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E-Jurnal Matematika
Published by Universitas Udayana
ISSN : -     EISSN : 23031751     DOI : https://doi.org/10.24843/MTK
Core Subject : Education,
Mathematics
The scope of the E-Jurnal Matematika includes analysis, algebra, topology, graphics, numerical simulation approaches or what is known as numerical analysis, optimal control, queuing problems, optimization, finance, biomathematics, industrial mathematics, financial mathematics, and others.
Arjuna Subject : Matematika - Matematika Terapan
Articles 39 Documents
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OPTIMASI SPLIT DELIVERY VEHICLE ROUTING PROBLEM DENGAN KETIDAKPASTIAN PERMINTAAN: STUDI KASUS PT. REZEKI SURYA GASINDO RTS SYAKILA YUANZA; SYAMSYIDA ROZI; NIKEN RARASATI
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p515

Abstract

Distribution activities at PT Rezeki Surya Gasindo face challenges due to limited vehicle capacity and uncertain customer demand, which complicate route planning and may affect distribution performance. This study aims to model and optimize the Split Delivery Vehicle Routing Problem (SDVRP) under demand uncertainty. The problem is formulated using Integer Linear Programming (ILP), where demand uncertainty is incorporated into the optimization framework to ensure that the resulting solutions remain feasible under varying customer demands. The model is implemented using Python with the PuLP library and further solved using a Genetic Algorithm based on the company’s distribution data. The results show that the proposed SDVRP model produces a distribution plan with a minimum total travel distance of 54.60 km. The optimal solution consists of two main routes: Route 1 serves Depot – Jalan Baru – Talang Gulo – Depot with a total delivery of 20 cylinders, while Route 2 serves Depot – Talang Gulo – Jeramba Bolong – Jambi Timur – Depot with a total delivery of 20 cylinders. These results demonstrate the applicability of the proposed SDVRP model in generating feasible distribution routes under demand uncertainty.
ANALISIS PERBANDINGAN METODE FUZZY SIMPLEKS DAN KUMAR DALAM OPTIMASI PRODUKSI FULLY FUZZY LINEAR PROGRAMMING NERLI KHAIRANI; RIZAL MUHAIMIN; NAFASA ZAHRI; NAYSLA AURA SIFFA
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p519

Abstract

This study discusses a comparative analysis between the fuzzy simplex method and Kumar’s method in solving production optimization problems based on Fully Fuzzy Linear Programming (FFLP). Production optimization problems in real conditions often involve uncertainty in production costs, resource availability, and market demand fluctuations. Therefore, the FFLP approach is applied because all model parameters, including objective functions, constraints, and decision variables, are represented using trapezoidal fuzzy numbers to better describe uncertainty. This research employed a quantitative comparative approach using simulation data with two decision variables. The optimization model was solved using the fuzzy simplex method and Kumar’s method with the Liou–Wang ranking function. The results showed that both methods produced identical optimal solutions, including the same optimal decision variable values, fuzzy profit values, and number of iterations required to reach optimality. However, Kumar’s method provided a simpler pivot selection process through the use of ranking functions, while the fuzzy simplex method was more effective in maintaining the integrity of fuzzy data throughout the iteration process. Based on the comparative analysis, both methods were proven effective for solving FFLP problems, although they differ in computational complexity and operational procedures.
PERBANDINGAN MODEL PROPHET DAN DEKOMPOSISI STL DALAM PERAMALAN FILM BOX OFFICE RIKARDO JORDAN RAJAGUKGUK; I WAYAN SUMARJAYA; I NYOMAN WIDANA
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p517

