https://ejournal.uin-malang.ac.id/index.php/Math/issue/feedCAUCHY2021-05-31T12:53:46+07:00Juhari, M.Sicauchy@uin-malang.ac.idOpen Journal Systems<h3>CAUCHY: Jurnal Matematika Murni dan Aplikasi</h3><p><span lang="id"><span class="hps"><strong>p-ISSN: <a href="http://u.lipi.go.id/1255061534" target="_blank">2086-0382</a> | e-ISSN: <a href="http://u.lipi.go.id/1447468580" target="_blank">2477-3344</a></strong></span></span><strong></strong></p><p><strong><span lang="id"><span class="hps"><br /></span></span></strong><span id="result_box" lang="en"> <strong>CAUCHY: Jurnal Matematika Murni dan Aplikasi</strong> <span>is a</span> <span>mathematical international journal</span> <span>published</span> <span>twice a year</span> <span>in May</span> <span>and</span> <span>November</span> <span>by</span> <span>the Mathematics</span> Department, F<span>aculty of</span> <span>Science</span> <span>and</span> T<span>echnology, </span><span>Universitas Islam Negeri Maulana Malik Ibrahim Malang</span></span></p><p><span id="result_box" lang="en"><strong>CAUCHY: Jurnal Matematika Murni dan Aplikasi </strong><span><strong>has been accredited Second Grade " SINTA 2" Ministry of Research and Technology/National Agency for Research and Innovation, Republic of Indonesia</strong></span><strong> (<a title="SK Akreditasi Jurnal 2020" href="https://drive.google.com/open?id=1v2Hrnf5azymhkZJRR4Jdqy_CoNTjtyjS" target="_blank">SK: 85/M/KPT/2020) since April 1, 2020</a> .</strong> </span></p><p><span lang="en">We welcome authors for original articles (research), review articles, interesting case reports, special articles illustrations that focus on the <strong>Pure and Applied <strong>Mathematics.</strong></strong></span></p><p>Subjects suitable for publication include, <strong>but are not limited</strong> <strong>to</strong>, the following fields of:</p><ul><li>Fuzzy Systems and its Applications</li><li>Geometry Theories and its Applications</li><li>Graph Theories and its Applications</li><li>Real Analysis and its Applications </li><li>Operation Research and its Applications</li><li>Statistical Theories and its Applications</li><li>Dinamical Systems and its Applications</li><li>Mathematical Modeling and its Applications</li><li>Discrete Mathematics and its Applications</li><li>Computer Mathematics and its Applications</li><li>Actuarial Mathematics and its Applications</li></ul><p><span lang="en"><span><strong>Journal History</strong><br />CAUCHY: Jurnal Matematika Murni dan Aplikasi has several changes and updates in its history as follows: 1). On 2009-2012, the cover color was changed from yellow to purple; 2). On 2013-2015, it used two-column system for the layout; 3). From 2016, it uses one-column layout and each article submitted to CAUCHY has to be written in English.</span></span></p><strong><span lang="en"><span id="result_box" lang="en"><span id="result_box" lang="en"><span> <a href="http://s1153.photobucket.com/user/joehari1/media/new1.gif.html" target="_blank"><img src="http://i1153.photobucket.com/albums/p503/joehari1/new1.gif" alt=" photo new1.gif" border="0" /></a> </span></span></span><span id="result_box" lang="en"><span id="result_box" lang="en"><span>Starting from Vol</span><span>.</span> <span>4 No.</span> <span>2</span> <span>(2016)</span> <span>CAUCHY: Jurnal Matematika Murni dan Aplikasi</span> <span>use a new layout template</span></span><br /></span></span></strong><p>Registration and article submission guidelines can be downloaded <a href="https://goo.gl/crrzlC" target="_blank">here</a>.