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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 11 Documents
 1   2 
Search results for , issue "Volume 12 Issue 2 December 2024" : 11 Documents clear
Penerapan Hybrid Metode ARFIMA-ANN Menggunakan Algoritma Backpropagation pada Peramalan Indeks Harga Saham Gabungan Buhungo, Rayhanul Jannah; Hasan, Isran K; Nurwan, Nurwan
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.28474

Abstract

The Composite Stock Price Index (IHSG) is a of the key indicator a country uses to assess its economic condition. The fluctuating movements of stock prices create uncertainly in the stock market, complicating decision-making for investors and government entities. Therefore, there is a need for a method that can forecast the Composite Stock Price Index to monitor such fluctuations. The objective of this study is to model the Composite Stock Price Index Utilizing a hybrid method and to assess the accuracy of this hybrid approach. The hybrid method employed is the Autoregressive Fractionally Integrated Moving Average (ARFIMA)-Artificial Neural Network (ANN). The results of this study show that the best ARFIMA model is ARFIMA (1,d,1) with a differencing parameter of dR/S = 0,362. The ANN model’s optimal architecture obtained through the backpropagation algorithm is ANN (3,2,1). The accuracy of the hybrid ARFIMA-ANN model, measured by the Mean Absolute Percentange Error (MAPE), yielded of 1,0164%, lower than the MAPE value of 1,7326% for the standalone ARFIMA model. This suggests that the hybrid model improves forecasting accuracy and is the most efferctive model for predicting the IHSG. 
Analisis Kestabilan Lokal pada Model SEIR Patogenesis Frambusia dengan Infeksi Primer-Sekunder dan Tersier Lasongke, Fahri Alam; Puspita, Juni Wijayanti; Ratianingsih, Rina; Utami, Vicya; Salman, Salman
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.27847

Abstract

Yaws is a skin disease characterized by red spots that can worsen if not treated promptly. This disease is caused by the bacteria Treponema Pallidum Pertenue. The symptoms of yaws have five stages, namely the primary stage, primary to secondary latent stage, secondary stage, secondary to tertiary latent stage, and tertiary stage. A mathematical model is one solution to describe the prognosis of yaws disease. Here, the population was divided into 5 sub-populations, namely susceptible sub-population, exposed sub-population, infected sub-population in the primary and secondary stages, infected sub-population in the tertiary stage, and recovered sub-population. The mathematical model of the spread of yaws disease is written as a system of nonlinear differential equations whose stability is analyzed around the critical point. From the system of differential equations, two critical points are obtained which describe the disease-free condition and the endemic condition. In this study, the existence and stability of both critical points can be guaranteed. Furthermore, numerical simulations were conducted using yaws disease data in Indonesia. Simulation results show that the transmission of yaws disease in Indonesia can be controlled by reducing contact between the primary-secondary infected population and the susceptible population.
Sistem Pendukung Keputusan Dengan Menggunakan Metode ELECTRE II Dalam Menentukan Faktor Yang Mempengaruhi Pemilihan Sabun Mandi Fazariani, Nabila; Sari, Rina Filia; Aprilia, Rima
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.25851

Abstract

Reviewed and with the increasing public awareness of skin health, soap manufacturers are competing to offer their products with various fragrances, forms, and benefits to the public. Each individual certainly has different criteria in choosing bath soap products, such as packaging, product price, product fragrance, type and form, and so on. The purpose of this research is to determine the factors that serve as the basis for each individual in choosing bath soap products by implementing the Elimination et Choix Traduisant la Réalité II (ELECTRE II) method. The ELECTRE II method uses simple criteria, namely setting the same threshold value for all criteria. In contrast, other methods use pseudo criteria where the threshold value is not the same for all criteria. The ELECTRE II method is one of the Multi-Attribute Decision Making (MADM) methods that is effective in determining ranking, as it involves both qualitative and quantitative criteria. Based on the research results, product quality becomes the priority factor in choosing bath soap products, with a Concordance value of 1.375 and a Discordance value of -1.80063, as well as the highest average rank, which is 1. The product price factor ranks second, followed by the skin condition factor in third place, and the product fragrance factor, which ranks last with an average rank of 4.
Shear Wave Travel Time Prediction using Well Log Filtering and Machine Learning Siregar, Indra Rivaldi; Nugraha, Adhiyatma; Fitrianto, Anwar; Erfiani, Erfiani; Jumansyah, L.M. Risman Dwi
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.29021

