cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Windarto
Contact Email
windarto@fst.unair.ac.id
Phone
+62315936501
Journal Mail Official
conmatha@fst.unair.ac.id
Editorial Address
Study Program of Mathematics, Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia Kampus C UNAIR Jl. Mulyorejo Surabaya, Jawa Timur 60115
Location
Kota surabaya,
Jawa timur
INDONESIA
Contemporary Mathematics and Applications (ConMathA)
Published by Universitas Airlangga
ISSN : -     EISSN : 26865564     DOI : https://doi.org/10.20473/conmatha
Core Subject : Science, Education,
Materials Science & Nanotechnology Mathematics
Contemporary Mathematics and Applications welcome research articles in the area of mathematical analysis, algebra, optimization, mathematical modeling and its applications include but are not limited to the following topics: general mathematics, mathematical physics, numerical analysis, combinatorics, optimization and control, operation research, statistical modeling, mathematical finance and computational mathematics.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 82 Documents
 5   6   7   8   9 
Forecasting the Consumer Price Index in Banyumas Regency Using Double Exponential Smoothing with Proportional Integral Derivative Controller Ashar, Nurcahya Yulian; Abiyyin, Maulana Fatih
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 2 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i2.74764

Abstract

The Consumer Price Index (CPI) is a crucial measure of inflation and the cost of living within a specific region. Accurate CPI forecasts are essential for policymakers, businesses, and stakeholders to make informed decisions. This study utilizes the Double Exponential Smoothing (DES) method to forecast the CPI for Banyumas Regency in January 2025, employing monthly CPI data from January 2020 to December 2024. The DES method was selected due to the observed upward trend in historical CPI data. Python programming was employed to optimize the smoothing parameters α and β, and the results were evaluated using Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). The forecasted CPI for January 2025 is 106.36, with high accuracy indicators, including a MAPE of 0.26%, demonstrating that DES is a reliable model for CPI forecasting in Banyumas Regency.
Nilpotent Graphs of Rings of Integer Modulo: Structural Properties and Topological Indices Deny Putra Malik; Gusti Yogananda Karang; Qurratul Aini; I Gede Adhitya Wisnu Wardhana
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 1 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i1.71177

Abstract

Nilpotent elements in modular rings play a fundamental role in understanding the algebraic structure of rings and their applications in various mathematical domains. Motivated by the need to explore the interplay between algebraic and combinatorial representations, this study introduces and investigates nilpotent graphs constructed from rings of integers modulo prime powers. We begin by characterizing nilpotent sets and establishing theorems that describe their distribution and algebraic behavior. Using these characterizations, we construct nilpotent graphs, where vertices represent nilpotent elements and edges reflect their interactions. The structural properties of these graphs are examined, and several well known topological indices, such as the Zagreb, Harary, Hyper Wiener, Randić, Harmonic, Sombor, and Schultz indices, are computed to quantify connectivity, complexity, and centrality. The results reveal meaningful patterns that bridge ring theory and graph theory.
Utilization of GEE for Mapping Land Cover Changes in Settlements Before and After the 2018 Lombok Earthquake in North Lombok Regency Lia Fitta Pratiwi; Luzianawati; Nuzla Af'idatur Robbaniyyah; Kurnia Ulfa; Muhammad Rijal Alfian
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 1 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i1.76412

Abstract

A major earthquake struck Lombok, West Nusa Tenggara, in 2018, causing significant infrastructure damage, including in North Lombok Regency. This study aims to analyze land cover changes in North Lombok Regency before and after the earthquake using Sentinel-2 Level-1C satellite imagery. Through supervised classification using the Maximum Likelihood method, changes in the area of various land cover types, such as Bare Land, Paddy Field, Dense Vegetation, Water Bodies, and Built-up Areas, were identified and analyzed temporally in 2017, 2020, and 2023. The results show that the earthquake caused drastic changes in land cover in the study area, particularly a decrease in the area of dense vegetation and an increase in the area of bare land. These changes indicate significant ecosystem disruption caused by the earthquake. Subsequently, a recovery trend was observed in the 2020-2023 period. Changes in land cover, especially in built-up areas and bare land, are consistent with the earthquake's impact and subsequent reconstruction efforts.
Cryptocurrency Price Prediction Using Long Short Term Memory Algorithm and Moving Average Convergence Divergence Abiyyu Dicky Pratama; Auli Damayanti; Edi Winarko
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 1 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i1.76496

