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Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
Published by Universitas Negeri Gorontalo
ISSN : 20879393     EISSN : 27763706     DOI : -
Core Subject : Science, Education,
Computer Science & IT Mathematics
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi is a national journal intended as a communication forum for mathematicians and other scientists from many practitioners who use mathematics in the research. Euler disseminates new research results in all areas of mathematics and their applications. Besides research articles, the journal also receives survey papers that stimulate research in mathematics and its applications. The scope of the articles published in this journal deal with a broad range of mathematics topics, including: Mathematics Applied Mathematics Statistics and Probability Applied Statistics Mathematics Education Mathematics Learning Computational Mathematics Science and Technology
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 221 Documents
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Sistem Rekomendasi Produk Skincare Halal Berbasis Komposisi Bahan menggunakan Metode Simple Additive Weighting Velisa Amanda Putri; Sri Winiarti; Nurkhasanah Nurkhasanah
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.38877

Abstract

The rapid development of the skincare industry has increased the complexity of product ingredient composition, making it difficult for consumers to determine products that suit their skin needs. This challenge is even more complex for Muslim consumers who must consider the halal aspects of skincare product ingredients. Lack of understanding regarding ingredient content, skin problems, skin type, and product halal status leads to a high risk of errors in skincare selection. Therefore, this study aims to implement a halal skincare product recommendation system based on ingredient content using the Simple Additive Weighting (SAW) method. The system uses seven criteria: ingredient content, halal logo, BPOM logo, ingredient safety, skin problems, skin type, and age. Alternatives consist of 61 skincare products, 22 facial washes, 23 moisturizers, and 16 sunscreens obtained from questionnaires with 300 respondents. The novelty of this study lies in the integration of halal aspects, skin conditions, and government regulations in a multi-criteria decision-making (MCDM)-based decision-making model. The SAW method is used to weight and rank alternatives based on preference values. The results show that the SAW method is able to generate product recommendations according to user characteristics. For normal-dull skin conditions, the best recommendations are Emina Bright Prebiotic Tranexamic (0.7800), Somethinc Skin Goals Moisture Silk Creme (0.8300), and Wardah UV Shield Active Protection Serum SPF 50 PA++++ (0.7050). For sensitive-acne skin conditions, the best recommendations are Skintific 3x Acid Acne Gel Cleanser (0.9750), Something Acne Treatment Moisturizer Gel (1.0000), and Wardah UV Shield Acne Calming Sunscreen SPF 50 PA++++ (0.8300). The results of the Black Box Testing showed that all system functions were running well, while the expert judgment by a dermatology specialist showed that the system was running well.
Penerapan Modified Jackknife Kibria-Lukman Regression dengan Koreksi Autokorelasi Prais-Winsten pada Nilai Tukar Rupiah terhadap Dolar Amerika Serikat Chrisadna Patricia Kabangnga; A. Muthiah Nur Angriany; Raupong Raupong
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.38482

Abstract

The movement of the Indonesian Rupiah exchange rate against the United States Dollar (USD) experienced volatility during the 2021-2024 period, thus requiring precise analysis to identify the factors influencing it. This modeling can be conducted through multiple linear regression analysis; however, parameter estimation using Ordinary Least Squares (OLS) is often inefficient and prone to producing large variances due to the violation of assumptions in the form of multicollinearity and autocorrelation. Therefore, this study aims to model the Rupiah exchange rate against the USD for the 2021–2024 period and identify the significantly influencing factors using the Modified Jackknife Kibria-Lukman Regression (MJKLR) method with Prais-Winsten (PW) autocorrelation correction. Autocorrelation handling was performed through the PW correction, followed by MJKLR modeling on the PW-transformed data to reduce the impact of multicollinearity. The results showed that the MJKLR-PW estimator provided a more efficient performance compared to OLS-PW and KLR-PW, with an estimator MSE of 0.1877, RMSE of 326.1730, and an adjusted R² value of 72.54%. The variables of money supply, interest rate, total exports, and total imports had a significant effect on the Rupiah exchange rate at a 5% significance level. In conclusion, the combination of MJKLR and PW is effective in modeling the Rupiah exchange rate against the USD that has autocorrelation and multicollinearity problems. Empirically, this study indicates that the stability of the Rupiah exchange rate relies heavily on macroeconomic fundamentals, particularly monetary policy and the trade balance.
Homomorfisma pada (R,S)-Modul Ira Lefiana; Suroto Suroto; Ari Wardayani; Najmah Istikaanah
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.38237

