JTAM (Jurnal Teori dan Aplikasi Matematika)
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.
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<![CDATA[Forecasting the Number of Dropout Student in Indonesia using ARIMA Model ]]>
<![CDATA[Az-Zahra, Aisyah Dhifa]]>;
<![CDATA[Fajriati, Luthfia Azzahra]]>;
<![CDATA[Sari, Sherlyana Devita]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.31625
<![CDATA[The high rate of dropout students in Indonesia remains a matter of considerable concern, as it erodes the quality of education and hinders the long-term development of human capital. The government of Indonesia has endeavored to address the issue of high dropout rates among students by implementing a range of initiatives. To demonstrate the effectiveness of this program, forecasting is necessary to measure and predict its outcomes. The purpose of this study is to utilize a time series approach, specifically the Autoregressive Integrated Moving Average (ARIMA) model, to predict the number of dropout students in the forthcoming years. This study employs a quantitative analysis using secondary data obtained from Statistics Indonesia (BPS) for the period 1970-2023. The ARIMA method is a statistical technique used to determine the most suitable forecasting model from historical data. This method has gained widespread popularity in the field of time series analysis due to its ability to manage non-stationary data effectively. The result shows that ARIMA (0,2,1) has the smallest AIC and meets the significant criteria model, also having the lowest MAPE value of 1.9%, indicating excellent forecasting accuracy. The plot of the result indicates a downward trend in the number of dropout students over the coming years. This downward trend aligns with the timeline of government interventions, suggesting a potential causal relationship between the implementation of educational support programs and the declining dropout rates. Thus, the prediction supports the effectiveness of these initiatives in mitigating dropout student in Indonesia.]]>
<![CDATA[Exploring Technology, Role, and Components of Computational Thinking in Mathematics Learning: A Systematic Literature Review ]]>
<![CDATA[Andriatna, Riki]]>;
<![CDATA[Turmudi, Turmudi]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.30440
<![CDATA[Computational thinking as a 21st century skill has attracted the attention of researchers, including in mathematics education. This research identifies the use of technology, the role and components of computational thinking in mathematics learning. This study uses a sysematic literature review with procedure consisting of planning the review, conducting the review, and reporting the review. The articles used came from the Scopus database in the 2010-2024 publication time range. Based on the PRISMA protocol involving criteria such as type of publication, language, field of study, publication stage, and accessibility to the article, 11 articles were obtained with the most research conducted in Spain. The research conducted involved many students and teachers as the object of research, including pre-service teachers. The reviewed studies also revealed that most of the computational thinking research used qualitative methods where the role of computational thinking in the research was mostly as a process or activity or tools used in learning, either using technological devices or in the form of unplugged activites. In addition, the results of the review of selected articles also reveal that the components of decomposition, pattern recognition, abstraction, and algorithm are still dominating as the main components studied in computational thinking.]]>
<![CDATA[Modeling Spatio-Temporal Precipitation Patterns in East Kalimantan using Space-Time Kriging and Median Polish-Based Spatio-Temporal Kriging ]]>
<![CDATA[Jannah, Friendtika Miftaqul]]>;
<![CDATA[Fitriani, Rahma]]>;
<![CDATA[Pramoedyo, Henny]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.30642
<![CDATA[Precipitation variability presents significant challenges for disaster risk reduction and water resource management, particularly in flood and drought-prone regions such as East Kalimantan. This study aims to develop and evaluate two statistical approaches for spatio-temporal precipitation modeling: spatio-temporal kriging (ST-Kriging) and spatio-temporal median polish kriging (ST-MPK). Using monthly precipitation data obtained from seven observation stations provided by BMKG and BPS for the period 2021 to 2023, both models were assessed using performance metrics. ST-Kriging employed a simple sum-metric semivariogram model that combines exponential spatial and Gaussian temporal components. This model achieved an RMSE of 84.05, MAE of 69.95, and MAPE of 52.67%. Meanwhile, ST-MPK model, incorporating robust median polish decomposition and ST-Kriging of residuals, produced a lower MAPE of 44.83% with higher RMSE (122.44) and MAE (91.35). This