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INDONESIA
JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI
Published by Universitas Hasanuddin
ISSN : 18581382     EISSN : 26148811     DOI : -
Core Subject : Education,
Mathematics
Jurnal ini mempublikasikan paper-paper original hasil-hasil penelitian dibidang Matematika, Statistika dan Komputasi Matematika.
Arjuna Subject : -
Articles 534 Documents
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Cox Weibull Regression Modeling for Graduation Rate Analysis of Statistics Students at Mulawarman University Suyitno Suyitno; Azkadiaannzumi Azkadiaannzumi; Darnah Darnah
Jurnal Matematika, Statistika dan Komputasi Vol. 22 No. 3 (2026): May 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v22i3.50137

Abstract

This study proposes a Cox regression model with a Weibull baseline hazard, representing a key statistical innovation, hereafter referred to as the Cox Weibull regression model. Parameter estimation was conducted separately, the regression parameters were estimated using the partial likelihood method, while the baseline hazard parameters were estimated using Maximum Likelihood Estimation (MLE). This study aims to identify factors influencing graduation rates and to examine variations in these rates among students in the Statistics Study Program at Universitas Mulawarman based on significant factors. The study used academic records of 77 students from the Statistics Study Program (cohorts 2016–2019), obtained from the Academic and Student Affairs Bureau, Faculty of Mathematics and Natural Sciences, Universitas Mulawarman. The best model selected using the backward elimination method, included three covariates and was considered adequate, as all covariates were statistically significant and the model yielded the lowest AIC value (462.34). The results indicate that cumulative grade point average (GPA), scholarship status, and university admission pathway significantly influence student’s graduation rates. Higher GPA was associated with a shorter time to graduation, scholarship recipients graduated faster than non-recipients, and students admitted through the SNMPTN pathway graduated faster than those admitted through other pathways.
Generalization of Viviani’s Theorem Using a Complex Number Approach on Regular Polygons Inscribed in the Unit Circle Zulfatra Lamuda; Asriadi Asriadi
Jurnal Matematika, Statistika dan Komputasi Vol. 22 No. 3 (2026): May 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v22i3.50210

Abstract

One of the classical theorems in geometry is Viviani’s Theorem. This theorem states that for any interior point of an equilateral triangle, the sum of the perpendicular distances from that point to each triangle side equals the triangle’s height. Therefore, this study aims generalize the property contained in Viviani’s Theorem to regular polygons inscribed in the unit circle using a complex number approach. The results of this study show that the obtained constant is n⋅ cos (π/n ), where nϵN. This constant replaces the height of the equilateral triangle as stated in Viviani’s Theorem.  
Optimizing Cluster Centroids using Hybrid Firefly-Genetic Algorithm for Village Development Clustering Annisa Rahma; Rani Nooraeni; Raditya Hizra
Jurnal Matematika, Statistika dan Komputasi Vol. 22 No. 3 (2026): May 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v22i3.50288

Abstract

Clustering in the Building Village Index (BVI) offers an alternative approach to identifying village groupings based on numerical and categorical characteristics similarities. K-Prototype (KP) is a popular clustering algorithm for handling . This study proposes the hybridization that combines the exploitation strength of the Firefly Algorithm (FA) with the exploration capability of the Genetic Algorithm (GA) to optimize centroid initialization of KP. The results show that FA-GA hybridization enables the centroid initialization process to be faster with optimal fitness compared to either a single FA or a single GA. FGAKP is the best clustering algorithm in this study because it produces the smallest Total Cost (TC) and the largest Cluster Validity (CV) index with the most efficient centroid initialization time across all training data. The implementation of FGAKP in village grouping based on BVI indicators in North Kalimantan Province in 2024 grouped 484 villages into 5 categories based on their village development potential, achieving an 11.69% reduction in TC and a 16.75% improvement in CV compared to the standard KP without optimization.  
Statistical Process Control And Capability Analysis of Mechanical Component Dimensions with Operator Factor Angelica Carolina Tambunan; Rut Remita Assianna g Situmoran
Jurnal Matematika, Statistika dan Komputasi Vol. 22 No. 3 (2026): May 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v22i3.50388