Abstract

The (R,S)-module structure is a generalization of the (R,S)-bimodule structure. The (R,S)-bimodule structure itself is an extension of the R-module structure. Thus, some properties that apply to R-modules can be extended to (R,S)-modules. In this article, we discuss the (R,S)-module homomorphism and its properties. The method used is to add a ring S action on the right to the R-module homomorphism and extend the compatibility condition to the (R,S)-bimodule homomorphism. The result is that the (R,S)-module homomorphism can be constructed from the R-module homomorphism by adding a ring S action from the right and extending the compatibility condition to the (R,S)-bimodule homomorphism with the associative condition of simultaneous action to obtain the left-linear and right-linear conditions simultaneously on the (R,S)-module homomorphism. Furthermore, the kernel and image structures as (R,S)-submodules and (R,S)-factor module structures must also maintain the consistency of the left action of the ring R as well as the right action of the ring S simultaneously.
Representasi Matematika di Media Sosial sebagai Prediktor Persepsi Publik terhadap Matematika: Analisis Regresi Logistik Ordinal Zakiyatur Rosidah; Sri Harini
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.38214

Abstract

Public perception of mathematics is often characterized by negative views, despite its fundamental role in everyday life and human development. This study aims to examine the effects of mathematics anxiety, teacher instructional quality, mathematics learning experience, and the representation of mathematics on social media on public perceptions of mathematics. A quantitative approach with an explanatory survey design was employed. Data were collected through an online questionnaire using a five-point Likert scale from 100 respondents from the general public who had previously participated in formal mathematics education. Ordinal logistic regression was used for data analysis. The results indicate that the regression model is statistically adequate and demonstrates good model fit. Mathematics anxiety, teacher instructional quality, and mathematics learning experience do not have a significant effect on public perceptions of mathematics. In contrast, the representation of mathematics on social media has a positive and significant influence on public perception. These findings suggest that contemporary experiences through social media play a more prominent role in shaping public perceptions of mathematics than past formal learning experiences. This study contributes theoretically to the literature on mathematics perception in public contexts and provides practical implications for developing effective strategies to promote positive representations of mathematics in digital spaces.
Evaluasi Portofolio Optimal IDX30 Berbasis Safety First Criterion Menggunakan Rasio Sharpe, Sortino, dan Treynor Abdul Maulana; Yundari Yundari; Evy Sulistianingsih
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.38342

Abstract

Constructing an optimal portfolio allows investors to achieve expected returns within an acceptable risk level. Unlike conventional approaches focusing on the risk--return trade--off, the Safety First Criterion (SFC) method minimizes the probability of portfolio returns falling below an investor's specified minimum threshold. This study constructs an optimal stock portfolio from the IDX30 index for the period February 5, 2024--July 28, 2025, using Roy’s, Kataoka’s, and Telser’s criteria, and evaluates performance through Sharpe, Sortino, and Treynor indices. The dataset comprises weekly closing stock prices of IDX30 constituents. The analysis calculates returns and expected returns, selects stocks with positive expected returns, constructs optimal portfolios via the Lagrange multiplier approach for each SFC criterion, and evaluates risk-adjusted performance. This study uniquely applies and compares three SFC criteria simultaneously using three distinct evaluation metrics. Results show that the Roy portfolio comprises ANTM, INDF, and PGAS; the Kataoka portfolio includes BRPT, INDF, and PGAS; and the Telser portfolio consists of ANTM, BRPT, and PGAS. The Roy portfolio generates the highest Sharpe Index (0.1453) and Treynor Index (0.00532), demonstrating superior performance against total and systematic risk compared to other portfolios. Meanwhile, the Telser portfolio achieves the highest Sortino Ratio (0.28566), showing the best capability in managing downside risk. Overall, the Roy portfolio emerges as the most optimal choice because it excels in two out of three evaluation indicators, proving that Roy's criterion produces the best risk--return balance during the study period.
Penerapan Fuzzy Time Series Markov Chain dalam Peramalan Harga Cabai Merah Berbasis Data Harian di Kabupaten Banyumas Dian Kartika Sari; Iqsyahiro Kresna A; Diah Septiani
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.37987

Abstract

Relatively high fluctuations in red chili prices often create challenges in maintaining food commodity price stability in various regions, including Banyumas Regency. Price changes influenced by weather conditions, supply availability, and market demand make red chili prices difficult to predict accurately. Therefore, a forecasting method capable of modeling uncertain and fluctuating time series data is needed. This study aims to forecast red chili prices in Banyumas Regency using the Fuzzy Time Series Markov Chain (FTSMC) model. The study used 317 daily price data points collected from January 1, 2025, to March 10, 2026. The research stages included determining the universe of discourse, constructing intervals and fuzzy sets, fuzzification, forming Fuzzy Logical Relationships (FLR) and Fuzzy Logical Relationship Groups (FLRG), constructing the Markov transition probability matrix, and performing defuzzification to obtain prediction values. The contribution of this study lies in applying the FTSMC method to model regional red chili price fluctuations with volatile characteristics and evaluating its performance using Mean Absolute Percentage Error (MAPE). The results indicate that the Fuzzy Time Series Markov Chain method can effectively model the fluctuation patterns of red chili prices. Based on the evaluation results, the prediction model achieved a MAPE value of 3.19\%, indicating very high prediction accuracy. Therefore, the FTSMC method can be used as an effective alternative forecasting model for predicting red chili prices and supporting decision-making related to food commodity price control in Banyumas Regency.
Pendekatan Metode Prophet dalam Peramalan Nilai Ekspor Jawa Tengah untuk Perencanaan Ekonomi Daerah Rio Wahyu Saputra; Mujiati Dwi Kartikasari
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.37781