suggests that while ST-Kriging offers better absolute error performance, ST-MPK provides greater relative accuracy and improved robustness to outliers, critical advantages for modeling precipitation in regions undergoing environmental shifts, where anomalies and extremes are increasingly common. These findings highlight ST-MPK’s potential to produce more reliable forecasts under irregular precipitation conditions, supporting early warning systems and informed water resource planning. Scientifically, this research contributes a robust modeling framework suitable for data-scarce and outlier-prone contexts. Practically, it can aid policymakers in designing adaptive flood mitigation strategies and sustainable water management policies tailored to the evolving climate realities of East Kalimantan.]]>
<![CDATA[Analysis Dynamics Model Predator-Prey with Holling Type III Response Function and Anti-Predator Behavior ]]>
<![CDATA[Pratama, Rian Ade]]>;
<![CDATA[Suryani, Dessy Rizki]]>;
<![CDATA[Ruslau, Maria F. V.]]>;
<![CDATA[Meirista, Etriana]]>;
<![CDATA[Nurhayati, Nurhayati]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.31533
<![CDATA[Understanding predator-prey dynamics is essential for maintaining ecological balance and biodiversity. Classical models often fail to capture complex biological behaviors such as prey defense mechanisms and nonlinear predation effects, which are vital for accurately describing real ecosystems. In light of this, there is a growing need to incorporate behavioral and functional complexity into mathematical models to better understand species interactions and their long-term ecological outcomes. This study aims to develop and analyze a predator-prey model that integrates two key ecological features: a Holling type III functional response and the anti-predator behavior exhibited by prey. The model assumes a habitat with limited carrying capacity to reflect environmental constraints. We formulate a nonlinear system of differential equations representing the interaction between prey and predator populations. The model is examined analytically by identifying equilibrium points and analyzing their local stability using the Routh-Hurwitz criteria. A literature-based theoretical analysis is supplemented with numerical simulations to validate and illustrate population dynamics. The model exhibits three equilibrium points: a trivial solution (extinction), a predator-free equilibrium, and a non-trivial saddle point representing coexistence. The non-trivial equilibrium best reflects ecological reality, indicating stable coexistence where prey consumption is balanced by reproduction, and predator mortality aligns with energy intake. Numerical simulations show that prey populations initially grow rapidly, then decline as they reach carrying capacity, while predator populations grow after a time lag and eventually stabilize. The results are further supported by the eigenvalue analysis, confirming local asymptotic stability. The proposed model realistically captures predator-prey dynamics, demonstrating that the inclusion of anti-predator behavior and a Holling type III response significantly affects population trajectories and system stability. This framework provides a more ecologically valid approach for studying long-term species coexistence and highlights the importance of incorporating behavioral responses in ecological modeling.]]>
<![CDATA[The use of Traditional Games to Increase Interest in Learning Multiplication in Class 4 Primary School Students in the City of Bandung ]]>
<![CDATA[Pratiwi, Intan Aprilianti]]>;
<![CDATA[Dallyono, Ruswan]]>;
<![CDATA[Kurniawan, Dede Trie]]>;
<![CDATA[Yuniarti, Yeni]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.29721
<![CDATA[Learning multiplication is challenging for fourth-graders of an elementary school in Bandung in terms of the subject when they learn it at school. Some students exhibit no curiosity in mathematics, despite the fact that curiosity is a significant part of learning effectively. This study aims to examine students’ responses on the use of traditional games as a way to grip the minds of pupils in learning multiplication with creative and constructive methods. With the use of the case study approach, the findings are presented through a descriptive analysis through a number of tables which are made from the responses to the questionnaires. The subjects were 30 fourth-grade students. The data were collected through questionnaires and documents with the help of the descriptive statistical methods for the analysis to represent the results in numerical and tabular formats. The conclusion drawn from the research is that the dakon game, the most traditional one, as a learning medium was perceived to be able to bring a remarkable change in students' interest to learn multiplication.]]>
<![CDATA[Naïve Bayes Algorithm: Analysis of Student Group Assignment Project Patterns in Mathematics Learning ]]>
