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INDONESIA
ARRUS Journal of Mathematics and Applied Science
Published by Yayasan Ahmar Cendekia Indonesia
ISSN : 27767922     EISSN : 28073037     DOI : https://doi.org/10.35877/mathscience.v1i1
Core Subject : Science, Education,
Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Mathematics Physics
Aim: To drive forward the fields related to Applied Sciences, Mathematics, and Its Education by providing a high-quality evidence base for academicians, researchers, scholars, scientists, managers, policymakers, and students. Scope: The focus is to publish papers that are authentic, original, and plagiarism free and should in interest of society and the world.
Arjuna Subject : Umum - Umum
Articles 75 Documents
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Comparison of R-Forecasting and V-Forecasting Singular Spectrum Analysis in Forecasting Farmers' Exchange Rates in Indonesia Fahmuddin S., Muhammad; Ruliana; Ahmad Imdad
ARRUS Journal of Mathematics and Applied Science Vol. 4 No. 2 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience3905

Abstract

Indonesia is an agricultural country where one of the main sources of income comes from the agricultural sector. One of the indicators often used to assess farmer welfare is the Farmer Exchange Rate (FER) index. Research on FER forecasting using the Singular Spectrum Analysis (SSA) method has been widely conducted, however, to date, there has been no research comparing the recurrent forecasting and vector forecasting methods in Indonesia. The purpose of this study is to obtain FER forecasting results using r-forecasting and v-forecasting, then compare the forecasting results based on MAPE values ​​to obtain the best forecasting results. The results of the study show that v-forecasting produces better forecasting results with a MAPE value of 0.57%. The forecast results for the next 12 months show an increase and decrease of FER in Indonesia. The highest FER value occurred in May 2022 at 103.79, while the lowest value was in September 2021 at 101.80.
Classification Of Hypertension Using Methods Support Vector Machine Genetic Algorithm (SVM-GA) Fahmuddin S, Muhammad; Rais, Zulkifli; Yuniar, Eka Citra
ARRUS Journal of Mathematics and Applied Science Vol. 5 No. 1 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience3976

Abstract

Support Vector Machine (SVM) is a machine learning method for classifying data that has been successfully used to solve problems in various fields. The risk minimization principle used can produce an SVM model with good generalization capabilities. The problem with the SVM method is the difficulty in determining the optimal SVM hyperparameters. This research uses Genetic Algorithm (GA) to optimize SVM hyperparameters. GA optimization on SVM is used to classify hypertension. From the result of classification analysis using GA, it shows good accuracy value performance, namely 100% compared to using only SVM.
The Analysis Of Mathematical Connection Ability In Two-Variabel Linear Equation System Based On Self Regulated Learning Of Students In VIII Grade Of Mts Negeri 1 Kota Makassar Musfira, Nur Fadillah; Arsyad, Nurdin; Rusli, Rusli; Musa, Hastuty; Rahman, Abdul
ARRUS Journal of Mathematics and Applied Science Vol. 5 No. 2 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience4088

Abstract

This study aims to analyze students' mathematical connection skills based on self-regulated learning in solving math problems in the Two-Variable Linear Equation System material. This research is qualitative research with a descriptive approach. The subjects in this study were class VIII MTs Negeri 1 Makassar City consists of two students for each level of high, medium, and low self-regulated learning. The research instrument used consisted of the main instrument, namely the researchers, and also the supporting instruments, namely a self-regulated learning questionnaire, a mathematical connection ability test, and an interview guide. The results showed that: (1) subjects who had high self-regulated learning met three indicators of mathematical connection, namely being able to recognize and use ideas in mathematics and understand the interrelationships of these ideas, and being able to recognize and apply mathematics in contexts in other fields of study. And able to relate mathematics in daily life. (2) subjects who have moderate self-regulated learning only meet two indicators of mathematical connections, namely being able to recognize and use ideas in mathematics and understand the interrelationships of these ideas, and being able to recognize and apply mathematics in the context of daily life. (3) Subjects who have low self-regulated learning, namely subjects R1 and R2 were unable to fulfill the three indicators of mathematical connection. Subject R1 was only able to fulfill one indicator of mathematical connection, while subject R2 did not fulfill any indicator of mathematical connection.
Multimedia-Based Mathematics Teaching Materials for Eighth Grade Students at SMP Negeri 1 Dua Boccoe, Bone Regency Musa, Hastuty; Maghfirah, Fatwa Ridha; Rusli, Rusli; Rahman, Abdul
ARRUS Journal of Mathematics and Applied Science Vol. 5 No. 1 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience4176

Abstract

The purpose of this study is to create multimedia-based teaching resources on quadrilaterals for eighth-grade students at SMP Negeri 1 Dua Boccoe. Research and development (R&D) is the methodology employed, and the ADDIE development model serves as the basis for the procedures. One math instructor, twenty-five eighth-grade students from SMP Negeri 1 Dua Boccoe, as well as media and content specialists, are the research subjects. In order to ascertain the practicality of the teaching materials in terms of learning quality, interest, and student independent learning, the following research instruments were used: (1) a material validation sheet by content experts, which aimed to assess the material content's suitability with the curriculum and learning objectives; (2) a material validation sheet by media experts, which aimed to assess the appearance, design, and feasibility of the multimedia used; and (3) a teacher response questionnaire. According to the study's findings, the instructional materials were deemed legitimate after being evaluated by media experts with a 95% approval rate and content experts with a 96% approval rate. Furthermore, based on the results of the teacher and student questionnaires, which covered ease, interest, and autonomous learning, the teaching materials were deemed practical with a 94% and 93% percentage, respectively. As a result, the multimedia-based teaching resources for mathematics for Class VIII pupils are deemed appropriate, fulfilling the requirements of being legitimate and useful for teaching the subject of quadrilaterals.
Implementation of Support Vector Regression (SVR) and Double Exponential Smoothing (DES) for Forecasting BRI Stock Prices Meliyana, Sitti Masyitah; Aidid, Muhammad Kasim; Rahmadhani, Amaliyah
ARRUS Journal of Mathematics and Applied Science Vol. 5 No. 2 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience4282

Abstract

This study aims to forecast the closing stock prices of BRI using Support Vector Regression (SVR) and Double Exponential Smoothing (DES) methods. The data used in this research is secondary data obtained from the Yahoo Finance website, covering the period from January 2020 to November 2023. The analytical steps using the SVR method involve selecting the optimal model by applying Grid Search Optimization to various kernels (linear, polynomial, radial, and sigmoid). The best-performing model was found to be the radial kernel with parameters ε = 0.1, C = 100, and γ = 10, yielding a Mean Absolute Percentage Error (MAPE) of 0.2431%, which was then used for forecasting. For the DES method, the steps involved parameter determination and minimizing the MAPE value, followed by smoothing calculations and forecasting. The optimal parameters obtained were α = 0.89 and β = 0.01, resulting in a MAPE value of 1.4832%. Based on the comparison of MAPE values, it can be concluded that the SVR method with a radial kernel (ε = 0.1, C = 100, γ = 10) provides the most accurate forecasts for BRI closing stock prices, with the lowest MAPE of 0.2431%.

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