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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 188 Documents
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Analisis Algoritma Canny Edge Detection dengan Tesseract OCR untuk Mendeteksi Pelat Nomor Kendaraan Bermotor Firin, Ananda Sarbaini; Sriani, Sriani
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.34868

Abstract

Identity and vehicle ownership checks are an important routine carried out by security personnel at the State Islamic University of North Sumatra (UINSU) to ensure the legality of vehicles entering and exiting. However, the still manual inspection process of matching vehicle registration certificates (STNK) and license plates is often time-consuming and causes vehicle queues, especially during peak hours. This research applies a combination of the Canny Edge Detection algorithm to detect license plate edges and Tesseract OCR (Optical Character Recognition) to extract text from images. The purpose of this research is to explore the effectiveness of this method in detecting and recognizing two-wheeled vehicle license plates within the UINSU environment, and to provide an alternative solution to the problems of the manual inspection system. The dataset used consists of 125 images of two-wheeled vehicles taken using a mobile phone camera. The research results show that before post-processing was applied, OCR produced an average character accuracy of 81.60% with a CER of 18.40%, while after post-processing, the accuracy increased to 82.49% and the CER decreased to 17.51%. These results confirm that rule-based correction is able to improve character reading errors, although the improvement is moderate and has not completely addressed cases of detection failure in some images. This finding serves as the basis for addressing queuing issues and human resource limitations, while also providing a foundation for the broader development of digital image-based vehicle identification systems across various sectors.
Pemodelan Kasus Tuberkulosis Berdasarkan Faktor Lingkungan Menggunakan Metode Geographically and Temporally Weighted Regression Trezenki, Randa; Novia, Novia; Supangadi, Egita Riyanti; Raihan, Abiyandra Radika; Amelia, Ririn
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.34645

Abstract

Tuberculosis (TB) is currently a global health problem with a high number of cases and deaths, including in Indonesia, which ranks third in the world after India and China. TB cases in the Bangka Belitung Islands Province showed significant fluctuations from 2020 to 2024, indicating the influence of environmental factors on the spread of this disease. This study aims to model the influence of environmental factors, including population density, proper sanitation, and air quality, on the spread of tuberculosis in the Bangka Belitung Islands Province using the Geographically and Temporally Weighted Regression (GTWR) method. The data used in this study are secondary data from seven districts/cities with a total of 35 spatial-temporal observations. The results of the study indicate significant spatial-temporal heterogeneity in the distribution of TB cases. The GTWR model proved to be better than multiple linear regression with an Adjusted R2 value of 0.9733, a lower Akaike Information Criterion (AIC) of 447.23, and a smaller Root Mean Square Error (RMSE) of only 102.66. This study shows that population density and proper sanitation play an important role in increasing or decreasing TB cases, while air quality has a relatively stable effect. The GTWR approach is able to provide a more accurate picture of the pattern of TB spread and serves as a basis for formulating more targeted health interventions in the island region of the Bangka Belitung Islands Province.
Analisis Ambang Batas Curah Hujan Dengan Pendekatan Statistik Median di Daerah Rawan Longsor Samigaluh, Kulon Progo Marganiswati, Yudha Tintana; Maharani, Yohana Noradika; Cahyadi, Tedy Agung; Prasetya, Johan Danu; Prastistho, Widyawanto
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.34962

