Mathematical Journal of Modelling and Forecasting https://mjomaf.ppj.unp.ac.id/index.php/mjmf <table width="100%"> <tbody> <tr> <td width="25%"> <p><strong>Journal title</strong></p> </td> <td width="74%"> <p>Mathematical Journal of Modelling and Forecasting (MJMF)</p> </td> </tr> <tr> <td width="25%"> <p><strong>Country</strong></p> </td> <td width="74%"> <p>Indonesia</p> </td> </tr> <tr> <td width="25%"> <p><strong>Subject</strong></p> </td> <td width="74%"> <p>Mathematics, Statistics, Actuarial, Financial Mathematics, Computational Mathematics, and Applied Mathematics</p> </td> </tr> <tr> <td width="25%"> <p><strong>Language</strong></p> </td> <td width="74%"> <p>English</p> </td> </tr> <tr> <td width="25%"> <p><strong>ISSN</strong></p> </td> <td width="74%"> <p>2988-1013 (<a href="https://portal.issn.org/resource/ISSN/2988-1013" target="_blank" rel="noopener">online</a>)</p> </td> </tr> <tr> <td width="25%"> <p><strong>Frequency</strong></p> </td> <td width="74%"> <p>2 issues per year (June, December)</p> </td> </tr> <tr> <td width="25%"> <p><strong>Editor-in-Chief</strong></p> </td> <td width="74%"> <p>Devni Prima Sari [<a href="https://sinta.kemdikbud.go.id/authors/profile/6041224" target="_blank" rel="noopener">Sinta</a>] [<a href="https://www.scopus.com/authid/detail.uri?authorId=57192115117" target="_blank" rel="noopener">Scopus</a>] [<a href="https://scholar.google.co.id/citations?user=1tFk4wkAAAAJ&amp;hl=id" target="_blank" rel="noopener">Google Scholar</a>]</p> </td> </tr> <tr> <td width="25%"> <p><strong>Publisher</strong></p> </td> <td width="74%"> <p>LP2M Universitas Negeri Padang</p> </td> </tr> <tr> <td width="25%"> <p><strong>Citation Analysis</strong></p> </td> <td width="74%"> <p><a href="https://scholar.google.com/citations?user=4Wfv2R4AAAAJ&amp;hl=id&amp;authuser=3" target="_blank" rel="noopener">Google Scholar</a></p> </td> </tr> </tbody> </table> Universitas Negeri Padang en-US Mathematical Journal of Modelling and Forecasting 2988-1013 Analysis of Product Quality Control Using the Taguchi Method and Principal Component Analysis (PCA) at the Pabrik Tahu Alami https://mjomaf.ppj.unp.ac.id/index.php/mjmf/article/view/22 <p>Indonesia's rapid economic growth in the global business sector has intensified competition among entrepreneurs, necessitating stringent control over product quality for companies to sustain their market position. This study utilizes the Taguchi method and Principal Component Analysis (PCA) to enhance quality control processes. The Taguchi method focuses on offline quality control with a single response, while PCA is employed for multiple responses. Experiments were conducted at Pabrik Tahu Alami, examining four factors: soybean rate, soaking time, boiling time, and whey water rate, each at three levels. The optimal combination determined was 3 kg of soybeans (level 1), 4 hours of soaking time (level 1), 20 minutes of boiling time (level 2), and 5 litres of whey water (level 2). These results provide a robust framework for optimizing product quality in similar production settings.</p> Trimodesman Hardinsyah Gulo Devni Prima Sari Copyright (c) 2024 Mathematical Journal of Modelling and Forecasting https://creativecommons.org/licenses/by-nc-sa/4.0 2024-07-06 2024-07-06 2 1 1 11 10.24036/mjmf.v2i1.22 Comparison of the Fuzzy Time Series Chen Model and the Heuristic Model in Forecasting the Number of International Tourists in West Sumatra https://mjomaf.ppj.unp.ac.id/index.php/mjmf/article/view/20 <p>The Fuzzy Time Series Chen and Heuristic are two forecasting methods based on fuzzy logic used to predict values in time series. The FTS Chen and Heuristic models have almost identical forecasting processes, but the main difference lies in how they develop fuzzy logical relationships. The FTS Chen model uses Fuzzy Logical Relationship Groups obtained from the results of Fuzzy Logical Relationships for the forecasting process. On the other hand, the FTS Heuristic model uses Fuzzy Logical Relationships directly in the forecasting process. Fuzzy Logical Relationships are a collection of fuzzy logical relationships used to connect values in time series. By using Fuzzy Logical Relationships, the Heuristic model can predict values in time series more accurately and effectively. The forecasting is done to plan the development of tourism infrastructure, determine service needs, and optimize tourism promotion. The data shows that the number of foreign tourists visiting West Sumatra has continued to grow from 2006 to 2023. The comparison of the accuracy of the forecasting results of FTS Chen and Heuristic models for foreign tourists in West Sumatra yielded a MAPE of 0.241% for FTS model Chen and 0.194% for FTS model Heuristic. This indicates that the best forecasting model for foreign tourists is the Heuristic model due to its lower MAPE value.