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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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Mapping Food Insecurity: Spatial Modelling of Undernourishment Prevalence in Indonesia using Geographically Weighted Regression Saifudin, Toha; Chamidah, Nur; Ramadhina, Fidela Sahda Ilona; Al Hasri, Ilham Maulana; Trisa, Nadya Lovita Hana; Valida, Hanny; Setyawan, Muhammad Daffa Bintang
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32063

Abstract

Undernourishment is a major global issue, with significant impact observed in Indonesia. A method of assessing the prevalence of energy deficiency resulting from inadequate nutrition is through the Prevalence of Undernourishment (PoU) index. From 2019 to 2022, Indonesia's PoU increased gradually, reaching 10.21% in 2022, indicating growing undernourishment and unstable food availability. This study aims to utilize Geographically Weighted Regression (GWR) to identify and analyze the factors contributing to undernourishment. The data were obtained from the Central Bureau of Statistics (BPS) in 2024, covering 38 provinces in Indonesia. This study examined six factors: per capita spending, access to potable water, mean years of schooling, access to adequate sanitation, college participation rate, and mean food expenditure. The findings show that the GWR model outperformed the conventional model, demonstrating greater explanatory power by accounting for 96.1% of the spatial variation in undernourishment and achieving the lowest AIC value of 176.7052. These findings highlight the need for region-specific food security policies, particularly in eastern Indonesia. The results can inform targeted government interventions and guide future spatial econometric research on food security.
Monitoring PH of Shrimp Water using Progressive Max Chart Rosyadi, Niam; Syahzaqi, Idrus; Ibrahim, Auron Saka; Sihotang, Raja Van Den Bosch; Ahsan, Muhammad; Mashuri, Muhammad
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.30255

Abstract

Control charts aim to reduce variability in the process and monitor for out-of- control processes. So far, the process of monitoring quality is usually carried out partially, namely monitoring the mean process and process variability. This approach is less effective and time-consuming because two separate charts must be created simultaneously. One alternative is to analyze both parameters simultaneously, such as through the Progressive Max Chart method (Mixed-Methods Research: Quantitative and Applied). The Progressive Max Chart is a control chart designed for monitoring both the mean and variability by considering the case of subgroup observations. This study uses a quantitative approach, combining primary data collection and simulations to generate findings through statistical analysis and quantifiable measurements. The purpose of this research is to compare methods such as the Progressive Max Chart, EWMA-Max, and Max Chart. The analysis results show that the Progressive Max Chart method performs better than the Max Chart and EWMA- Max Chart, both in terms of mean, variance, and mean-variance detection, for small shifts and large shifts. The control chart performance results provide optimal outcomes for monitoring out-of-control signals at subgroup sizes of n = 2, 3, 5. This is characterized by ARL₁ values that approach 1 more quickly. This method is applied to pH data from vannamei shrimp pond water located in Madura. The Progressive Max Chart method provides optimal results by maximizing the detection of in-control signals. Additionally, it is tested on synthesized data and demonstrates optimal performance in detecting both small and large shifts in mean, variance, and mean-variance.
Creative Geometry through Roof Modeling: Enhancing Angle Understanding via Deep Learning Herliana, Puspa; Hermawan, Hendry; Sulistiyana, Sulistiyana; Aslamiah, Aslamiah; Suriansyah, Ahmad
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.33710

Abstract

This study aimed to evaluate the effectiveness of deep learning-based geometry instruction using miniature roof construction in improving students’ understanding of angles. A quasi-experimental design was conducted at SMPN 1 Kotabaru with 64 seventh-grade students divided into experimental and control groups. The experimental group participated in eight sessions of project-based learning that integrated contextual modeling and collaborative exploration, while the control group received conventional textbook-based instruction. Students’ comprehension of angle concepts including classification, measurement, and application was assessed using a validated geometry test and structured reflection journals. The results showed that students in the experimental group demonstrated significantly greater improvement in angle understanding compared to the control group. Statistical analysis confirmed the effectiveness of the intervention, with a large performance gap favoring the experimental group. These findings suggest that deep learning strategies, when combined with hands-on modeling and contextual relevance, can substantially enhance conceptual mastery in geometry education. 
Interpolation of Fire Radiative Power in West Kalimantan using Ordinary Kriging Fitriyana, Gita; Imro'ah, Nurfitri; Huda, Nur'ainul Miftahul; Zuleha, Zuleha
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32643