Abstract

Statistical quality control (SQC) is a fundamental approach in modern manufacturing for ensuring that  production processes consistently conform to specified quality requirements. This study applies an integrated SQC framework comprising the Xbar-R control chart, one-way analysis of variance (ANOVA), and process capability analysis to evaluate the dimensional quality of mechanical components sourced from an open manufacturing dataset publicly available on Kaggle (Parts Manufacturing Industry Dataset). Three critical dimensions were examined: length, width, and height, each measured by 20 operators with five replicates per operator (n = 100 per dimension). Prior to control charting, data normality was verified through probability plots based on the Anderson-Darling statistic. The Xbar-R analysis revealed out-of-control signals for the length dimension at subgroups 3 and 5, and for width at subgroup 3, indicating the presence of assignable (special) causes of variation. One-way ANOVA demonstrated that inter-operator effects on width were statistically non-significant (F = 1.34, p = 0.185), whereas significant operator-to-operator differences were detected for length (F = 2.10, p = 0.012). Process capability indices showed that all three dimensions fell below the minimum acceptable threshold of Cp ≥ 1.33, with length being most critical (Cp = 0.84, Cpk = 0.71). The findings underscore the necessity of targeted corrective actions including measurement system standardisation, operator retraining, and process variability reduction.  
Fisrt Zagreb, Gutman, and Wiener Index of The Non-Coprime Graph for Dihedral Group Dimas Indrawadi; I Gede Adhitya Wisnu Wardhana; Hazzirah Izzati Hassim; Fariz Maulana
Jurnal Matematika, Statistika dan Komputasi Vol. 23 No. 1 (2026): September 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/sqqdm542

Abstract

This study investigates the structure of non-coprime graphs derived from the dihedral groups of prime power order using approaches from graph theory and group theory. In molecular representation and pure mathematics, graphs serve a tool to illustrate the internal structure of systems through topological indices. A non-coprime graph is a graph formed by connecting two distinct vertices if the greatest common divisor (GCD) of their orders is not equal to one, meaning the two elements are not coprime. The primary focus of this research is to derive general formulas for the first Zagreb index, the Gutman index, and the Wiener index of non-coprime graphs constructed from the dihedral group ​. For the first Zagreb index, the cases and are considered, where is a prime number and is a positive integer. Meanwhile, for the Gutman and Wiener indices, the study focuses on the case, with as a positive integer. This research produces explicit formulas for the first Zagreb index, Gutman index, and Wiener index of the corresponding non-coprime graphs.
Insurance Portfolio Valuation under Market Jumps: A Framework Combining Kou Jump-Diffusion Forecasting and Dynamic CPPI Hedging Andi Fitriawati; Sapto Wahyu Indratno; Kurnia Novita Sari; Werry Febrianti
Jurnal Matematika, Statistika dan Komputasi Vol. 23 No. 1 (2026): September 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/gxed0068

Abstract

This study develops an integrated valuation framework for insurance portfolios under discontinuous market conditions. The framework combines asset-price forecasting based on the Kou jump-diffusion model with Dynamic Constant Proportion Portfolio Insurance (D-CPPI) to support portfolio protection and capital guarantee management. The Kou jump-diffusion model is employed to capture asymmetric jumps and extreme market movements, while D-CPPI dynamically allocates wealth between risky and risk-free assets. To address gap risk, a volatility-adjusted risk multiplier with a non-negativity constraint is incorporated into the portfolio insurance mechanism. The proposed framework is evaluated using S&P 500 index data from 2006–2010 at daily, weekly, and monthly observation frequencies. The forecasting results demonstrate satisfactory predictive performance, with Mean Absolute Percentage Error (MAPE) values of 4.76%, 5.04%, and 5.36% for the daily, weekly, and monthly models, respectively. Portfolio simulations indicate that arbitrarily selected multipliers can lead to substantial losses and floor violations, whereas the constrained volatility-adjusted multiplier maintains portfolio values above the guaranteed floor across all observation frequencies and effectively mitigates gap risk. These findings suggest that integrating Kou jump-diffusion forecasting with D-CPPI provides an effective approach for insurance portfolio valuation under volatile market conditions. The proposed framework contributes to the literature by jointly addressing asset-price jumps, dynamic portfolio allocation, and gap-risk mitigation within a unified insurance portfolio management framework.
Exact Sequences in (R,S)-Modules Dian Ariesta Yuwaningsih; Yassin Dwi Cahyo; Nanda Subastian
Jurnal Matematika, Statistika dan Komputasi Vol. 23 No. 1 (2026): September 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ersnw733