Abstract

Landslides in tropical regions are often triggered by intense rainfall, causing significant impacts. This study assesses the feasibility of rainfall thresholds for landslide early warning in Kapanewon Samigaluh, Kulon Progo. The objectives include characterizing the rainfall regime, testing the relationship between rainfall and landslide events, evaluating spatial consistency with the landslide hazard map, and establishing and verifying operational thresholds. Landslide data from the BPBD and daily rainfall data from BMKG were processed by aligning the dates and performing quality checks, followed by quantitative analysis. The number of landslide events analysed was 197, with rainfall data collected from a single measurement station. Thresholds were set using the median approach for daily rainfall (CH0) and three-day accumulation (CH−2) from the 2014–2023 series. Verification was conducted on 213 days of the 2024 rainy season using Proportion Correct. Characterization shows a consistent monsoonal pattern with notable interannual variability. A positive tendency is observed between annual rainfall accumulation and landslide frequency. Spatially, around 93% of events occur in high-hazard zones. The median-based thresholds obtained are 31 mm for CH0 and 81 mm for CH−2. Operational verification results in PC values of 84.0% for CH0 and 83.6% for CH−2, indicating acceptable performance. Physically, the intensity of rainfall on event days effectively distinguishes landslide from nonlandslide days, while three-day rainfall accumulation increases risk through soil saturation. These findings support the implementation of locally calibrated thresholds for strengthening early warning, with a focus on monitoring during the rainy season. However, the potential for false alarms related to geological conditions and land-use variability may affect model accuracy. Furthermore, periodic recalibration of thresholds is necessary to address uncertainties resulting from changing hydrometeorological conditions and land-use dynamics.
Klasifikasi Status Kemiskinan Rumah Tangga Berdasarkan Karakteristik Demografi dan Hunian Menggunakan Algoritma Clasification and Regression Tree Winata, Aji Pandu; Aprilia, Dinda; Sriliana, Idhia; Aryati, Fitri; Puspasari, Reny
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.34952

Abstract

Poverty is a multidimensional issue that remains a central focus of development in Bengkulu Province. Decision-tree–based approaches, particularly the Classification and Regression Tree (CART), can be used to classify households based on demographic and housing characteristics. This study utilizes data from the 2024 National Socio-Economic Survey (SUSENAS), with household poverty status as the response variable and six predictor variables including area type, gender of household head, age of household head, number of household members, floor area of the house, and housing ownership status. The analysis consists of data preprocessing, descriptive statistics, data splitting, CART model construction, identification of influential variables, and model evaluation using a confusion matrix. The results show that the number of household members, floor area of the house, and age of the household head are the most influential variables in distinguishing poor and non-poor households. Model evaluation produced an accuracy of 0.73, sensitivity of 0.58, and specificity of 0.75. The accuracy and specificity values indicate adequate classification performance, while the low sensitivity suggests that the model is still less optimal in detecting poor households, partly due to class imbalance in the dataset. These findings indicate that the CART method can be applied to poverty analysis in Bengkulu Province, although further model improvement is needed to enhance its capability in identifying poor households.
Cluster Analysis of BPJS Kesehatan Claim Data in Madiun City to Identify High Claim Patterns and Fraud Indications Shobri, Muhammad Qolbi; Al-Kubro, Putri Balqis; Kawuri, Gabriella Vindy
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.35013

Abstract

The increasing number of BPJS Kesehatan (Health Social Security) service claims in Madiun City poses significant challenges to financing efficiency and raises concerns about potential irregular or fraudulent claims. This study aims to identify high-claim patterns and detect indications of fraud using a data mining approach through the K-Means and Hierarchical Clustering methods. The research employed secondary data consisting of 309 hospital claim records from Madiun City in 2025. The primary variables were the number of claims and total claim costs, supported by additional variables such as age, gender, occupation, type of service, and disease diagnosis. Data analysis involved three main stages: preprocessing, clustering, and cluster quality evaluation using the Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index. Ths Study further compared the performance of both clustering methods, revealing that K-Means achieved superior validity scores across major evaluation metrics. The K-Means method produced the best performance, with a Silhouette Score of 0.617 and a Calinski-Harabasz Index of 419.581, reflecting well-separated and compact cluster structures. Three main clusters were identified-low, medium, and high. The high-claim cluster consisted of participants aged 55 years and above, with a claim frequencies of 2 to 7 claims and total claim costs exceeding IDR 20 million. This cluster was dominated by retirees, housewives, and private-sector employees utilizing inpatient services. Although categorized as a high-risk group, verification results revealed no signs of fraud but rather complex medical needs. These findings suggest that integrating clustering analysis into BPJS Kesehatan’s claim monitoring system can support early anomaly detection and enhance both financing efficiency and claim management integrity.
Implementasi Design Research dalam Pembelajaran Analisis Riil yang Terkoneksi dengan Matematika Sekolah Nur Atiqoh, Khamida Siti; Hafiz, M
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.35095