Abstract

Box office is the term that used as a movie’s income as well as an indicator of a movie’s success. Forecasting daily box office is important to do because it will be a guidance for producers and distributors in determining a movie’s release date and also as a profit prediction. Daily box office has a large amount of historical data and strong seasonality. Prophet model and seasonal-trend decomposition using Loess (or simply STL decomposition) are some of the forecasting methods that are capable for forecasting daily data with large frequency and strong seasonalities. The goal in this research is to observe the comparison between prophet model and STL decompostion and also to demonstrate each method’s computation to further elaborate on each method’s forecasting performance. The result in this research shows that a modification of prophet model with the addition of holidays as a parameter has the lowest error using root mean square error (RMSE) evaluation with a score of 7.515.225 and using mean absolute percentage error (MAPE) evaluation with a score of 33.62%.
ANALISIS PRIORITAS KEPUTUSAN KONSUMEN DALAM MEMILIH COFFEE SHOP MENGGUNAKAN METODE ANALYTIC HIERARCHY PROCESS NI GUSTI AYU KADEK SARI PURNAMAYANTI; I KOMANG GDE SUKARSA; G. K. GANDHIADI; I PUTU EKA NILA KENCANA
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p518

Abstract

This study aims to determine the priority weights of criteria and sub-criteria, as well as the priority order of coffee shop alternatives based on consumer preferences using the analytic hierarchy process (AHP) method. This study involved 50 respondents consisting of three groups: 5 expert respondents, 30 active respondents, and 15 passive respondents. The hierarchical structure was compiled based on the 4P Marketing Mix framework, which includes four main criteria: product quality, price, location, and promotion, with three sub-criteria each. The three alternatives compared were Kopi Kenangan, Fore Coffee, and Point Coffee. The results of the study from all respondents showed that Price was the criterion with the highest priority weight (0.358), followed by Product Quality (0.237), Promotion (0.213), and Location (0.189). In terms of alternative priorities, Kopi Kenangan ranked first (0.402), Fore Coffee ranked second (0.335), and Point Coffee ranked last (0.261). These findings can serve as a reference for businesses in increasing their competitiveness.
PENDEKATAN TEORI PERMAINAN DALAM MENENTUKAN MODEL HARGA EQUILIBRIUM PADA RANTAI PASOK SORGUM DI DESA KAWALELO YEREMIAS SABON MUKIN; JUSRRY ROSALINA PAHNAEL; MIRA WADU; ROBERUS DOLE GUNTUR
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p512

Abstract

This study aims to analyze the determination of equilibrium prices in the sorghum supply chain involving suppliers, distributors, and retailers using a game theory approach. The research was conducted in Kawalelo Village, Demon Pagong District, East Flores Regency, Indonesia, using primary data collected through interviews and questionnaires administered to 53 respondents, consisting of 42 suppliers, 2 distributors, and 9 retailers. The analysis was carried out by constructing payoff matrices, determining best responses, and identifying Nash Equilibrium strategies. The results indicate that game theory is capable of modeling the strategic interactions among supply chain actors in determining optimal pricing decisions. The equilibrium strategy for the supplier–retailer combination is (High, High), while the equilibrium strategy for the distributor–retailer combination is (Low, High). Factors influencing the formation of equilibrium prices include production and distribution cost structures, purchase and selling price levels, production volume, and interactions among supply chain participants. The resulting equilibrium pricing model demonstrates the potential to improve supply chain efficiency and achieve a more proportional distribution of profits, thereby supporting farmers' welfare and the development of sorghum as an agricultural commodity in East Flores.
EXPLORING SPATIAL HETEROGENEITY OF LIFE EXPECTANCY IN WEST JAVA PROVINCE USING GEOGRAPHICALLY WEIGHTED REGRESSION VERA MAYA SANTI; MUHAMAD RIFAN; WIDYANTI RAHAYU
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p513

Abstract

Life Expectancy Rate (LER) is a key indicator of population health and regional welfare. Significant disparities in LER across districts and municipalities in West Java suggest that the factors influencing life expectancy may vary geographically. Conventional regression models often assume spatial homogeneity and may therefore be inadequate for capturing local variations. This study aims to identify the determinants of LER in West Java by applying Geographically Weighted Regression (GWR) with an adaptive kernel bisquare weighting scheme. Secondary data were obtained from Statistics Indonesia (BPS) of West Java Province and the Open Data Jabar portal. The analysis involved 27 districts and municipalities and examined 11 potential explanatory variables. The results indicate that the influence of predictor variables differs across locations, confirming the presence of spatial heterogeneity in LER determinants. The GWR approach produced 27 local regression models and classified the study area into 10 groups based on similarities in significant factors. Furthermore, the proposed model achieved a coefficient of determination (R²) of 98.86%, indicating a strong ability to explain regional variations in life expectancy. These findings highlight the importance of location-specific policy interventions to improve public health outcomes across West Java.
ANALISIS SISA HASIL USAHA (SHU) KOPERASI DI INDONESIA MENGGUNAKAN REGRESI DATA PANEL VANESSA ANGELICA HERIYANTO; I GUSTI AYU MADE SRINADI; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p521