Abstract

The concept of modules has been generalized to the structure of (R,S)-bimodules, which has further been extended to (R,S)-modules. Various properties of classical module theory have been developed within the framework of (R,S)-modules. One of the important topics in module theory that can be extended to this setting is the concept of exact sequences. In this paper, we develop the notion of exact sequences in modules to exact sequences in (R,S)-modules. We begin by introducing the definitions of exact sequences and short exact sequences in (R,S)-modules and examine their basic properties. Several examples are provided to illustrate the concepts and to highlight the similarities and differences with classical module theory. In addition, we establish criteria for determining when a short exact sequence of (R,S)-modules splits and present related structural results using commutative diagrams. Furthermore, we present the necessary and sufficient conditions for an (R,S)-module to be Noetherian in a short exact sequence. These results contribute to a deeper understanding of the homological behavior of -modules and provide a foundation for further research in this area.
A Study of Multivariate Time Series Clustering Based on Vector Autoregressive with Exogenous Models for Forecasting Cooking Oil Prices in Indonesia Mawar Cahyanindri; Rohaeti Embay; Maya Widyastiti
Jurnal Matematika, Statistika dan Komputasi Vol. 23 No. 1 (2026): September 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/kxgq2516

Abstract

The fluctuations in cooking oil prices in 77 regencies and cities included in the Strategic Food Price Information Center data show varying levels of volatility over time. This phenomenon presents a challenge for forecasting cooking oil prices in Indonesia in the future. Consequently, a method capable of estimating these prices is required. One such approach involves Multivariate Time Series Clustering (MTSCLUST) method based on the Vector Autoregressive with Exogenous (VARX) model. The MTSClust method is employed to map spatial time series pattern interdependencies across regions, while the VARX model is utilized for its ability to capture the dynamics of intervariable relationships influenced by external factors. This study aims to examine the application of the MTSClust method based on the VARX model in forecasting cooking oil prices in Indonesia in the future. Cluster formation results with K-Means with the Chebyshev distance metric indicate that the 77 regencies and cities in Indonesia can be grouped into three clusters, achieving excellent forecasting accuracy with MAPE values below 10%. Cluster 3 became the best cluster using the VARX (24,1) model, demonstrating optimal performance with a MAPE value of 0.228%. The findings of this study confirm that the MTSClust model with VARX integration is effective for forecasting future cooking oil prices.
Edge Metric Dimension of Uniform Theta Graphs and Sunflower Graphs Muchammad Abrori; Deddy Rahmadi; Lailatul Ulla Safitri; Alvian Nur Rohman; Jaqueline Widad Zuha
Jurnal Matematika, Statistika dan Komputasi Vol. 23 No. 1 (2026): September 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/t02sds33

Abstract

Let be a graph with vertex set and edge set . In graph theory, an edge resolving set is defined as a subset of vertices such that every edge in has a distinct distance representation with respect to . The minimum cardinality of an edge resolving set is called the edge metric dimension of , denoted by . This study aimed to determine the edge metric dimension of the uniform theta graph and the sunflower graph . The method employed a graph-structure approach and distance analysis between edges and vertices supported by a literature review. The results showed that for and , for , and for . Furthermore, for and , for and , for , and for .
Application of Agglomerative Hierarchical Clustering Based on Rolling Horizon and Minimum Variance in IDX30 Stock Portfolio Optimization Khoirunnisa Puspa Negari; Ezra Putranda Setiawan
Jurnal Matematika, Statistika dan Komputasi Vol. 23 No. 1 (2026): September 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/wm9n6k43

Abstract

Portfolio diversification is a strategy to reduce investment risk by spreading assets across stocks with different movement patterns. However, most investors tend to select stocks based on highest historical returns and exhibit herding behavior without considering inter-stock correlations, risking undiversified portfolios. Stock movement patterns are dynamic, requiring methods that accommodate such changes. This study aims to cluster IDX30 stocks using agglomerative hierarchical clustering based on rolling horizon to identify stocks with relatively consistent movement patterns, compare diversification characteristics, and evaluate portfolio performance using minimum variance and equal weight. Data consists of daily closing prices of IDX30 stocks from January 3, 2022 to December 30, 2024 obtained from Yahoo Finance. Results show stocks tend to cluster based on sectoral similarity with cluster membership proportion of for and for . Horizons 5 and 12 were selected as portfolio construction periods due to having the highest number of consistent stocks. Clustering portfolios exhibit better diversification with more low-correlated stock pairs compared to non-clustering portfolios. Minimum variance optimization shows the clustering portfolio outperforms with Sharpe ratios of at horizon 5 and at horizon 12 compared to and non-clustering portfolios. Conversely, equal weight shows non-clustering portfolios outperform clustering portfolios. During the evaluation period, the clustering portfolio with minimum variance achieved average returns of for 30 days and for 60 days after horizon 5 and demonstrated relatively stable performance under extreme market conditions at horizon 12.

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