Abstract

Forest fires are recurring environmental disasters with severe ecological and economic impacts, particularly in regions like West Kalimantan. One of the key indicators used to measure fire intensity is Fire Radiative Power (FRP). Accurate spatial prediction of FRP is essential to support early warning systems and mitigation strategies. This study is a quantitative descriptive research that applies a geostatistical spatial analysis technique, namely Ordinary Kriging interpolation, to predict FRP values in West Kalimantan for July, August, and September 2024. The data were obtained from satellite imagery (VIIRS NOAA-20), including latitude, longitude, and FRP values. Prior to modeling, data were tested for normality and found to follow a normal distribution. The spherical semivariogram model yielded the best fit for July and August with RMSE values of 0.046 and 0.011, respectively, while the Gaussian model was optimal for September (RMSE = 0.007). The results show spatial variation in FRP distribution across different regencies each month, with the highest estimated FRP values recorded in Kapuas Hulu (July: 63.56), Melawi (August: 69.00), and Ketapang (September: 55.27). Most areas demonstrated low fire intensity, as shown by the dominance of green zones on the prediction maps. However, localized red-yellow zones indicate areas with high fire potential, which shifted monthly. This study contributes by demonstrating the application of Ordinary Kriging in forest fire intensity mapping and highlights the importance of choosing an appropriate semivariogram model to enhance predictive accuracy. The resulting FRP prediction maps can serve as a valuable tool for policy planning and targeted fire prevention efforts.
Markov Chain Analysis of Bank Customer Migration: Implication for Financial Inclusion in Maritime Economies Hayati, Nahrul; Sulistyono, Eko; Gusrita, Rani
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32121

Abstract

Objectives: This study analyzes customer migration patterns among five major banks (BCA, BNI, BRI, BSI, and Bank Mandiri) in Batam’s strategic maritime economic zone using a Markov Chain model to assess long-term market dynamics and financial inclusion implications. The research aims to quantify interbank transition probabilities, to identify key switching drivers, and to develop targeted policy recommendations. Methods: Using a quantitative descriptive-analytical approach, we collected structured questionnaires from 250 Batam Institute of Technology academic members, capturing historical bank transitions and 5-point Likert-scale evaluations of eight switching factors. These factors included ATM/branch proximity, administrative fees, mobile/internet banking service, salary/ scholarship payment linkages, promotions/rewards, interest rates, family/friend recommendations, and Sharia compliance. Data were analyzed via Markov Chain modeling to project steady-state distributions. Results: The transition matrix revealed BCA’s superior retention (85.1%) compared to peers, with steady-state projections showing market dominance (32.44%), followed by Bank Mandiri (26.51%) and BSI (26.39%). Salary linkages (mean score: 3.45) and ATM accessibility (3.16) emerged as primary retention drivers, while BCA’s digital services (3.40) and low fee perception (3.67) explained its competitive edge. Paradoxically, BSI capitalizes on institutional salary systems (4.27) despite moderate Sharia compliance ratings (2.87). Implications: Three key policy directions emerge: hybrid digital-physical banking for coastal communities, Islamic financial ecosystem development, and fee transparency regulations. The study advances Markov Chain applications in behavioral finance while providing SEZ-specific insights for inclusive banking strategies.
The Compound Area of Quadrilaterals and Triangles: A Worked Example Based Learning Design Retnowati, Endah; Fadlila, Nindy
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 1 (2023): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i1.11678

Abstract

Complex yet hierarchical mathematical material in fact does not mean that the process of schema acquisition and accommodation in long-term memory is easy. For an instance, year seven students learn to solve problems related to the compound area of quadrilaterals and triangles. This problem may be categorized as a well-structured problem, therefore, it might be procedurally obvious to reach the solution, for those who have possessed sufficient prior knowledge of the aspects of the shapes. This study aims to discuss instructional strategy for novices when learning to solve problems like these. Based on a cognitive load theory, the strategy of worked example could be applied effectively for novices. The design of the worked example must be presented in such a way it could minimize extraneous cognitive load. The composite shapes of quadrilateral and triangles might be challenging to be described in an integrated format to avoid the split attention effect. This paper shows how this can be done by using techniques, such as (1) number sequences of the solution steps; (2) different colors for prompting attention resource; (3) less wording, more procedure application; and (4) consistency of layout within overall material. In order to apply these, the instructional designers should follow ADD steps, (1) Analyze the learning content, arrange them accordingly; (2) Design one worked example, evaluate its accuracy and niche; and (3) Develop into several worked example pairs. Two worked example with paired problems have been successfully developed and declare valid. Eventually, it might be suggested that comprehensive consideration when designing worked example that contain pictures should reflects how students use their cognitive resource during learning.
Comparing MARS and Binary Logistic Regression to Modelling Hepatitis C Cases using the SMOTE Balancing Method Chamidah, Nur; Ramadhanti, Aulia; Ramadhani, Azzah Nazhifa Wina; Syahputra, Bimo Okta; Ariyawan, Jovansha; Kurniawan, Ardi
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i1.33196

Abstract

Hepatitis is an inflammatory liver disease caused by viral infection and remains a major global public health concern, responsible for approximately 1.4 million deaths annually. Egypt is among the countries with the highest prevalence of Hepatitis C. To address this issue and support Goal 3 of the Sustainable Development Goals (SDGs), this study applies a quantitative approach using secondary data to analyze factors influencing Hepatitis C infection in Egypt. Two statistical models Binary Logistic Regression and Multivariate Adaptive Regression Splines (MARS) were compared, with the SMOTE method implemented to correct class imbalance. The dataset consisted of 608 patient observations, initially imbalanced at a ratio of 86.5:13.5, and were balanced to 52.6:47.4 after SMOTE application. The results revealed that the MARS model demonstrated superior predictive performance compared to binary logistic regression. All independent variables were found statistically significant (p < 0.05), except sex. Additionally, all odds ratios were less than 1, indicating a lower probability of Hepatitis C infection relative to non-infection. These findings highlight the relevance of statistical modeling and data-driven strategies in supporting preventive health measures. 
Analysis of the Spatial Error Model with Queen Contiguity Matrix Weights on Dengue Fever Soraya, Siti; Aziza, Istin Fitriani; Arisandi, Rizwan; Verma, Kirti; Isasi, Widani Darma; Sufahani, Suliadi Firdaus
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i1.33477

