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Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Published by Universitas Jenderal Soedirman
ISSN : 20851456     EISSN : 25500422     DOI : -
Core Subject : Education,
Mathematics
JMP is a an open access journal which publishes research articles, reviews, case studies, guest edited thematic issues and short communications/letters in all areas of mathematics, applied mathematics, applied commutative algebra and algebraic geometry, mathematical biology, physics and engineering, theoretical bioinformatics, experimental mathematics, theoretical computer science, numerical computation and applications of systems, partial differential and differential equations, integral and integral differential equations and mathematical modeling.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 375 Documents
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MODEL PREDATOR-PREY DENGAN KONTROL OPTIMAL PADA BUDIDAYA BAWANG MERAH Wibowo, Rohman Prasetyo; Adi, Yudi Ari
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 17 No 1 (2025): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2025.17.1.15722

Abstract

Shallot farming creates a predator–prey interaction between leaf miner flies as pests and pesticides as control agents applied by farmers. This article discusses the application of a predator–prey mathematical model to shallot cultivation in Selopamioro Village, Imogiri, Bantul. The interaction between predator and prey is mathematically formulated using the Holling-Tanner response function and analyzed numerically using the fourth-order Runge-Kutta method to examine equilibrium point stability. The model is further developed by introducing optimal control in the form of manual pest removal and reduced insecticide dosage, aiming to improve shallot productivity through more effective pest management. The state and co-state conditions are solved using the Forward–Backward Sweep method based on the fourth-order Runge-Kutta on the Hamiltonian function. Simulation results show that the implementation of control significantly reduces the leaf miner fly population from 997 to 141 individuals and decreases the duration of insecticide application from 39 days to just 10 days
PENCARIAN RUTE OPTIMAL TRAVELING SALESMAN PROBLEM DENGAN ALGORITMA ANT COLONY OPTIMIZATION (ACO) Nuraliya, Aliffia Yasya; Nurshiami, Siti Rahmah; Jajang, Jajang
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 17 No 1 (2025): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2025.17.1.15866

Abstract

The implementation of product distribution requires transportation to deliver products effectively across various locations. Challenges encountered during this process include varying distribution sites, travel distances, time taken for product delivery, transportation costs, and other related factors. To address these challenges, selecting an efficient travel route is crucial. The Traveling Salesman Problem (TSP) serves as a practical application of graph theory in tackling such distribution issues. The Ant Colony Optimization (ACO) algorithm emerges as a viable solution for route optimization, particularly in addressing TSP challenges to derive optimal routes. Results derived from the TSP calculations utilizing ACO, executed through the Matlab R2018a application, employed parameters of
PENERAPAN METODE JACKKNIFE RIDGE REGRESSION UNTUK MENGATASI MULTIKOLINEARITAS (STUDI KASUS: KEMISKINAN DI PROVINSI JAWA TENGAH) Yulinda, Nisa Tri; Supriyanto, Supriyanto; Guswanto, Bambang Hendriya
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 17 No 1 (2025): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2025.17.1.16050

Abstract

Multicollinearity is one of the problems in linear regression that can lead to unstable parameter estimates. This study aims to address multicollinearity issues in multiple linear regression models applied to poverty data in Central Java Province using the Jackknife Ridge Regression method. The data used are secondary data from the Central Java Provincial Statistics Agency for 2022-2023, with the poverty rate as the dependent variable and eight independent variables representing poverty-related factors. This research was conducted using a literature review method and data analysis with R software. The results show that the Jackknife Ridge Regression method successfully mitigates multicollinearity, producing an accurate model. The final model indicates that average years of schooling, life expectancy, labor force participation rate, human development indeks, and regional gross domestic product have a negative effect on the poverty rate. These findings highlight the importance of improving education quality, healthcare, human development, and access to basic infrastructure as key strategies for poverty alleviation in Central Java Province.
PENERAPAN METODE REGRESI ROBUST ESTIMASI-M UNTUK KASUS DATA PDRB PERKAPITA PROVINSI JAWA TENGAH TAHUN 2021 Rizqi, Safina Sabila; Nurhayati, Nunung; Maryani, Sri
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 17 No 1 (2025): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2025.17.1.16165

Abstract

Economic growth and a more even distribution of income are needed to improve social welfare. One of the most important indicators for measuring the economic growth of a region is the growth value of the gross regional domestic product (GRDP). The size of the gross regional domestic product (GRDP) in Central Java can be predicted using a regression model. One of the estimation methods used in linear regression models is the LS method. The use of LS method becomes less appropriate if there is a violation of classical assumptions caused by outliers in the data. The M-estimation robust regression method can be used to solve outliers problem in the data. In this study, the M-estimation robust regression method was applied to the case of district or city GDP per capita data in Central Java Province in 2021. The weighting functions used were the Tukey bisquare weighting function and the Huber weighting function. The adjusted R-squared value and mean squared error (MSE) are used to determine the criteria for the best model. Based on the research results, it can be concluded that robust M-estimation regression with the Huber weighting function is the optimal parameter estimate for determining the best model. This is because the Huber weighting function has a higher adjusted R-squared value than the bisquare Tukey weighting function, and the Huber weighting function has a lower MSE than the bisquare Tukey weighting function
PERBANDINGAN KEAKURATAN METODE MACK CHAIN LADDER DAN BORNHUETTER -FERGUSON DALAM ESTIMASI CADANGAN KLAIM Firdausy, Andini Erika; Oktaviarina, Affiati
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 17 No 1 (2025): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2025.17.1.16200

Abstract

Abstract: Risk is an uncertain event that can cause losses, both financially and non-financially, so insurance is needed as a form of protection. In insurance, claim reserves are an estimate of the funds that a company must prepare to pay claims in the future. This study aims to compare two claim reserve estimation methods, namely Mack Chain Ladder and Bornhuetter-Ferguson, and evaluate their accuracy using Root Mean Square Error (RMSE). The Mack Chain Ladder method uses cumulative triangle run-off data, while the Bornhuetter-Ferguson method combines the loss ratio approach with incremental triangle run-off data. The data used comes from an insurance company in the United States with a claim period of 2013–2022. The estimation results show that the claim reserve with the Mack Chain Ladder method is 1,406,731 million USD with an RMSE value of 199,826, while with the Bornhuetter-Ferguson method it is 1,386,492 million USD with an RMSE value of 83,251. These results indicate that the smaller RMSE value is obtained by using the Bornhuetter-Ferguson method. Keywords: insurance, Bornhuetter-Ferguson, claims reserve, Mack Chain Ladder

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