</p> Rizki Akbar Fadhilah Fitri Dodi Vionanda Tessy Octavia Mukhti Copyright (c) 2024 Mathematical Journal of Modelling and Forecasting https://creativecommons.org/licenses/by-nc-sa/4.0 2024-07-06 2024-07-06 2 1 12 19 10.24036/mjmf.v2i1.20 Modeling Network Problem using Metric Dimension: Applied Algorithm on Corona Graph https://mjomaf.ppj.unp.ac.id/index.php/mjmf/article/view/21 <p>Let <em>G</em> be a graph is a finite set of vertices and edges. A graph G can be defined as a pair of sets . The minimum cardinality of all distinguishing sets in a graph is called the metric dimension. The metric dimension was first introduced in 1966 by Harary and Melter. The method used in this research is deductive proof. The results obtained from this research are we determine the metric dimension of the graph resulting from the corona operation on and obtain the result that is 2n.</p> Deddy Rahmadi Ilma Nindita Ramadhani Clarissa Elva Dheana Miftah Aulia Mustamin Copyright (c) 2024 Mathematical Journal of Modelling and Forecasting https://creativecommons.org/licenses/by-nc-sa/4.0 2024-07-06 2024-07-06 2 1 20 26 10.24036/mjmf.v2i1.21 Application of the Inflection Point in the Evaluation of the Halley and Newton-Raphson Techniques for Finding the Root of Non-Linear Equations https://mjomaf.ppj.unp.ac.id/index.php/mjmf/article/view/23 <p>Numeric Method is one of the methods used to solve nonlinear equation roots. Many methods can be used, both open methods and closed methods. In this case, the method used is closed, namely the Newton-Raphson Method and Halley Method. The research aims to find out the comparison result between the Newton-Raphson Method and the Halley Method. The research used a literature method from a book, journal, and any other literature, where it connected with the topic. The steps used are formulation problem, finding and collecting information, describing and explaining the information, analysis, and conclusion of the result. The conclusion can be explained with a table of data and explanations Based on data analysis, it can be stated that the Halley Method is faster toward convergence compared to the Newton-Raphson Method based on the first case or second case.</p> Laode Apriano Yusmet Rizal Copyright (c) 2024 Mathematical Journal of Modelling and Forecasting https://creativecommons.org/licenses/by-nc-sa/4.0 2024-07-06 2024-07-06 2 1 27 31 10.24036/mjmf.v2i1.23 Optimal Portfolio Risk Estimation Using Expected Shortfall of Jakarta Islamic Index (JII) Shares https://mjomaf.ppj.unp.ac.id/index.php/mjmf/article/view/19 <p class="Abstract">Forming an optimal portfolio using the Mean-Variance method with Downside Deviation as a measure of risk produces a good combination of assets. Before investing, estimating risk as a worst-case scenario is very important. Expected shortfall (ES) serves as a risk measure that takes into account the possibility of losses that exceed Value at Risk (VaR). This study aims to determine the optimal portfolio and compare ES and VaR at the 90%, 95%, and 99% confidence levels. This research data involves 3 stocks namely ACES, WIFI, and TLKM. Based on the results of the analysis conducted, the optimal combination of weights is ACES (19%), WIFI (10%), and TLKM (71%). Comparison of ES and VaR shows that the higher the level of confidence, the higher the VaR and ES values generated, so the greater the risk that will be borne by investors and the capital allocation used to cover these losses.</p> Adika Risky Lestari Devni Prima Sari Copyright (c) 2024 Mathematical Journal of Modelling and Forecasting https://creativecommons.org/licenses/by-nc-sa/4.0 2024-07-06 2024-07-06 2 1 32 39 10.24036/mjmf.v2i1.19