Abstract

Export plays an important role in promoting regional economic growth. Central Java Province, as one of the regions with significant international trade activities, contributes to the national export value. However, the export value of Central Java has shown fluctuations influenced by various factors, such as global economic dynamics, the COVID-19 pandemic, and trade policies. Therefore, a forecasting method capable of producing accurate predictions is needed to support regional economic planning and policy decision-making. This study aims to forecast the export value of Central Java for the period 2019–2025 using the Prophet method based on monthly data obtained from the Central Java Provincial Statistics Agency (BPS). The dataset was divided into 70% training data and 30% testing data. The modelling process utilized the trend, seasonality, and holiday components available in the Prophet method. Model performance was evaluated using the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) accuracy measures. The results show that the best-performing model yields an RMSE of 54.094 and an average MAPE of 16.2317%, indicating a good level of forecasting accuracy. The forecasting results also indicate that the export value of Central Java is expected to increase until the end of 2025, with the highest export value predicted to occur in December at approximately 1,028.44 million US dollars.
SAR-FEM Spatial Panel Regression for Spatio-Temporal Modeling of Stunting Cases in Indonesia Zakiyah Mar'ah; Isma Muthahharah; Sitti Masyitah Meliyana R
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.38016

Abstract

Stunting remains a crucial issue in Indonesia, with a prevalence of 21.5\% in 2023. This study aims to model the number of stunting cases in toddlers in 34 provinces in Indonesia (2020--2022) using Spatial Panel Regression to address the weaknesses of traditional regression that ignore the effects of spatial and temporal dependencies.  Predictor variables analyzed include the percentage of malnutrition, underweight, poor population, access to basic health facilities, and access to drinking water services. The selection of the best model specification was carried out using the Chow test, Hausman, and the Bayesian log-marginal posterior probabilities approach. The results of the diagnostic test confirmed the existence of spatial and temporal autocorrelation in stunting cases. Based on the Bayesian analysis, the Spatial Autoregressive (SAR) Fixed Effect (FEM) model was selected as the most optimal model with a log-marginal value of -21.360, a posterior probability of 0.630, and a coefficient of determination ($R^2$) of 0.880. Impact analysis shows that the percentage of underweight children and access to health facilities have a significant direct effect on stunting in a region. However, no significant indirect spillover effect from neighboring provinces was found. Therefore, policymakers are advised to formulate stunting management strategies that focus on precisely addressing local determinants in each region.
Total Absolute Difference Edge Irregularity Strength of Several Ladder-type Graphs Faisal Susanto; Kristiana Wijaya
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.39334

Abstract

This paper studies edge irregular total absolute difference labeling for several classes of ladder-related graphs, namely triangular ladders, alternating triangulated ladders, and double triangulated ladders. By deriving coinciding lower and upper bounds, the precise values for the total absolute difference edge irregularity strength of these graphs are successfully established.
Analisis Komparatif Model SARIMAX, XGBoost, dan LSTM untuk Peramalan Curah Hujan Bulanan di Kota Makassar Mohammad Zahid; Rahmawati Rahmawati; Andi Seppewali; Bintang Guntur
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 2 August 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i2.39072

Abstract

Rainfall is one of the important meteorological elements in various sectors, such as agriculture, water resource management, and hydrometeorological disaster mitigation. This study aims to compare the performance of Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX), Extreme Gradient Boosting (XGBoost), and Long Short-Term Memory (LSTM) models in monthly rainfall forecasting in Makassar City. The data used were monthly meteorological data from January 2000 to December 2024 obtained from NASA POWER with a total of 300 observations. The variables used include rainfall, temperature, humidity, wind speed, pressure, and solar radiation. The research stages consisted of data preprocessing, exploratory data analysis, stationarity testing using the Augmented Dickey-Fuller (ADF) test, SARIMAX, XGBoost, and LSTM modeling, and model evaluation using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R^2). The results showed that the XGBoost model achieved the best performance with an RMSE value of 2.5441 and an R^2 value of 0.8063, while the SARIMAX model produced the lowest MAPE value of 39.2614%. Meanwhile, the LSTM model showed less optimal performance with an RMSE value of 5.2125 and an R^2 value of 0.1646. The results indicate that the boosting-based machine learning approach is more effective in handling nonlinear relationships in monthly rainfall data compared to classical statistical and deep learning models on limited datasets.

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