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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 27 Documents
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Search results for , issue "Vol 9, No 3 (2025): July" : 27 Documents clear
Mathematical Modeling and Integration of Machine Learning-Based Prediction System on E-Learning Platform to Improve Students' Academic Performance Farida, Anisatul; Atina, Vihi; Suwandi, Djatmiko
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.30994

Abstract

The purpose of this study was to develop and integrate a student academic performance prediction system into an e-learning platform using a mathematical modelling approach combined with machine learning algorithms. The method employed was Research and Development (R&D), encompassing stages of needs analysis, mathematical modelling, development of a machine learning-based prediction system, and implementation and evaluation. The study was conducted at Duta Bangsa University, Surakarta, involving 100 students from the Informatics Engineering study program. Data were collected through the e-learning platform, covering student activity logs such as access frequency, quiz scores, assignment completion time, and forum participation. This behavioral data was then analyzed using supervised learning algorithms, namely logistic regression and decision tree, to build a predictive model for academic performance. The resulting predictive system was integrated into the e-learning platform to deliver risk notifications and adaptive learning material recommendations automatically. To measure the improvement in academic performance, a validated academic achievement test was administered as both a pre-test and a post-test to the experimental group. This test consisted of multiple-choice and short-answer items aligned with the course learning objectives. The results showed that the decision tree model achieved a prediction accuracy of 87.4%, while logistic regression reached 81.2%. Evaluation of the system’s effectiveness using the pre-test and post-test scores revealed a significant increase in students’ academic performance. Statistical analysis with a paired t-test yielded a significance level of p < 0.001, indicating that the adaptive prediction system effectively supports more personalized and impactful learning. This study contributes to the advancement of machine learning-based prediction systems in e-learning by designing and implementing a model that leverages real student activity data. The system enables early detection of academic risks and provides automated, adaptive content recommendations, thus fostering personalized and data-driven learning in higher education. Its practical implementation helps students identify learning weaknesses promptly and receive appropriate supporting materials immediately, promoting proactive and self-regulated learning behavior. 
Mathematics in Transition: Assessing the Impact of Curriculum Changes on Student Performance Metrics Siregar, Juni Satria; Abdullah, Sarini
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.30514

Abstract

Curriculum changes in higher education, especially in mathematics, are intended to align academic content with scientific advancements and evolving workforce demands; however, such reforms often bring unintended academic challenges for students. In Indonesia, recent changes in the 2016, 2020, and 2024 mathematics curricula introduced shifts in course credit allocations, course learning outcomes (CLOs), material scope, instructional methods, and evaluation systems. This study specifically aims to evaluate the impact of these curriculum changes on student academic performance across five core mathematics courses: Introduction to Data Science, Calculus 1, Calculus 2, Linear Algebra, and Mathematical Statistics. Employing a quantitative, exploratory approach, the research analyses academic records from 586 students using descriptive statistics and visualisation techniques such as boxplots and bar-line charts. The findings reveal fluctuating average grades and a general decline in pass rates, particularly under the 2024 curriculum, which introduced more complex CLOs, deeper content coverage, and application-oriented assessments. These results highlight the urgent need to balance curriculum innovation with student readiness and provide valuable insights for curriculum development and educational policy planning. 
Modeling the Human Development Index of the West Nusa Tenggara Province using Panel Data Regression Astuti, Alfira Mulya; Islamiyah, Pizatul; Choir, Achmad Syahrul; Setambah, Mohd Afifi Bahurudin
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.31055

Abstract

The human development index is the primary indicator used to measure the level of success of human development. It is important to study because the human development index can provide a more comprehensive picture of a region or country's progress in improving its people's quality of life and guide the government in designing more effective development policies, identifying social gaps, and directing efforts to improve the quality of life of society as a whole. This research aims to identify the most significant component of the HDI calculation through the application of standardized coefficients and to analyze the influence of the number of poor people on the human development index in West Nusa Tenggara (NTB) province during 2010-2023 period. This research is quantitative in essence. The independent variables were life expectancy at birth, expected years of schooling, mean years of schooling, adjusted per capita expenditure, and number of poor people. The individual observation units in this study were 10 districts/cities in the NTB province. Data were sourced from Badan Pusat Statistik (BPS) NTB Province and analyzed using the panel regression method. The results of model selection show that the Fixed Effect Model is the best model for modeling the human development index in NTB province. The adjusted per capita expenditure had the greatest impact on the human development index of NTB Province in 2010–2023. The expected years of schooling was the variable that contributed the least to the entire components of the HDI in NTB province. The number of poor people had a significant effect on the human development index of NTB province from 2010 to 2023.  
Regression Model as a Tool for Evaluating Mangrove Degradation in Lembar Bay, West Lombok Johari, Harry Irawan; Rahmat, Nurul Isnaeni; Sukuryadi, Sukuryadi
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.31664