Abstract

Cryptocurrency is one of the digital assets that is increasingly popular for investment in Indonesia. However, the price movements of cryptocurrencies tend to be volatile, as prices can change at any time and are not easy to predict. This study aims to predict cryptocurrency price movements using the Long Short-Term Memory Algorithm (LSTM) and Moving Average Convergence Divergence (MACD). LSTM is an algorithm used to generate optimal weights and biases in modeling cryptocurrency data, while MACD is used to analyze trends and momentum in cryptocurrency prices. The data used consists of daily closing prices of Bitcoin (BTC), totaling 809 data points. The data is divided into 70% (566 data) for the training process and 30% (243 data) for the testing process. From this data, patterns are formed with five inputs and one output, resulting in 561 patterns for the training process and 238 patterns for the testing process. The LSTM and MACD processes for predicting cryptocurrency include procedures for data input, data division, parameter initialization, LSTM calculation, average error evaluation, and MACD calculation. Based on the program implementation, with several parameter values, the average error difference obtained during the training stage is 0.0695 and 0.0303 during the testing stage. Because the average error difference obtained is relatively small, this indicates that LSTM-MACD is capable of recognizing data patterns and predicting data effectively.
Super Edge-Magic Total Labelings of ?? × ?? With ?? Pendants Rica Amalia; Kholifatur Rohmah; Khairil Anam
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 1 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i1.85975

Abstract

A graph ? is defined as a finite nonempty set ? of objects called vertices (vertex for singular) together with a possibly empty set of ? ⊆ {{?, ?} ∣ ?, ? ∈ ?} called edges. One of interesting topic in graph theory is graph labelling. Super edge magic total labeling is a special form of total edge magic labeling, where vertex labels must come from the set {1,2,…,|?|}, while edge labels come from the remainder of the set {1,2,…,|?|+|?|}. Formally, this labeling is a bijective mapping: ? : ? ∪ ?→{1,2,…,|?|+|?|} with the following conditions: ?(?) ∈ {1,2,...,|?|} ∀? ∈ ? where there is a constant number ? such that for every edge ? = ?? ∈ ?, ?(?) + ?(?) + ?(?) = ?. The main focus of this research is to determine the existence and construction of super edge-magic total labeling on cartesian product graph ?? × ?? with additional pendants. In this study, we get that ?? × ?? with pendants are graphs with super edge-magic total labelling’s by constructing the labeling of their vertices and edges, thereby obtaining a magic constant ?.
Performance Evaluation of the Gated Recurrent Unit Model in Predicting the Closing Stock Price of PT Aneka Tambang Tbk Wahyu Erinna Ratih; Safira Fitri Anggraini; Tri Maryono Rusadi
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 1 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i1.86603

Abstract

Stock price prediction is a crucial task in financial market analysis due to its impact on investment decision-making. This study aims to apply the Gated Recurrent Unit (GRU) model to forecast the stock price of ANTM.JK using historical time series data. A total of 12 experimental models were developed by varying data split ratios, window sizes, epochs, and batch sizes to identify the optimal model configuration. Model performance was evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The results show that the GRU model is capable of predicting stock prices with high accuracy, achieving an accuracy of 98.02%. The RMSE values ranged from 57.78 to 91.09, MAE values ranged from 38.20 to 62.87, and MAPE values ranged from 1.98% to 3.22%. The best-performing model was Model 7, with a 70:30 training–testing split, a window size of 30, 50 epochs, and a batch size of 16, which produced the lowest error values among all models. These findings indicate that GRU is an effective and reliable approach for modeling nonlinear and dynamic stock price time series and has strong potential for supporting financial market analysis and investment decision-making.
Modelling the Effect of Toxicants in Water and Sediments on Aquatic Population Kenneth Ojotogba Achema; Danjuma Jibrin Yahaya; Charity Jumai Alhassan
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 2 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i2.81566

Abstract

A mathematical model to study the effect of toxicants in water and sediments on aquatic population is proposed and analyzed. The model has six possible equlibria. By applying stability theory, it was demonstrated that the overall species population stabilizes at an equilibrium level. However, it was found that as the toxicant emission rates increases, the aquatic population density was severely affected and the aquatic population decreased significantly.
The Impact of Investment Value and Number of Projects on Employment in Surabaya’s Leading Economic Sectors Karisma Indra Pitaloka; Dian Yuliati; Hani Khaulasari
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 2 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i2.85955

