltonian Circuit using the Nearest Neighbor Algorithm Cipta, Hendra; Widyasari, Rina; Dongoran, Raisha Zuhaira
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.v10i2.35430

Abstract

The rapid urban expansion of Medan City has intensified the complexity of municipal waste transportation, where limited fleet capacity, congested road segments, and long travel distances to the Terjun disposal site result in high operational costs and excessive carbon monoxide (CO) emissions. In addition, daily fluctuations in waste volume introduce uncertainty that disrupts routing efficiency and increases the risk of vehicle overload. This study proposes a Robust Optimization based Green Capacitated Vehicle Routing Problem model to minimize transportation cost and CO emissions while maintaining route feasibility under demand uncertainty. The model incorporates a Hamiltonian circuit structure to ensure closed-loop routing and applies the Nearest Neighbor Algorithm (NNA) as a constructive heuristic for generating initial solutions. Compared to commonly used methods such as the Clarke–Wright Savings algorithm, NNA provides faster computational performance, simpler implementation, and more stable feasible routes when integrated with robust capacity constraints. Using real CO emission data from major arterials in Medan, the model was evaluated across multiple uncertainty levels (Γ = 0–6). The results show that the robust model reduces overload risk by up to 12%, lowers total emission cost by approximately 5% relative to the deterministic solution, and produces more environmentally efficient routing decisions even when route distance increases slightly. From an analytical perspective, the RO Green-CVRP framework enables evaluation from operational, environmental, and robustness performance dimensions. This research contributes theoretically to green robust optimization and practically supports the development of adaptive, low-emission waste transportation strategies aligned with Medan’s sustainable urban development goals.
Analysis of Food Inflation in Indonesia using the Nonlinear Autoregressive Distributed Lag Approach Salsabila, Nur; Rahkmawati, Yeni; Muslim, Agus; Rahman, Mizan Ikhlasul
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.v10i2.35352

Abstract

Food Inflation remains one of the most persistent sources of price volatility in Indonesia and poses a significant challenge for macroeconomic stability and household welfare. This study conducts quantitative empirical time series research to examine the asymmetric effects of Money Supply (M2) and Farmers Terms of Trade (FTT) on Food Inflation. The analysis uses monthly data from 2011 to 2023 obtained from Bank Indonesia and Statistics Indonesia and applies the Nonlinear Autoregressive Distributed Lag (NARDL) model, which is appropriate for capturing asymmetry and accommodating variables integrated at different orders. The selection of M2 is based on monetary theory which states that changes in liquidity influence aggregate demand and inflation, while the use of FTT is supported by agricultural and development literature showing that farmers purchasing power affects food production capacity and food price dynamics. The results reveal significant asymmetric effects in both the short and long run. Increases and decreases in M2 both raise Food Inflation, and the stronger effect during declining M2 reflects downward price rigidity and the dominance of quasi money in Indonesia. A decline in FTT significantly increases long run inflation through constraints on agricultural input access and reduced food supply. The findings also confirm inflation persistence. These results imply that liquidity management and policies that strengthen farmer purchasing power are essential to stabilize food prices. The study recommends integrating monetary policy with agricultural support measures to mitigate future food inflation pressures.
Exploring Non-Mathematics Students’ Reasoning in Solving Function Continuity Problems in Calculus Courses Suryanti, Sri; Anyanmwu, Clinton Chidibere
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.v10i2.36864

Abstract

Understanding the concept of function continuity is one of the main conceptual challenges for non-mathematics students in learning calculus, as they tend to rely on algorithmic procedures rather than reasoning conceptually. This study aims to explore and compare the types of mathematical reasoning used by non-mathematics students in solving function continuity problems in basic calculus courses, using Lithner's reasoning framework. Using qualitative descriptive, this study compares two first-year calculus classes from two non-mathematics study programs using Lithner's framework. The research instruments comprised three written assignments on function continuity, developed according to the categories of Imitative Reasoning (IR) and Creative Reasoning (CR), in addition to task-based interviews (think-aloud) conducted to investigate students' cognitive processes. Data were analyzed by categorizing mathematical reasoning into Memorized Reasoning (MR), Algorithmic Reasoning (AR), Local Creative Reasoning (LCR), and Global Creative Reasoning (GCR), accompanied by an inter-rater reliability assessment. The results indicate differences in reasoning patterns between engineering and general education students, especially regarding their propensity to employ imitative reasoning (IR) or creative reasoning (CR) when confronted with continuity-of-function problems. These results offer a significant critique of the utilization of Lithner's framework in the analysis of calculus tasks especially the continuity of functions and propose minor adjustments to enhance the categorization of reasoning, making it more suitable for non-mathematics students.
Development of the MARIBANG Pop-Up Book as a Learning Medium for Seventh-Grade Students at State Junior High School Bulkani, Bulkani; Rahmaniati, Rita Rahma; Safiyah, Nur
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.v10i2.35466