Abstract

Dengue Fever is one of the deadly diseases caused by a rapidly spreading virus transmitted through the Aedes aegypti mosquito. This study focuses on the NTB region, which has different geographical characteristics and infrastructure challenges. The variables used in this study are: dengue fever incidence, population, hospitals, community health centers, poor residents, and floods. The aim of this study is to model the factors that influence the occurrence of dengue fever in NTB. The method used is the Spatial Error Model (SEM), which serves to analyze spatial data to observe spatial correlation in the error variables. The research results indicate that the Moran Index and the Lagrange Multiplier test confirm the existence of spatial dependence in the error aspects. Significant variables at the 5% level affecting dengue fever cases are population size, the number of hospitals, and the number of community health centers. These findings provide an important scientific contribution as they represent one of the early studies that specifically identify and model the spatial dependence patterns of dengue fever cases in West Nusa Tenggara using a spatial econometric approach, thereby enriching the literature on spatial epidemiology at the regional level. The findings indicate that population growth and disparities in healthcare facilities increase the risk of dengue fever. This implies that more equitable spatial planning of healthcare services, strengthening of primary care, population density control, and increased community participation in sanitation and regular mosquito breeding site eradication are necessary as part of an to reduce dengue fever cases in NTB.
Sentiment Analysis of Hotel Reviews in Senggigi using Decision Tree and Support Vector Machine Algorithm Putra, Lalu Muhammad Reza Suganda; Wijayanto, Heri; Wedashwara, I Gede Putu Wirarama
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i1.34960

Abstract

The tourism industry is a rapidly growing sector that significantly contributes to the economy, including Indonesia. One of the popular tourist destinations in Indonesia is Senggigi, located on the island of Lombok. This destination offers high natural and cultural appeal. In the tourism industry, hotels are crucial as primary accommodations for travelers to stay and rest. Tourist reviews on hotel services greatly influence potential visitor’s decisions in selecting the right accommodation. Therefore, sentiment analysis of hotel reviews is essential for understanding customer satisfaction levels and assisting hotel managers in improving service quality. This research applies a comparative quantitative approach using Decision Tree and Support Vector Machine (SVM) algorithms. The dataset consists of 6,920 hotel reviews collected from TripAdvisor platforms through web scraping techniques. Data preprocessing included data cleaning, case folding, tokenization, stop word removal, and stemming to enhance classification performance. Sentiment labels were categorized into positive, neutral, and negative classes. Model performance was evaluated using multiple metrics, including accuracy, precision, recall, and F1-score, to ensure a comprehensive assessment. The word frequency distribution reveals that that accommodation experience and room quality play a crucial role in customer satisfaction. Positive sentiment is dominated by adjectives like great, nice, and beautiful, reflecting pleasant experiences. Negative sentiment is expressed more politely through phrases such as not good or not very nice. Neutral sentiment tends to be descriptive without strong emotional expression. In terms of model performance, SVM outperformed the Decision Tree model, achieving an accuracy of 90%, precision of 91%, recall of 90%, and an F1-score of 85%. In comparison, the Decision Tree achieved an accuracy of 87%, precision of 84%, recall of 87%, and an F1-score of 85%. These findings demonstrate the superior capability of SVM in handling complex and diverse textual data. This study contributes academically by strengthening empirical evidence on the effectiveness of machine learning–based sentiment analysis in the tourism domain and practically by providing actionable insights for hotel managers to improve service quality and customer satisfaction.
Application on Hypergraph in Vigenere Chiper Asari, Okta Endri; Dafik, Dafik; Adawiyah, Robiatul; Kristiana, Arika Indah; Prihandini, Rafiantika Megahnia
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i1.34572

Abstract

Message protection remains a major focus in the field of cryptography. This study proposes a new development on the Caesar cipher algorithm by utilizing hypergraph as a keystream generation source. The research designs a super (a,d)-hyperedge antimagic total labeling method applied to three hypergraph structures (Volcano, Semi Parachute, and Comb) to generate the keystream. Security is evaluated using four mechanisms: brute force analysis, processing time, ciphertext character distribution, and ciphertext bit size. The findings prove that the hypergraph based approach is robust against brute force attacks, improve memory and time efficiency. Quantitatively, the Comb hypergraph demonstrates the best efficiency, achieving an encryption time of 0.0030 seconds for 512 bytes and superior storage efficiency (e.g., 136 bytes for 16 bytes ), outperforming the Semi Parachute and Volcano structures. The main contributions include the hypergraph labeling-based keystream generation algorithm, dynamic block key construction, and a Vigenere protocol that is more adaptive to storage constraints and computationally efficient..

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