Abstract

This study aims to analyze the impact of investment value and the number of projects on employment in Surabaya’s leading economic sectors during the 2020–2024 period, motivated by fluctuations in investment realization and labor absorption. The data used are sectoral panel data obtained from the Surabaya City Investment and One-Stop Integrated Service Office (DPMPTSP). The analytical method applied is panel data regression, with model selection conducted using the Chow Test and Lagrange Multiplier Test. The results indicate that the Common Effect Model (CEM) is the most appropriate model. The estimation results show that both the number of projects and investment value have a positive and statistically significant effect on employment, as indicated by t-statistics of 24.85441 (p-value = 0.00) and 2.220927 (p-value = 0.037), respectively. Simultaneously, the model is significant based on the F-test (F = 381.9359; p-value = 0.00). The model demonstrates strong explanatory power, with an R-squared value of 0.972006 (97.20%) and an adjusted R-squared of 0.969461, indicating that most of the variation in employment can be explained by the independent variables. Furthermore, classical assumption tests confirm that the model satisfies normality (Jarque-Bera p-value = 0.1064), shows no multicollinearity (VIF < 10), no autocorrelation (Breusch–Godfrey p-value = 0.8476), and no heteroscedasticity (Goldfeld–Quandt p-value = 0.9684). These findings suggest that increasing the number of projects has a more substantial effect on employment compared to increasing investment value, highlighting the importance of expanding labor-intensive projects to enhance job creation.
Predicting Customer Numbers at PT PLN (Persero) West Nusa Tenggara Regional Main Unit Using the Prophet Time Series Model Rida Alkausar Hardi; Rio Satriyantara; Yunita Septriana Anwar; I Gede Adhitya Wisnu Wardhana
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 2 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i2.88166

Abstract

Electricity is a fundamental need for modern society, and in developing regions such as West Nusa Tenggara, the continuous growth in the number of customers requires PT PLN (Persero) to conduct effective resource planning to prevent potential energy crises. This study aims to predict the growth of PLN’s customer numbers using the Facebook Prophet time series model. A quantitative approach was applied using monthly customer data from PT PLN (Persero) covering the period from January 2019 to December 2024. The model was optimized through a hyperparameter tuning process, and its performance was evaluated using the Mean Absolute Percentage Error (MAPE) metric. The results demonstrate that the optimized model achieved a MAPE of 0.27% during cross-validation. Analysis of the results indicates that the model effectively captured long-term growth trends and seasonal fluctuations. These findings suggest that the Prophet model can serve as a technical reference for forecasting customer numbers, potentially supporting strategic decision-making and resource allocation at PT PLN (Persero).
Spectral Properties and Determinant Formulas for a Two-Parameter Family of Symmetric Circulant Matrices Eric Machisi; Anas Mahmoud Ahmad Alrababah; Abdullah Kurudirek
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 2 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i2.89073

Abstract

This paper investigates the spectral properties of the symmetric circulant matrix ??(?,?)=circ (?,?,0,…,0,?), where ?,?∈ℝ and ?≥3. While the eigenvalue structure of general circulant matrices is well understood, explicit and unified characterizations for specific structured subclasses remain of interest. In this work, we derive closed-form expressions for the eigenvalues and provide a complete characterization of the positive definiteness of this matrix family, explicitly highlighting the role of the parity of ?. In addition, we obtain a compact determinant formula using Chebyshev polynomials, yielding an analytically tractable condition for singularity. The results establish a direct connection between circulant matrix theory and classical trigonometric polynomial identities, providing a unified framework that links spectral properties, determinant structure, and parity effects. These findings extend existing formulations by providing explicit, structurally transparent results for this class of symmetric circulant matrices.

Page 8 of 9 | Total Record : 82

 5   6   7   8   9 

Filter by Year

2019 2026


Reset
Filter By Issues
All Issue Vol. 8 No. 2 (2026) Vol. 8 No. 1 (2026) Vol. 7 No. 2 (2025) Vol. 7 No. 1 (2025) Vol. 6 No. 2 (2024) Vol. 6 No. 1 (2024) Vol. 5 No. 2 (2023) Vol. 5 No. 1 (2023) Vol. 4 No. 2 (2022) Vol. 4 No. 1 (2022) Vol. 3 No. 2 (2021) Vol. 3 No. 1 (2021) Vol. 2 No. 2 (2020) Vol. 2 No. 1 (2020) Vol. 1 No. 2 (2019) Vol. 1 No. 1 (2019) More Issue