Abstract

This study aims to describe a learning trajectory for the topics of sequences and its limits in Real Analysis that connects abstract mathematical concepts with school mathematics. The research employed a Design Research approach consisting of three stages: preliminary design, design experiment (including pilot and teaching experiments), and retrospective analysis. The participants were 30 fifth-semester students of the Mathematics Education Study Program at UIN Syarif Hidayatullah Jakarta. Data were collected through student worksheets, classroom observations, and interviews, and were analyzed qualitatively by comparing the Hypothetical Learning Trajectory (HLT) with the actual learning trajectory that emerged during instruction. The results indicate that the developed trajectory effectively supported students in understanding the concepts of real number sequences, convergent and divergent sequences, and limits through a gradual process from intuitive to formal understanding. Revisions to the worksheets and HLT in the second phase also improved students’ ability to generalize patterns and build mathematical connections. This study contributes to the development of a relevant Local Instruction Theory (LIT) for Real Analysis instruction in mathematics teacher education and offers an alternative instructional design that bridges the gap between school mathematics and advanced mathematics.
Discrete-Time Dynamics of Deposit-Loan Volumes Model with Repayment Rate: Standard and Non-Standard Approaches Musafir, Raqqasyi Rahmatullah; Sari, Meylita
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.35039

Abstract

In the banking system, the repayment rate of loans, which is influenced by interest rates and nonperforming loans, plays an important role in the bank’s cash flow. In this paper, we propose a discrete model of deposit–loan volumes by considering the repayment rate. The proposed model involves the standard forward Euler discretization and the non-standard finite difference (NSFD) scheme. The numerical schemes of both models are explicitly defined. Both models have three fixed points, i.e., the transaction-free point, the loan-free point, and the active-transaction point. The transaction-free fixed point is unstable, while the other two are locally asymptotically stable under certain conditions. The stability of the Euler model’s fixed point depends on the stepsize h. This indicates that the NSFD model is dynamically more consistent since it does not depend on h. Numerical simulations also confirm that the stability property of the NSFD model’s fixed points does not depend on h. Meanwhile, the stability of the fixed points of the Euler model depends on h. The simulations also show that the Euler model undergoes period-doubling and Neimark–Sacker bifurcations. This is indicated by changes in the stepsize that cause the convergence of the solution to shift into oscillations or even chaos. The chaotic condition is an undesired or even avoided situation in the banking sector. High and irregular fluctuations lead to the failure of policy control and liquidity projection. We also performed a case study using weekly loan data from September 2022 to March 2025 via parameter estimation. We use two performance metrics, i.e., the coefficient of determination (R2) and the root mean square error (RMSE). Both models produce realistic parameter values and provide a good fit to the data trend, as observed visually and from R2. Based on RMSE, the NSFD model performs better than the Euler model. Moreover, the larger the h, the better the performance. These results suggest the use of the NSFD model, which has better relevance and accuracy than the Euler model.
Validasi Estimasi Batas Atas Luas Sofa dan Perhitungan Luas Sofa Gerver serta Analisis Mekanisme Pergerakan Sofa Hammersley Akbar, Muhammad Imam; Gumilang, Aji; Hakim, Denny Ivanal
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 3 December 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i3.33457

Abstract

The Moving Sofa Problem concerns the planar shape of maximum area that can be moved around a right-angled corner in a two-dimensional hallway of unit width. The objectives of this study are (1) to validate the upper bound estimate of the sofa area obtained from the intersection of the straight corridor and the right-angled corridor models, (2) to analyze the movement mechanism of the Hammersley sofa through rotation paths and contact paths, and (3) to provide details of the Gerver sofa area calculation for numerical validation. The methods used include analysis of the function A(u, θ), which is the upper bound value function of the sofa area obtained from the area of the intersection of the straight corridor and the right-angled corridor, the application of the concepts of rotation paths, contact points, and contact paths to prove that the Hammersley sofa construction can pass through the right-angled corridor, and the calculation of the area using Green’s Theorem to validate the Gerver sofa area. The main results show that (1) the minimum upper bound of the function A(u, θ) reaches two times the square root of two under certain conditions, (2) the rotation path used proves that the Hammersley sofa satisfies the definition of a shape that can pass through a right-angled corridor, and (3) calculations using Green’s Theorem yield an area of approximately 2.2195 area units. The findings of this study clarify the geometric construction elements of the Hammersley and Gerver sofas, and provide validation details that have rarely been fully described before.

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