<![CDATA[Dewi, Wardhani Utami]]>;
<![CDATA[Vahlia, Ira]]>;
<![CDATA[Linuhung, Nego]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.30459
<![CDATA[Effective collaboration in mathematics learning is essential for developing students' critical thinking and problem-solving skills; however, identifying patterns that lead to successful group collaboration remains challenging. This study aims explicitly to identify and classify the patterns of student group assignment completion in the Logic and Sets course using the Naïve Bayes algorithm. Survey data from 65 mathematics education students were analyzed using a quantitative approach and machine learning techniques. Attributes such as group size, task completion time, participation, contribution strategies, and communication effectiveness were collected via structured questionnaires. Data analysis involved preprocessing, model training using Naïve Bayes, and validation through accuracy and posterior probability analysis. Results indicated that the Naïve Bayes model accurately distinguished groups with very good (A) and fairly good (B) performance, achieving 84.62% accuracy. Groups achieving an A grade typically featured balanced participation and open communication strategies, whereas groups graded B exhibited uneven participation and passive members. This research significantly contributes by demonstrating how data-driven predictive analytics can support instructors in monitoring and enhancing collaborative learning processes in mathematics courses. Future research could further refine predictive accuracy by incorporating additional factors such as leadership style and collaborative technologies, potentially integrating the model into learning management systems for real-time evaluation and intervention.]]>
<![CDATA[Mathematical Semiotics in Primary Learning: Helping Prospective Teachers Understand Mathematical Representations ]]>
<![CDATA[Purwasih, Ratni]]>;
<![CDATA[Irawan, Edi]]>;
<![CDATA[Minasyan, Sona]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.30835
<![CDATA[Mathematics learning in elementary schools is often faced with the challenge of bridging abstract concepts with participants' concrete experiences. One of the reasons is the difficulty in understanding and using mathematical signs and symbols appropriately. Semiotic representation of mathematics, which involves symbols, diagrams and notations as visual and conceptual aids, is an important approach in overcoming these challenges. This study aims to explore the ability of prospective elementary school teachers to understand and use semiotic representations of mathematics, especially in the context of number patterns. A qualitative approach with a hermeneutic phenomenological design was chosen to understand prospective teachers' experiences, views, and thought processes in interpreting and using mathematical symbols. The researcher used written tests and semi-structured interviews as data collection techniques to explore the semiotic representations used in mathematical problem solving. The participants were grouped based on the results of the initial ability test, and six of them were selected as research subjects. Data analysis used the Interpretive Phenomenology Analysis (IPA) method with the help of NVivo 14 Plus software, which allows researchers to systematically manage and analyze qualitative data. The results of this study are expected to provide insight into prospective teachers' understanding of symbolic representation in mathematics learning and the challenges they face, which can be the basis for designing more effective learning strategies in the context of mathematics education in primary schools. Using a descriptive qualitative approach, data were obtained through observation and analysis of problem solving activities involving symbolic and visual representations. The results of the study are expected to provide insight into the importance of semiotic training in prospective teacher education, so that they are able to convey mathematical concepts meaningfully and contextually.]]>
<![CDATA[A Comparison of Multivariate Adaptive Regression Spline and Spline Nonparametric Regression on Life Expectancy in Indonesia ]]>
<![CDATA[Pratama, Bagas Shata]]>;
<![CDATA[Suliyanto, Suliyanto]]>;
<![CDATA[Mardianto, M. Fariz Fadillah]]>;
<![CDATA[Sediono, Sediono]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.29413
