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Journal of Mathematics, Computation and Statistics (JMATHCOS)
Published by Universitas Negeri Makassar
ISSN : 24769487     EISSN : 27210863     DOI : https://doi.org/10.35580/jmathcos
Core Subject : Education,
Mathematics
Fokus yang didasarkan tidak hanya untuk penelitian dan juga teori-teori pengetahuan yang tidak menerbitkan plagiarism. Ruang lingkup jurnal ini adalah teori matematika, matematika terapan, program perhitungan, perhitungan matematika, statistik, dan statistik matematika.
Arjuna Subject : Matematika - Matematika Terapan
Articles 210 Documents
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The Analysis and Simulation of Consumer Behavior Towards Product Boycotts Using Mathematical Modeling in North Sangatta District Jusman, Jusman; Side, Syafruddin; Syam, Rahmat; Yusuf SAP, Andi Muh. Ridho
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.6864

Abstract

This study aims to analyze and simulate a mathematical model of product boycott behavior in North Sangatta District using a modified SEIRS model approach. This model divides the population into four compartments: Susceptible (S), Exposed (E), Infected (I), and Recovered (R). Primary data were obtained through a survey of individuals aged 15-60 years living in North Sangatta District. The SEIRS-type mathematical model was used to determine the equilibrium point. The analysis showed that the basic reproduction number , indicating that an individual who boys can influence others to do the same. Stability analysis shows that when , the boycott-free equilibrium point is unstable, while the endemic equilibrium point is locally asymptotically stable. This means that individuals who boycott will remain in the population. Simulations show that reducing the transition rate from susceptible to exposed and from exposed to boycotts, as well as increasing the recovery rate, can be a solution to reduce the impact of boycotts.
PCA-SVM Classification: Motor Ability of Down Syndrome Based on Education, Economics And Physiotherapy Therapy Bota Muhammad Akbar; Al Um Aniswatun Khasanah; Sangidatus Sholiha; Wardhani Utami Dewi
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7261

Abstract

The classification of motor abilities of individuals with Down Syndrome is essential to identify more effective developmental patterns. However, research that integrates educational, economic, and physiotherapy factors in the classification model is still limited, especially in the application of machine learning-based methods. The purpose of this study is to classify using PCA-SVM on the motor ability of DS based on education, economics, and physiotherapy therapy. PCA is used to reduce the dimensions of the dataset by extracting the main features that have the greatest variation, thereby increasing the efficiency and accuracy of classification. Meanwhile, SVM with Radial Base Function RBF Kernel is applied to build a classification model capable of handling non-linear data and finding optimal hyperplanes as the separation boundary between classes. This study used 50 samples obtained from POTADS in Lampung Province, Indonesia. The results showed that PCA successfully extracted three main components that explained 80.2% of the variance of the data. The SVM model achieved an overall accuracy of 80.2%, with the highest classification success rate at Level 1 (100%) and Level 3 (75%), while Level 2 had some classification errors due to a wider variation in sample characteristics. This study implies that the resulting model can be used to identify individuals at risk of motor difficulties, allowing for earlier and targeted behavior. In addition, the results of this study can be a reference for medical practitioners and educators in developing therapy and education strategies that are more in line with the needs of each individual.
Optimization of Interval Singh’s Fuzzy Time Series with Particle Swarm Optimization for Forecasting Consumer Price Index in Luwuk City siswanto, Navira; Djakaria, Ismail; Arsal, Armayani
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7282

Abstract

High inflation can threaten economic stability, with CPI as the main indicator to measure the inflation rate. Luwuk City experiences significant CPI fluctuations, reflecting economic uncertainty so an accurate forecasting method is needed. This research aims to apply Singh's Fuzzy Time Series (FTS) method optimised with Particle Swarm Optimization (PSO) to improve CPI forecasting accuracy. This research includes quantitative research, using secondary data obtained from monthly CPI data in Luwuk City on the official website of the Badan Pusat Statistik Kota Luwuk. The results showed that the use of PSO optimisation on Singh's FTS was able to optimise the prediction accuracy level of Singh's FTS forecasting on Luwuk City CPI data, with a MAPE value of 0.45%, where this value is less than 10% which indicates that the forecasting accuracy is very accurate.
Mathematical Game Theory in Optimal Strategy Analysis for E-Wallet Competition (Case Study: Users of GoPay, DANA, and OVO in Makassar City) Side, Syafruddin; Irwan; Khadijah , Ummul
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7356

