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CAUCHY: Jurnal Matematika Murni dan Aplikasi
Published by Universitas Islam Negeri Maulana Malik Ibrahim Malang
ISSN : 20860382     EISSN : 24773344     DOI : 10.18860
Core Subject : Education,
Mathematics
Jurnal CAUCHY secara berkala terbit dua (2) kali dalam setahun. Redaksi menerima tulisan ilmiah hasil penelitian, kajian kepustakaan, analisis dan pemecahan permasalahan di bidang Matematika (Aljabar, Analisis, Statistika, Komputasi, dan Terapan). Naskah yang diterima akan dikilas (review) oleh Mitra Bestari (reviewer) untuk dinilai substansi kelayakan naskah. Redaksi berhak mengedit naskah sejauh tidak mengubah substansi inti, hal ini dimaksudkan untuk keseragaman format dan gaya penulisan.
Arjuna Subject : -
Articles 533 Documents
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Mechanism Design-Based Mathematical Modeling of the Decoy Effect in Housing Type Selection Sentot Eko Baskoro; I Nyoman Sutapa; Suhartono Suhartono
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36937

Abstract

This study develops a mechanism design-based mathematical model to induce a decoy effect in housing selection, shifting consumer preferences from small to large house types. Using an area-per-price utility function and dominance constraints, two optimal decoy configurations (adjacent and strong) are derived analytically. We consider a developer offering a small house (500,000,000 IDR; 40 m2 building; 100 m2 land) and a large house (1,000,000,000 IDR; 100 m2 building; 200 m2 land), and design an additional decoy alternative. By imposing dominance and feasibility constraints, we derive closed-form conditions on the decoy's building area Ad and land area Ld for two price levels, 750,000,000 IDR and 850,000,000 IDR. The resulting adjacent ( = 0.002) and strong ( = 0.010) decoys ensure that the large house weakly dominates the decoy while maintaining internal consistency of preferences. Sensitivity analysis shows that the advantage margin increases linearly with proximity and context intensity parameters. The proposed framework provides developers with an operational and auditable mechanism for housing portfolio design.
Modeling Fuzzy Geographically Weighted Clustering with Flower Pollination Algorithm for Spatial Optimization and Clustering Friansyah Gani; Henny Pramoedyo; Achmad Efendi
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36800

Abstract

This study aims to analyze the clustering of districts/cities in East Nusa Tenggara Province (NTT) using the Fuzzy Geographically Weighted Clustering method optimized through the Flower Pollination Algorithm (FGWC-FPA). The data consist of eight health and sanitation indicators for 2024. The analysis produced two clusters with distinct characteristics. Cluster 1 is dominated by areas with relatively higher rates of complementary feeding and good BCG immunization coverage but still shows a higher proportion of low birth weight (LBW) infants and limited access to drinking water and sanitation. Meanwhile, Cluster 2 demonstrates significant advantages in access to proper drinking water (90.37%) and proper sanitation (83.19%), as well as more optimal Hepatitis B immunization coverage. Evaluation of cluster validity using Classification Entropy (CE) and the Separation Index (SI) shows that the best configuration is obtained at m = 1.5 with c = 2, yielding the lowest CE value (0.584872) and reasonably good cluster separation (SI = 1.069092). Thus, the FGWC-FPA method is capable of producing optimal cluster partitioning and can serve as a basis for formulating more targeted health intervention strategies in NTT.
b-coloring Analysis on Tree Graph Families Rafiantika Megahnia Prihandini; Arika Indah Kristiana; Lusita Risma Dana; Edy Wihardjo; Robiatul Adawiyah; Hutkemri Zulnaidi
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.32328

Abstract

A tree graph is a connected graph and has no circuits. Tree graphs used in this study include: broom graph, centipede graph, and Banana Tree graph. Graph coloring is the process of giving color to graph elements with the rule that neighboring elements must not have the same color, and the number of colors used must be as minimal as possible. b-coloring of a graph G is a coloring of the vertices of G such that each color class has at least one vertex adjacent to all other color classes. The b-chromatic number of a graph G is denoted by φ(G), is the largest integer k such that G has a b-coloring with k colors. The limit of b-coloring of graph G with maximum degree ∆(G) is as follows, χ(G) ≤ φ(G) ≤ ∆(G) + 1.χ(G) is the chromatic number of a graph G where χ(G) is the minimum value of the color required for proper coloring of graph G. While ∆(G) is the maximum degree of the vertices in graph G. This study uses an exploratory research type with an axiomatic deductive method and a pattern detection method. Based on this study, the results of the b-coloring analysis on the tree graph family are known. The results of this study are expected to be used as study material and the development of scientific knowledge related to b-coloring analysis on other graphs.
Modelling Factors Affecting the Middle Income Trap in Indonesia Using Generalized Additive Models (GAM) Dita Amelia; Suliyanto Suliyanto; Azizah Atsariyyah Zhafira; Aulia Ramadhanti; Billy Christandy Suyono; Firqa Aqila Hizbullah
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.35119