Abstract

Cooperatives are a vital pillar of the Indonesian economy aimed at improving member welfare, as reflected in the Surplus of Operations (SHU). This study aims to analyze the influence of the number of members, equity, business volume, and external capital on the SHU of Indonesian cooperatives at the provincial level from 2017 to 2023. Given the potential for multicollinearity among independent variables, the research method employs panel data regression analysis integrated with a Ridge Regression approach to produce more stable parameter estimates. The models estimated include the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM), with the best model selected using the Chow and Hausman tests. To ensure estimation accuracy against heteroskedasticity and autocorrelation, this study applies the Robust Standard Error procedure. The results show that the Fixed Effect Model (FEM) with individual effects integrated with Ridge Regression is selected as the best model, yielding an R-squared value of 88.45%. The analysis reveals that equity and business volume have a significant effect on SHU.
PEMODELAN TINGKAT PENGANGGURAN TERBUKA DI PULAU JAWA MENGGUNAKAN METODE REGRESI SPASIAL STEFANI PUTRI WULANDARI; I KOMANG GDE SUKARSA; KETUT JAYANEGARA; I PUTU EKA NILA KENCANA
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p520

Abstract

This study aims to model the open unemployment rate (OUR) in regencies and cities in Java using a spatial regression approach. The analysis uses secondary data from 2024 covering 118 regencies and cities in Java. The response variable is the open unemployment rate, while the predictor variables include the regency/city minimum wage, average years of schooling, labor force participation rate, GRDP growth rate, and population growth rate. The analysis begins with multiple linear regression using the OLS method followed by classical assumption tests. Spatial dependence is examined using Moran’s I with several spatial weight matrices, namely queen contiguity, inverse distance, and k-nearest neighbors. The Lagrange Multiplier test is then conducted to determine the appropriate spatial regression model for each spatial weight matrix. The results show that the spatial autoregressive model (SAR) with the queen contiguity spatial weight matrix is the best model. The selected model produces a coefficient of determination of 69,37% and an AIC value of 352,46. The estimation results indicate that labor force participation rate, and population growth rate significantly affect the open unemployment rate in Java in 2024, while the spatial parameter confirms spatial dependence among regions.
PEMODELAN REGRESI DATA PANEL PADA POLA KEMISKINAN: STUDI KASUS KABUPATEN/KOTA DI PROVINSI BALI NI KADEK NITA PRATIWI; GUSTI PUTU RADHA MAHARANI; MADE SUSILAWATI; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol. 15 No. 3 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i03.p522

Abstract

Poverty remains one of the key indicators of development success and continues to challenge in Bali Province. This study combines panel data regression with comprehensive diagnostic testing and spatial analysis using Local Indicators of Spatial Association (LISA) to examine the determinants of the Poverty Rate (PR) across nine regencies/cities in Bali Province, using 72 observations from 2017–2024. Independent variables include economic growth (EG), unemployment rate (UR), district/city minimum wage in natural logarithm form ( ), and average years of schooling (AYS). Three panel data approaches were estimated, namely the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). Based on the Chow and Hausman tests, FEM was selected as the best model. Diagnostic tests revealed autocorrelation and cross-sectional dependence, so inference relied on Arellano robust standard errors. The results show that minimum wage and average years of schooling significantly reduce poverty, while economic growth and unemployment rate are not significant. LISA analysis identified a significant Low-Low cluster in Denpasar, reflecting spatial spillover in southern Bali. These findings highlight minimum wage policy, education access, and place-based regional strategies as key instruments for poverty reduction.

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