Abstract

This study aimed to develop and evaluate the feasibility of the MARIBANG Pop-Up Book as an innovative learning medium for seventh-grade students at SMPN 2 Sampit. The research employed a Research and Development (R&D) approach using the ADDIE model, which includes the stages of analysis, design, development, implementation, and evaluation. The subjects of this study were 36 seventh-grade students, while the object of the research was the MARIBANG Pop-Up Book learning media. Data were collected through expert validation questionnaires, student and teacher response questionnaires, and learning outcome tests. The data were analyzed using descriptive statistics and N-gain analysis to measure improvements in students’ learning outcomes. The results indicated that the MARIBANG Pop-Up Book demonstrated a very high level of validity based on evaluations from material, media, and language experts. In terms of practicality, both students and teachers gave very positive responses, indicating that the media was easy to use and engaging in classroom learning. Furthermore, the effectiveness of the media was confirmed by a significant increase in students’ learning outcomes, as reflected in the N-gain scores and classical learning completeness. These findings suggest that the MARIBANG Pop-Up Book is a valid, practical, and effective learning medium. This study highlights the potential of pop-up book–based media to enhance student engagement and learning achievement, and provides practical implications for the development of interactive instructional media in junior high school education.
Fuzzy C-Means Clustering of Student Mathematical Communication Skills and Cognitive Performance and Its Association with Learning Models Pambudi, Dhidhi; Nakano, Sachiko; Damayanti, Alfina
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.v10i2.35522

Abstract

This study applies Educational Data Mining (EDM) to examine how students’ mathematical communication skills and cognitive styles interact under different instructional contexts. A quantitative research that applies quasi-experimental design combined with EDM was employed involving 64 seventh-grade students at SMP Negeri 2 Jaten, divided into Learning Cycle 7E (LC7e) and Direct Instruction (DI) groups. The research instruments included a validated essay test for mathematical communication and the Group Embedded Figures Test (GEFT). Data were analyzed using the Fuzzy C-Means (FCM) algorithm to partition students into distinct clusters based on their cognitive-communicative attributes. The analysis resulted in a stable five-cluster model, representing progressive levels of cognitive–communicative integration. The model shows that cognitive profile predominantly creates cluster structure, whereas the Learning Cycle 7E (LC7E) model exerts a moderating influence. Students taught through LC7E were more concentrated in higher-performing clusters than those in DI classrooms. Furthermore, Field-Independent (FI) learners tended to achieve the highest communicative profiles, yet Field-Dependent (FD) learners also benefited meaningfully from LC7E activities that emphasized exploration and reflection. These results demonstrate that the LC7E model supports cognitive and communicative development across the learner spectrum, with differentiated gains linked to cognitive style. These findings highlight the utility of EDM in capturing student heterogeneity and provide a basis for educators to design adaptive learning strategies that accommodate diverse cognitive characteristics. 
Estimation of Stunting and Wasting Prevalence in Southern Part of Sumatra Using Nadaraya-Watson Kernel and Penalized Spline Oktarina, Cinta Rizki; Nugroho, Sigit; Sriliana, Idhia
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.v10i2.36177

Abstract

This study aims to estimate the prevalence of stunting and wasting in the southern region of Sumatra using a bivariate nonparametric regression framework based on the Nadaraya-Watson Kernel and Penalized Spline estimators with Penalized Weighted Least Squares (PWLS). The analysis utilizes data from the 2023 Indonesian Toddler Nutrition Survey, comprising 60 regencies and cities across five provinces, namely Bengkulu, South Sumatra, Lampung, Jambi, and Bangka Belitung. By jointly modeling stunting and wasting as correlated response variables, this study seeks not only to compare methodological performance, but also to provide empirical insights into the nonlinear patterns underlying child nutritional outcomes influenced by maternal-child health and socioeconomic conditions. Model performance was evaluated using the Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and the coefficient of determination (R²). The empirical results indicate that the Nadaraya-Watson Kernel estimator outperforms the Penalized Spline approach, yielding a substantially lower prediction error (MSE = 0.0008), high goodness-of-fit values (R² of 99.98% for stunting and 99.95% for wasting), and relatively small RMSE values of 0.038 and 0.017, respectively. These findings suggest that the kernel-based estimator provides stable and accurate predictions within the data structure considered, particularly in capturing complex nonlinear relationships between predictors and nutritional outcomes. Furthermore, the results reveal that the effects of health-related and socioeconomic factors vary across different prevalence levels, underscoring the importance of nonparametric methods in accommodating heterogeneous and nonlinear response patterns. In line with previous evidence emphasizing integrated, multisectoral approaches to child nutrition improvement, the findings highlight the relevance of combining health interventions with broader social protection strategies. Nevertheless, the interpretation of results is subject to methodological caution, given the limited sample size and the aggregated nature of the data. Overall, this study demonstrates the potential of bivariate nonparametric regression as a complementary analytical tool for health data analysis and evidence-based policy formulation related to stunting and wasting reduction.
Assessment of Dietary Intervention Effects on Food Intake in Mus musculus using Repeated Measures ANOVA Suliyanto, Suliyanto; Amelia, Dita; Arrofah, Aini Divayanti; Alisiah, Rindiani Ahmada; Anida, Nuzulia; Maulidya, Utsna Rosalin
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.v9i4.32467