Abstract

. Game theory is a branch of applied mathematics within operations research that focuses on studying and understanding competitive situations involving multiple parties. The rapid growth of e-wallet usage has significantly intensified competition in the digital sector. This study aims to analyze the optimal strategies in the e-wallet competition between GoPay, DANA, and OVO in Makassar City using game theory. The data utilized in this research were obtained through a questionnaire survey involving 100 student respondents. Six strategic attributes are examined: product, price, promotion, place, practicality, and security. The results indicate that in the competition between GoPay and OVO, GoPay's optimal strategy is to focus on promotion to maximize profits, while OVO's optimal strategy is prioritizing security to minimize losses. In the competition between DANA and OVO, DANA's optimal strategies include product, price, and place to achieve maximum profits, while OVO focuses on product, promotion, and place to minimize losses. Meanwhile, in the competition between DANA and GoPay, DANA's optimal strategies are price, practicality, and security to maximize profitability, while GoPay prioritizes price, place, and security to minimize losses. These findings demonstrate the varying strategic approaches each e-wallet employs to adapt to the competitive market dynamics and optimize outcomes based on their respective priorities and strengths
Stability Analysis of a Time-Delayed Disease Transmission Model in Prey–Predator Populations Incorporating a Holling Type II Functional Response Rauf, Nurul Maqfirah; Sianturi, Paian; Jaharuddin, Jaharuddin
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7428

Abstract

Abstrak. This article presents a comprehensive study of a mathematical model describing the spread of infectious disease within a prey–predator population, incorporating the Holling type II functional response and a delay parameter, denoted as τ, representing the incubation or infection period. The model captures the interactions among four population groups: susceptible prey, infected prey, susceptible predators, and infected predators. Through analytical investigation, six fixed points (equilibrium points) of the system were identified. The stability of these fixed points was examined using the eigenvalues of the Jacobian matrix, and one locally stable fixed point was found, while the others were identified as saddle points or unstable. To gain deeper insights into the model’s behavior over time, numerical simulations were conducted for different values of the delay parameter . The results indicate that the presence of a time delay significantly affects the dynamics of all four population groups. Specifically, the infection delay can suppress or slow the spread of the disease by delaying the transition from susceptible to infected classes. Oscillatory behavior emerged in certain population groups when the delay was introduced, especially among infected prey and predators, before gradually stabilizing toward the disease-endemic equilibrium. These findings highlight the critical role of time delay in disease transmission dynamics in ecological systems and provide a framework for further research on delay-induced phenomena in epidemiological models. Keywords: Prey–Predator, Disease Spread, Delay Time, Functional Response, Stability Analysis.
Evaluation of Spatial Approaches of Poverty in East Java Agusta, Madania Tetiani; Sartono, Bagus; Djuraidah, Anik
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7663

Abstract

Geographically Weighted Regression (GWR) is the most frequently used for spatial modeling. GWR produces local model parameter estimates for each observed point. Unfortunately, GWR is known to be numerically unstable and can produce extreme coefficient estimates. Spatially Clustered Regression (SCR) and Spatially Constrained Clusterwise Regression (SCCR) are new approaches that combine cluster identification and regression estimation in one stage. This research evaluates these approaches to develop poverty alleviation in East Java with the largest number of poor people in rural areas as per March 2023 according to BPS. The response variable used is the percentage of poor families. While the explanatory variables used are the percentage of female heads of households, the percentage of non-electricity families, the average years of schooling, the percentage of home ownership, and the percentage of agricultural laborers. The results of GWR and K-Means produced three clusters in East Java, SCR produced four clusters in East Java, and SCCR produced three clusters in East Java. Based on the AIC value, the best approach is SCR with a value of 1,614. Based on its grouping, SCR is better in forming cluster with adjacent locations rather than GWR + K-Means and SCCR. The variables that significant to the percentage of poor families are the percentage of agricultural laborers, the percentage of home ownership, and the percentage of female heads of households.
Analysis of Geographically Weighted Negative Binomial Regression (GWNBR) Model with Adaptive Bisquare Kernel Weighting on Factors Causing Acute Respiratory Tract Infection (ARI) in Toddlers in South Sulawesi Province Wihda, Wihdatul Ummi; Ihsan, Hisyam; Ja'faruddin, Ja'faruddin
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7745