Abstract

Shear wave travel time (also known as Delta-T Shear and commonly abbreviated as DTS) is an important parameter in petroleum for exploration, production, and characterization of borehole stability. Direct measurement of DTS is often limited by high costs and a constraint of geography, making machine learning (ML) predictive approaches necessary. This study aims to explore the effectiveness of ML models in predicting DTS, emphasizing the importance of data preprocessing techniques to improve prediction accuracy. Preprocessing techniques include Yeo-Johnson transformation to handle non-normality, outlier elimination using z-score, and data smoothing using the Savitzky-Golay filter and median filter. Incorporating smoothing techniques can fill important gaps in some existing studies and may improve the performance of machine learning models in predicting DTS, particularly in situations with limited or noisy data. Four ML models were tested in this study, namely Linear Regression (LR), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), and Random Forest (RF), with performance evaluation based on metrics RMSE (Root Mean Squared Error), MAE (Mean Absolute Error), and R2 (coefficient of determination). The results showed that the RF model produced the best performance with RMSE of 9.41, MAE of 6.35, and R2 of 0.90 in scenarios with Yeo-Johnson transformation, outlier elimination, and smoothing techniques using a median filter with a window size of 5.
Perbandingan Fuzzy Time Series Chen dan Cheng untuk Peramalan Harga Beras di Kabupaten Banyumas Sari, Dian Kartika; Sa'adah, Aminatus
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.28012

Abstract

Indonesia is mostly an agricultural country. Most people here make a living from farming. Rice is a major crop in Indonesia. The price of rice is very important to the economy, especially in farming areas like Banyumas. Fluctuating rice prices can affect the economic lives of both farmers and consumers in the region. The rapid fluctuation in rice prices and the uncertainty of future prices demand the need for rice price forecasting. This study uses fuzzy time series to forecast rice prices. The prediction models used are the Chen model and the Cheng model. To calculate the accuracy of the models, MAPE calculations are employed. Based on the results, the MAPE value for the Chen model is 0.957539%, and for the Cheng model, it is 0.477921%. The results indicate that the accuracy of the Cheng model is higher than that of the Chen model, meaning that the Cheng model is better suited for forecasting rice prices in Banyumas Regency.
Dimensi Partisi Graf Hasil Amalgamasi Sisi Graf Roda dengan Graf Bintang Daming, Ahmad Syukur; Yuliani, Yuliani
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.27683

Abstract

This study discusses the analysis of the partition dimension of the graph resulting from the edge amalgamation between the wheel graph ( Wn) and the star graph ( Sm), where the partition dimension is an important parameter in graph theory that serves to measure the minimum number of partitions required to distinguish every pair of vertices through a set of supporting vertices. The amalgamation process is carried out by merging one edge of the wheel graph with one edge of the star graph, thus forming a new graph. This research employs theoretical and algorithmic approaches to calculate the partition dimension of the resulting amalgamated graph, focusing on the influence of the number of vertices in both constituent graphs on the changes in the partition dimension. The results show that pd(amal_s(Wn,Sm;v1v2,u1u2))=3 when 4n7 and m=3, and 4 when n=3 and 3≤m≤4, whereas if n≥8 and 3≤m≤⌊n/2⌋, then ⌊n/2⌋ is obtained.
Penerapan Collective Risk Model dalam Penentuan Premi Asuransi Bencana Alam Yusuf, Feby Indriana; Adi, Puti Zakiyah Raisa; Saragih, Trecy Elisabet Tioralina
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.28632