Abstract

Indonesia is currently facing the risk of the Middle Income Trap (MIT), a condition in which economic growth stagnates after reaching middle-income status. This study aims to identify and model socio--economic factors affecting MIT at the provincial level in Indonesia during 2020--2023. The Generalized Additive Model (GAM) is employed to capture nonlinear and heterogeneous relationships between predictors and GRDP per capita with complex patterns that conventional linear or parametric models often fail to detect. The use of GAM in this context represents a methodological contribution, as studies applying GAM for MIT analysis in Indonesia remain very limited. This research therefore introduces a novel analytical approach by demonstrating how GAM can reveal flexible functional relationships and uncover nonlinear effects that are overlooked by traditional panel regression. GRDP per capita is modeled using six predictors: life expectancy, poverty rate, informal employment share, upper secondary education completion, food insecurity prevalence, and population density. The best model is obtained using the Gaussian family with an identity link, with five predictors showing nonlinear effects and food insecurity exhibiting a negative linear influence. The selected model demonstrates strong performance, indicated by an AIC value of 2743.279 and a R^2 of 98.6%, suggesting a very high explanatory power. In addition, the model achieves good predictive accuracy, with a MAPE of 8.04%. The findings support evidence-based policies aligned with Sustainable Development Goal (SDG) 8, promoting inclusive and sustainable economic growth.
University Scheduling Optimization Using Integer Programming: A Case Study Gayus Simarmata; Rajainal Saragih; Anil Hakim Syofra
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37815

Abstract

This paper presents an Integer Linear Programming (ILP) model to construct a weekly lecture timetable for the Mathematics Study Program at HKBP Nommensen University, Pematangsiantar. The case study comprises 25 courses, three rooms (RK 11, RK 12, and LAB 1), five teaching days (Monday–Friday), and 13 time periods per day. The model enforces hard constraints on room, lecturer, and cohort non-overlap; consecutive periods according to credit load; room-type compatibility between theory and practicum sessions; and an institutional worship-time restriction on Tuesday. Lecturers’ availability is represented by a binary acceptance matrix collected at the course level, and rejected time periods are penalized in the objective. The ILP is implemented in Python using the PuLP (Python Linear Programming) library and solved with the CBC (Coin-or Branch and Cut) solver. For the real instance, the solver returns an optimal solution with objective value Z∗ = 0 (no scheduled period falls in a rejected slot) in approximately 94 seconds. The resulting timetable is conflict-free and operationally interpretable, with a weekly room-time utilization of about 31.3%. To support verification and communication to stakeholders, the paper also provides a heatmap of the acceptance matrix and a graphical timetable by room and day.
Enhancing Spatio-Temporal PCA with FASTMCD for Climate Comfort Assessment Agus Yarcana; Henny Pramoedyo; Suci Astutik
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37866

Abstract

This study presents a robust formulation of the Spatio-Temporal Principal Component Analysis (STPCA) by integrating the Fast Minimum Covariance Determinant (FASTMCD) estimator into the spatio-temporal decomposition framework. Unlike classical STPCA—which constructs the spatio-temporal matrix from sample-based means and is therefore highly sensitive to extreme observations—the proposed STPCA–FASTMCD replaces the classical mean and scatter structure with robust estimates derived from FASTMCD. The method incorporates functional Fourier-based temporal smoothing and an inverse power–distance spatial weight matrix to better capture the underlying spatio-temporal patterns. Monthly climate data (thermal comfort, cloud cover, rainfall, and wind speed) from 24 monitoring locations in Bali during 2010–2019 are analyzed. Performance is evaluated using mean-shift analysis, eigenvalue-stability assessment, and eigenvector perturbation diagnostics. The classical STPCA produces inflated and unstable leading components, with the first eigenvalue reaching 63.36, whereas STPCA–FASTMCD reduces this value to 37.79 and yields smoother, more coherent spatial loading patterns. The robust STPC1 reveals a clear thermal–wind variability mode, enhancing the interpretability of spatial gradients relevant to climate comfort. Overall, the proposed formulation substantially improves the stability and climatic relevance of dominant spatio-temporal modes, providing a more reliable foundation for climate comfort assessment in Bali.
Transmission Dynamics of Dengue Disease Incorporating Treatment, Mass Awareness, and Wolbachia Intervention Rafika Nanda Agustina; Budi Priyo Prawoto
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.39026