Abstract

The mangrove ecosystem plays a vital role in maintaining ecological balance, supporting economic livelihoods, and sustaining socio-cultural functions. However, in Lembar Bay, West Lombok Regency, this ecosystem is increasingly threatened by human activities, particularly land conversion for aquaculture. These activities have led to significant ecological degradation, biodiversity loss, and weakened coastal protection. This study aims to analyze the key factors influencing mangrove degradation and to evaluate the effectiveness of regression models in assessing the contribution of these factors. A quantitative research approach was employed, with data collected through structured questionnaires distributed to 45 purposively selected community members considered knowledgeable about local mangrove conditions. The study also integrated field measurements and satellite imagery interpretation to assess mangrove density, biodiversity, and related environmental variables. Multiple linear regression analysis was used to examine the relationship between anthropogenic pressures such as land clearing, water quality, and rehabilitation efforts and indicators of mangrove degradation, namely biodiversity and mangrove density. Regression analysis showed a strong and significant effect of water quality on both mangrove biodiversity and density. The biodiversity regression model produced a correlation coefficient (R) of 0.820 and a determination coefficient (R²) of 0.673, indicating that 67.3% of the variation in biodiversity can be explained by the analyzed factors. Similarly, the mangrove density model yielded an R of 0.800 and R² of 0.640, meaning that 64.0% of the variation in mangrove density was explained. F-test results confirmed that both models were statistically significant (p-value < 0.05). The findings indicate that aquaculture expansion and land use changes are the most critical contributors to mangrove degradation. These pressures directly impair the physical condition of the ecosystem, leading to biodiversity loss and increased vulnerability to coastal hazards. Based on community perceptions, most respondents supported stricter sanctions against mangrove destruction and agreed that mangrove conservation improves the quality of life. Therefore, this study recommends that policymakers and local governments strengthen their roles in monitoring and controlling land use changes, enforcing environmental regulations, and promoting environmental education programs. It is also essential to enhance community participation in mangrove rehabilitation through inclusive, knowledge-based initiatives and integrate scientific evidence into participatory coastal spatial planning. This study contributes to the scientific literature on mangrove conservation by demonstrating the empirical effectiveness of regression analysis in identifying and quantifying human-induced pressures affecting mangrove ecosystems.
Analysis of Students' Academic Performance in the Department of Mathematics Based on Semester GPA Dynamics: A Case Study of the 2017–2024 Cohorts Rahmat, Shafa Khadijah; Abdullah, Sarini
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.30287

Abstract

This quantitative exploratory study investigates changes in students' Semester Grade Point Average (GPA) and their relationship with graduation status and study duration. It uses academic records from the Department of Mathematics at a public university in Indonesia for cohorts from 2017 to 2024. The study addresses concerns raised after the COVID-19 pandemic, which may have disrupted academic progression and altered the predictive power of initial GPA on graduation outcomes a gap not sufficiently explored in existing literature. Data were collected directly from the university's academic database, ensuring accuracy and consistency without relying on self-reported surveys. Descriptive statistical methods and visual analytics (e.g., line charts, boxplots, and scatter plots) were applied to uncover trends and patterns. Results show that earlier cohorts (2017–2020) have high graduation rates (82.7%–94.4%), while the 2019 cohort recorded the highest dropout rate (11.1%). Newer cohorts (2021–2024) predominantly consist of students still enrolled, though some early graduations and dropouts occurred. A positive correlation was found between first-semester GPA and graduation success, yet the pandemic likely introduced new variables that affect academic outcomes. These findings provide actionable insights for academic policy and support the development of early detection systems to identify students at academic risk.
Analysis of Online Game Addiction with Crowley-Martin Incident Rate Function Syata, Ilham; Halim, St. Nur Humairah
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.31641

Abstract

This study aims to build and analyze a new mathematical model of online game addiction with the Crowley-Martin type incidence rate function approach. This research is categorized as a theoretical-quantitative study using mathematical modeling as its primary approach. The research instruments used include symbolic computation, simulation software, and parameter estimation techniques derived from literature. Stability analysis is conducted through Jacobian linearization, the Routh-Hurwitz criterion, and the Next Generation Matrix method to calculate the basic reproduction number. Optimal control is formulated using Pontryagin’s Minimum Principle with two strategies: parental guidance and counseling therapy. Data analysis combines analytical techniques in stability and control theory with numerical simulations to evaluate the system. The results show that: The addiction-free fixed point T_0 is locally asymptotically stable if R_0<1, the addiction fixed point T^*is locally asymptotically stable if R_0>1. Numerical simulations demonstrate that combined control strategies effectively reduce the number of exposed and addicted individuals.
Survival Time Analysis of Multiple Myeloma Patients using Type 1 Censored Exponential Distribution Parameter Estimation Wahyu Subekti, Cahya Arsyika; Nilasari, Inas; Syarif, Devi Mufidah; Syahzaqi, Idrus; Kurniawan, Ardi
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 3 (2025): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i3.32179

Abstract

Multiple myeloma is a type of blood cancer that attacks plasma cells in the bone marrow and affects the immune system. This study analyzes the survival time of patients with multiple myeloma using Type 1 censored exponential distributed parameter estimation. The data, consisting of 47 patients (35 uncensored and 12 censored), were tested for exponential distribution fit using the Anderson-Darling test, yielding a p-value of 0.495, confirming the suitability of the exponential model. The maximum likelihood estimation method was applied, resulting in a parameter estimate (θ ̂) of approximately 54.028 days, representing the mean survival time. Hypothesis testing and confidence intervals were conducted, with the 95% confidence interval for θ_0 ranging between 32 and 53 days. The findings suggest that the exponential distribution effectively models the survival data, providing insights into patient survival trends and supporting clinical decision-making.

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