Abstract

Indonesia is prone to natural disasters such as volcanic eruptions, earthquakes, and tsunamis due to tectonic activity involving the Indo-Australian and Eurasian plates. Therefore, the government introduced natural disaster insurance in 2018 to mitigate financial losses caused by such events. This study employs the Collective Risk Model (CRM) to determine premium rates. The Poisson process and Gamma distribution are utilized to estimate the frequency and severity of natural disasters. Estimation is performed using Maximum Likelihood Estimation (MLE), while premiums are calculated based on the expected value and variance of aggregate risk using the Expected Value Principle and the Standard Deviation Principle. The results show that the expected value and variance of claim frequency are both . Furthermore, claims for losses follow the Gamma distribution, with an expected value and variance of  and . The mean and variance of aggregate claims are Rp  and Rp . The Standard Deviation Principle produces lower premiums than the Expected Value Principle under the same loading factor.
Modeling of Gross Domestic Product Growth in Indonesia by Using Multi-Input Intervention Model Chandrawati, Chandrawati; Kertanah, Kertanah; Ramli, Tri Juliantin; Chintyana, Alissa; Hirzi, Ristu Haiban
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.27949

Abstract

The Gross Domestic Product (GDP) Growth of Indonesia has fluctuated over time due to established policies, economic crises, changes in political direction, and natural disasters. In 1998, due to the fall of the New Order regime, the Indonesian economy contracted by -13.13 percent, leading to hyperinflation. In 2020 the COVID-19 pandemic occurred which caused Indonesia's GDP Growth to contract again. Accurate forecasting of GDP Growth is crucial for government to formulate effective future policy strategies to maintain the stability of Indonesia's economy. There are several outliers in Indonesia's GDP Growth data, so the proper analysis is a multi-input intervention. The best model analysis is ARIMA (1,0,0) with non-zero mean using the first order intervention b=0, r=0, s=0 and the second order intervention b=0, r=0, and s=0 which resulted in a Mean Absolute Percentage Error (MAPE) of 23.47 percent. The outlier effect on Indonesia's GDP Growth data is both direct and temporary.
The Orthogonal Matrices of O(2) under A Transitive Standard Action of S^1 Kurniadi, Edi; Pratiwi, Putri Nisa; Queency, Aurillya; Parmikanti, Kankan
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.27752

Abstract

In this paper, we study a Lie group action of the matrix Lie group O(2) on S1 the unit sphere  . The research aims to establish the explicit formulas for all entries of  whose action on S1  is transitive. All possibilities matrices of  are given in which the space  is homogeneous. We prove that there are exactly two matrices in  such that  is the homogeneous space. Moreover, the homogeneous spaces  S(n-1) of O(n)   for n=3  are also discussed.
Analisis Kemampuan Berpikir Aljabar Ditinjau Dari Kepercayaan Diri Siswa Adawiyah, Anisah Luthpi; Nur Atiqoh, Khamida Siti; Satriawati, Gusni
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.28094

Abstract

Student confidence is one of the factors that affect students' algebraic thinking skills. Algebraic thinking ability is the ability to present information mathematically through diagrams, tables, graphs, equations, and understanding of patterns, functions, structures, and uncertain objects. This study aims to describe and analyze quantitatively the algebraic thinking ability of high school students, high school students' self-confidence and know the influence between algebraic thinking ability and students' self-confidence. This research was conducted in three public high schools in South Tangerang City in the 2023/2024 school year. This research is a survey research with a correlational approach. The test instrument given was a description of algebraic thinking ability and a non-test instrument of self-confidence to 111 students. The results showed that students' algebraic thinking ability and self-confidence were in the moderate category. The results also showed that the effect between students' self-confidence on algebraic thinking ability was 33.60%. It can be concluded that if students' self-confidence is good then the ability to think algebra will also be good. The results of this study can be a consideration for teachers to develop mathematics learning activities that can increase student confidence.

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