Abstract

The prevalence of type 2 diabetes, metabolic syndrome, along with obesity that causes disturbances in the body's metabolic processes are the main triggers of chronic liver disease or in scientific language called Non-Alcoholic Fatty Liver Disease (NAFLD), getting out of control. This makes managing this disease an increasingly serious global health challenge. One of the main factors influencing this condition is a high-fat diet and an unhealthy lifestyle. Therefore, evaluation of high-fat diet programs on metabolic parameters such as food intake patterns is important as a preventive measure. This study aims to analyze the differences in food intake levels with seven different types of dietary treatments for 28 days, which were tested on mice (Mus musculus) which have physiological and biochemical characteristics that almost resemble humans. The method used was analysis of variance (ANOVA) for longitudinal data to evaluate the dynamics of food consumption across diet groups and observation periods. The results showed that the type of dietary treatment significantly influenced food intake patterns over time, indicating that diet composition plays a crucial role in shaping eating behavior. These findings highlight the importance of both diet type and treatment duration in influencing consumption patterns. However, since this study has not yet identified the most effective dietary regimen, future research is recommended to investigate diet types with high variability, while considering additional factors such as age, sex, and physiological characteristics, as well as extending the observation period to better understand long-term impacts.
Comparing Areal and Grid Supports for Fire Radiative Power within a GSTAR (p; λ₁, λ₂, …, λₚ) Framework Zuleha, Zuleha; Huda, Nur'ainul Miftahul; Imro'ah, Nurfitri
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.v10i2.36663

Abstract

Forest fire phenomena exhibit spatial interdependence and temporal dependence, necessitating a spatiotemporal modeling approach to capture the dynamics of fire occurrences. This study models and predicts forest fires using Fire Radiative Power (FRP) as an indicator of fire intensity. Weekly hotspot data from NASA FIRMS, covering the period from July 2024 to August 2025, were analyzed using the Generalized Space-Time Autoregressive (GSTAR) model. The modeling was conducted by considering various forms of spatial partitioning and spatial weight matrices to capture inter-location dependencies. Four spatial partitioning schemes were employed: areal, and grids of 0.50°×0.50°, 1.00°×1.00°, and 1.25°×1.25°; alongside three spatial weight matrices: Queen Contiguity, Rook Contiguity, and Inverse Distance Weighting (IDW). The temporal order and spatial lag were determined using STACF and STPACF plots. From these combinations, 42 GSTAR models were constructed and evaluated through a three-stage process of estimation and residual diagnostic testing. The results indicate that the GSTAR (1;1) model with a 1.00°×1.00° grid and Rook Contiguity and IDW spatial weight matrices is the best-performing model. This model satisfies the white noise assumption and yields a Root Mean Square Error (RMSE) of 6.866, which is the smallest among all evaluated models. The estimates indicate that fires at a given location are influenced by prior conditions and spatial interactions with surrounding areas, suggesting that the GSTAR model supports spatiotemporal monitoring and early warning systems.

Page 56 of 57 | Total Record : 565

 53   54   55   56   57 

Filter by Year

2017 2026


Reset
Filter By Issues
All Issue Vol 10, No 2 (2026): April Vol 10, No 1 (2026): January Vol 9, No 4 (2025): October Vol 9, No 3 (2025): July Vol 9, No 2 (2025): April Vol 9, No 1 (2025): January Vol 8, No 4 (2024): October Vol 8, No 3 (2024): July Vol 8, No 2 (2024): April Vol 8, No 1 (2024): January Vol 7, No 4 (2023): October Vol 7, No 3 (2023): July Vol 7, No 2 (2023): April Vol 7, No 1 (2023): January Vol 6, No 4 (2022): October Vol 6, No 3 (2022): July Vol 6, No 2 (2022): April Vol 6, No 1 (2022): January Vol 5, No 2 (2021): October Vol 5, No 1 (2021): April Vol 4, No 2 (2020): October Vol 4, No 1 (2020): April Vol 3, No 2 (2019): October Vol 3, No 1 (2019): April Vol 2, No 2 (2018): October Vol 2, No 1 (2018): April Vol 1, No 1 (2017): October More Issue