Abstract

Abstrak. Infeksi Saluran Pernapasan Akut (ISPA) pada balita masih menjadi masalah kesehatan serius di Sulawesi Selatan dengan pola sebaran kasus yang bervariasi antar wilayah. Penelitian ini dilatarbelakangi oleh perlunya pendekatan statistik yang mampu menangkap heterogenitas spasial, yaitu model Geographically Weighted Negative Binomial Regression (GWNBR).Penelitian ini bertujuan untuk mengestimasi parameter model Geographically Weighted Negative Binomial Regression(GWNBR) dengan pembobot adaptive bisquare kernel, menganalisis penyebaran spasial kasus Infeksi Saluran Pernapasan Akut (ISPA) pada balita, serta mengidentifikasi faktor-faktor signifikan yang memengaruhi kejadian ISPA di Provinsi Sulawesi Selatan. Data yang digunakan merupakan data sekunder dari survei kesehatan Badan Pusat Statistik (BPS) Indonesia, mencakup 24 kabupaten/kota selama satu tahun. Hasil menunjukkan bahwa model GWNBR mampu menangkap variasi spasial antarwilayah dengan baik, dibuktikan oleh nilai AIC terendah dan Quasi-global R² sebesar 0,9489. Faktor-faktor yang secara signifikan memengaruhi ISPA pada balita meliputi persentase perokok usia ≥15 tahun, jumlah penduduk miskin, indeks literasi masyarakat, serta tingkat pendidikan. Di beberapa wilayah, seperti Kabupaten Barru, persalinan tanpa fasilitas kesehatan juga berpengaruh signifikan. Temuan ini menegaskan pentingnya pendekatan spasial dalam perumusan kebijakan kesehatan yang responsif terhadap karakteristik lokal. Kata Kunci: Analisis spasial, GWNBR, ISPA, overdispersi
ENSEMBLE METHODS IN STATISTICAL DOWNSCALING WITH GAMMA-LASSO REGRESSION FOR RAINFALL PREDICTION IN WEST JAVA Sativa, Oryza; Djuraidah, Anik; Notodiputro, Khairil Anwar
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7748

Abstract

Rainfall is a crucial factor in weather and climate studies, particularly in disaster mitigation efforts such as flood and landslide prevention. West Java, with its mountainous topography and high rainfall, requires accurate rainfall predictions as a basis for decision-making. One effective approach is the ensemble method, which provides valuable insights into prediction outcomes and captures uncertainty. This study analyzes rainfall data from six stations in West Java (Cibukamanah, Krangkeng, Kawali, Katulampa, Cibeureum, and Gunung Mas) over the period 1991–2020. The results indicate that applying the ensemble method in Statistical Downscaling modeling using Gamma-Lasso Regression improves rainfall prediction accuracy compared to single models.
An Analysis of Expected Return and Risk for Determining the Efficient Portfolio of Financial Firms Listed on the Indonesia Stock Exchange Pratama, Muhammad Isbar; Lismayani, Angri
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7821

Abstract

Investors can allocate their funds in many ways, but stock investment is one of the most popular. To obtain a favorable return and minimize risk, investors must consider several factors in order to achieve optimal investment outcomes. The formation of a stock portfolio serves as a means for investors to maximize their investment performance. The objective of this study is to calculate the expected return and portfolio risk to determine the efficient portfolio among financial companies listed on the Indonesia Stock Exchange. The calculations identify three portfolio combinations as the efficient ones. Portfolio 1, with a fund proportion of 40% : 60%, yields an expected return of 0.00032 or 0.032% and a portfolio risk of 0.059 or 5.9%. Portfolio 2 has an expected return of 0.0128 or 1.28% and a portfolio risk of 0.0504 or 5.04%. Portfolio 3 yields an expected return of 0.0057 or 0.57% and a portfolio risk of 0.0667 or 6.67%. Based on these results, Portfolio 2 is identified as the efficient portfolio, as it provides the highest expected return, albeit with relatively high risk. This type of investment is typically preferred by risk-seeking investors, who are inclined toward high-risk, high-return opportunities
Mathematics and Culture: Affine Transformation Representation of Atakkae Traditional House in Wajo Regency Using Blender Software Ja’faruddin, Ja’faruddin; Chen, Wen Haw; Oeitama, Whennie Youngger; Padasasih, Andi Ismudiah; Wijayana, Widhi Kesawa; Murnianti, Murnianti; Rahman, Nurul Qalbi; Utami, Indah Tri Wira
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.7843

Abstract

This study examines the application of affine transformations to the geometric structure of the Atakkae traditional house in Wajo Regency, South Sulawesi, in the context of ethnomathematics. This traditional house, known as Saoraja La Tenri Bali, is a typical Bugis stilt house with architectural uniqueness in the form of 101 pillars and large dimensions. Affine transformations were used to analyze the geometric elements of this traditional house, including scale, rotation and shear, in order to understand the mathematical relationships in traditional design. This research used a descriptive qualitative approach with data collected through direct observation and literature review. Geometric visualization was conducted using Blender software, which utilizes matrix transformation to model the structure of the traditional house in detail. The results show that the geometric elements in Atakkae traditional houses reflect a combination of local wisdom and mathematical principles, which are relevant in preserving culture while providing new insights into the relationship between mathematics and tradition. The findings are expected to contribute to the documentation of cultural heritage and the development of ethnomathematics learning.

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