Abstract

Dengue Hemorrhagic Fever (DHF) remains a serious global public health threat, with its transmission dynamics strongly influenced by vector control strategies and human behavior. This study constructs and analyzes a mathematical model based on a system of differential equations to investigate the transmission dynamics of DHF by integrating three control strategies: treatment, public awareness, and the release of Wolbachia-infected mosquitoes. The basic reproduction number (R0) is derived using the Next Generation Matrix (NGM) method and serves as a threshold parameter for disease spread. Numerical simulations show that when R0 < 1, the system converges to the disease-free equilibrium, indicating that the disease will eventually die out. Conversely, by adjusting the parameter δ such that R0 > 1, the system becomes stable at the endemic equilibrium, implying the persistence of the disease within the population. These findings highlight the importance of controlling key parameters through integrated intervention strategies to reduce R0 below unity.
Nasdaq Inc. Stock Price (NDAQ) Prediction Due to Trump’s Tariff Policy Using Pulse Function Intervention Analysis Sediono Sediono; Kimberly Maserati Siagian; Josephin Viona Aditya
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37168

Abstract

Nasdaq Inc. (NDAQ) is one of the leading stock exchanges in the United States, ranking second globally after the New York Stock Exchange (NYSE) based on market capitalization. As a highly dynamic and information-sensitive market, Nasdaq Inc. stock prices respond quickly to internal corporate conditions and external macroeconomic or policy changes. One notable event affecting market stability was President Donald Trump’s import tariff policy, aimed at protecting U.S. industries from foreign competition, particularly Chinese imports. The implementation of this policy triggered significant volatility, including a sharp decline in Nasdaq Inc. stock prices on March 2, 2025. This study examines the impact of this policy on Nasdaq Inc. stock movements using the ARIMA(0,2,1) model with an intervention of order b = 0, r = 1, and s = 0. The results show that all model parameters are statistically significant and produce accurate forecasts, with a MAPE of 2.19%, an RMSE of 5.98766, and an MAE of 2.05232. These findings indicate that intervention analysis effectively captures the impact of import tariff policies on stock market dynamics and provides valuable insights for investors and policymakers in anticipating market fluctuations driven by global economic policy changes.
Implementation of DenseNet121 Based on Convolutional Neural Network with Geometric Augmentation for Breast Cancer Histopathology Image Classification Nabilah Evi Ariani; Sugiyarto Surono; Aris Thobirin
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37896

Abstract

This study evaluates the performance of the DenseNet121 architecture for binary classification of breast cancer histopathological images using the BreakHis dataset. The model employs ImageNet pre-trained weights, fine-tuning, and geometric data augmentation to improve feature learning and generalization. To obtain more reliable results, three optimization algorithms (Adam, AdamW, and RMSprop) were evaluated through repeated experiments, and performance was reported using mean and standard deviation of test metrics. The experimental results demonstrate that DenseNet121 achieves consistently high classification performance across different optimizers, with the Adam optimizer showing the most stable results. These findings indicate that DenseNet121 combined with data augmentation provides an effective and robust approach for histopathological image classification while emphasizing the importance of repeated evaluation for reliable performance assessment.
Modeling the Dynamics of Tuberculosis-Diabetes Mellitus Coinfection with an Optimal Control Approach Muna Afdi Muniroh; Kresna Oktafianto; Eriska Fitri Kurniawati
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37539

Abstract

Tuberculosis–Diabetes Mellitus (TB–DM) coinfection increases morbidity, treatment failure, and healthcare costs. This study analyzes TB–DM transmission dynamics and identifies effective prevention strategies using a ten-compartment mathematical model that distinguishes non-diabetic and diabetic populations, each classified into susceptible, latent, active, treatment, and recovered classes. Numerical analysis verifies that the disease-free equilibrium is stable when the basic reproduction number is less than one, whereas an endemic equilibrium exists when it exceeds one. Using baseline parameter values, the reproduction number is estimated as 3.592, indicating persistent TB–DM transmission. An optimal control framework is formulated to evaluate two time-dependent interventions: reducing TB transmission through case detection and contact tracing, and preventing diabetes onset in non-diabetic individuals through metabolic monitoring. Numerical simulations demonstrate that the combined implementation of both control strategies significantly reduces TB–DM incidence while minimizing intervention costs. These findings support the importance of integrated, time-varying TB–DM control programs for public health.

Page 43 of 54 | Total Record : 533

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