<![CDATA[Life expectancy is a key indicator of a population’s overall health and well-being. It also reflects the effectiveness of government efforts in improving public welfare. Despite various initiatives by both the government and society to improve life expectancy in Indonesia, significant disparities remain. This quantitative study aims to support these efforts by analyzing factors influencing life expectancy in Indonesia using data from the Indonesian Central Agency of Statistics (BPS) in 2023. A comparative analysis was conducted using two methods: Multivariate Adaptive Regression Spline (MARS) and Spline Nonparametric Regression. The results show that the MARS model outperforms the Spline model, achieving a lower Mean Squared Error (MSE) of 1.183 and a higher R-Square of 82.7%. Key variables significantly influencing life expectancy include access to decent housing, access to safe drinking water, per capita expenditure, and the Gini ratio. The findings not only confirm the presence of complex interactions among predictor variables effectively captured by the MARS method, but also contribute to the existing literature by emphasizing the importance of socioeconomic determinants in health outcomes. From a policy perspective, the results suggest that government strategies should prioritize improving access to basic needs and reducing inequality. These insights can guide targeted, data-driven interventions aimed at enhancing life expectancy in Indonesia.]]>
<![CDATA[A Spatiotemporal Analysis of Humidity Pattern in Bali using Space-Time Kriging with Seasonal Drift ]]>
<![CDATA[Nugroho, Salma Fitri]]>;
<![CDATA[Fitriani, Rahma]]>;
<![CDATA[Iriany, Atiek]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.30874
<![CDATA[Climate plays a vital role in framing the characteristics of tourist activity. Humidity reflects the amount of moisture in the air relative to the maximum it can hold at a specific temperature, it has a direct influences on perceived comfort levels. Bali, one of the most popular destinations renowned for its breathtaking natural beauty and varied landscapes. However, this island is currently served by only four climate observation stations which are insufficient to capture the humidity across the island. Therefore, this research aims to model humidity levels in Bali based on four observed locations at 2019-2023 using the space-time kriging with seasonal drift and predict humidity at unobserved locations. This approach was choosen due to the strong seasonal pattern exhibited in climate data, which leading to non-stationary. The space-time kriging method is applied to the residuals. The most effective model identified was the exponential-exponential-Gaussian (Exp-Exp-Gau) model using a sum-metric structure. This model provided the lowest RMSE of 2.1442. Humidity contour maps suggest a gradual decline in humidity levels over time across Bali. This trend may have significant impacts for both environmental quality and the tourism sector. Lower humidity levels could lead to increased discomfort for tourists and potentially reduce the attractiveness of the destination. Theoretically, the development of the kriging model enhances the accuracy of predictions, as shows by the low RMSE. Practically, these findings emphasize the importance of integrating climate considerations into sustainable tourism planning and management strategies based on the humidity information.]]>
<![CDATA[Robust Optimization Model Analysis for Online Sentiment Issues on Shopee using Support Vector Machine ]]>
<![CDATA[Dongoran, Raisha Zuhaira]]>;
<![CDATA[Cipta, Hendra]]>
<![CDATA[ JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Mataram ]]>
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DOI: 10.31764/jtam.v9i3.31555
<![CDATA[In the digital economy era, e-commerce platforms like Shopee receive thousands of user reviews daily, which significantly influence customer perceptions and purchasing decisions. However, sentiment analysis of such reviews remains challenging due to the presence of noise, uncertainty, and dynamic data changes. This quantitative research aims to develop a more reliable sentiment classification model by integrating a Lexicon-Based labeling approach and Support Vector Machine (SVM) classification with a Robust Optimization framework. The labeling process uses a sentiment lexicon dictionary that assigns polarity values to words, classifying texts into positive, negative, or neutral categories. The classification process utilizes SVM to evaluate sentiment prediction based on key performance metrics: Accuracy, Precision, Recall, and F1-score. These performance metrics are treated as uncertain parameters in the optimization phase. The main contribution of this study is the formulation of a robust optimization model for sentiment analysis weighting problems, transforming a multi-criteria objective into a single-objective utility function. By applying polyhedral uncertainty modeling, the robust counterpart formulation accounts for worst-case scenarios in model evaluation. Numerical experiments using Python in Google Colab show that while the deterministic model achieves a higher performance score (0.865), the robust model yields a slightly lower score (0.825) but offers better stability under uncertainty. These results imply that robust optimization can enhance the reliability of sentiment classification systems in real-world e-commerce applications, providing more trustworthy insights for businesses in managing consumer feedback.]]>