</p><p><span lang="id"><span class="hps"><br /></span></span></p>https://ejournal.uin-malang.ac.id/index.php/Math/article/view/12311Front-Matter2021-05-31T12:52:35+07:00Front Mattercauchy@uin-malang.ac.id2021-05-30T00:00:00+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/12312Back-Matter2021-05-31T12:53:46+07:00Back Mattercauchy@uin-malang.ac.id2021-05-30T00:00:00+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/8882Selection of Specialization Class Using Support Vector Machine (SVM) Method in Sekolah Menengah Atas Negeri 1 Ambon2021-05-30T09:53:58+07:00Stevanny Tamaelaannytamaela@gmail.comYopi Andry Lesnussayopi_a_lesnussa@yahoo.comVenn Yan Ishak Ilwaruvennilwaru007@gmail.comThe curriculum is a plan to form the abilities and character of children based on a standard. One of its form is the division of specialization classes at the high school level. The 2013 curriculum emphasizes that all students in Indonesia can practice their abilities based on their interests and talents, so students no longer choose majors but choose abilities (interests) in them specialize. This research uses the Support Vector Machine (SVM) method in specialization Decision Making System (DMS) at SMA Negeri 1 Ambon. By using the motivating acceptance factors and student selection as input data, this SVM method that processed with MATLAB Software produces a Classification of Interest Class with an accuracy rate more than 95%.2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/8933Optimizing the Membership Degree of Fuzzy Inference System (FIS) and Fuzzy Clustering Means (FCM) in Weather Data Using Firefly Algorithm2021-05-30T09:53:59+07:00Dinita Rahmaliadinitarahmalia@gmail.comIn weather clustering, there are many variables which can be observed such as air temperature, humidity, sunlight intensity, and so on. In this research, Takagi-Sugeno Fuzzy Inference System (FIS) will be used for forecasting the sunlight intensity based on temperature and humidity and Fuzzy Clustering Means (FCM) will be used for clustering them based on fuzzy set. From the data consisting of temperature, humidity, and sunlight intensity, we will forecast sunlight intensity and cluster them into two clusters, three clusters, and four clusters by FCM method. In FIS method, the membership degree are often generated by trial and error. Also, the optimization of the initial of membership degree are required in FCM. Because the initial of membership degree are often generated by trial and error, in this research, we use heuristic method like Firefly Algorithm to optimize the membership degree. From the simulations, Firefly Algorithm can optimize the membership degree of FIS for forecasting the data with minimum Mean Square Error (MSE) and the initial of membership degree of FCM with two clusters, three clusters, and four clusters with minimum objective value.2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/10212Learning Interest of Poliwangi Students to Learn Mathematics Engineering Through MOOCs Using Dummy Regression2021-05-30T09:54:01+07:00Ika Yuniwatiika@poliwangi.ac.idAprilia Divi Yustitaaprilia.divi@poliwangi.ac.idSiska Aprilia Hardiyantisiska_aprilia3@poliwangi.ac.idI Wayan Suardinatawayan.suardinata@poliwangi.ac.id<p class="Abstract">MOOC is a learning system in the form of an online course that was massive and open to allow participants to enjoy unlimited and can be accessed via the web. Mathematics Techniques taught by using MOOC that will be developed are expected to be liked by students. Therefore it is necessary to do research related to student interest in studying the MOOC. This study uses a dummy regression model. Dummy regression is considered a suitable model because dummy regression can quantify qualitative data. Qualitative data here are obtained from questionnaires which distributed to 240 students. The questionnaire contains indicators of student interest in MOOC, including cognitive, affective, and psychomotor interests. The results of this study are the interest of students who do not want to study engineering mathematics through MOOC is lower than the interest of students who are interested in learning engineering mathematics through MOOC. Moreover, the interest of students who do not want to study engineering mathematics through MOOC is lower than the interest of students who do not like to study engineering mathematics through MOOC.</p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/10275Stability Analysis of HIV/AIDS Model with Educated Subpopulation2021-05-30T09:54:02+07:00Ummu Habibahummu_habibah@ub.ac.id<p class="Abstract">We had constructed mathematical model of HIV/AIDS with seven compartments. There were two different stages of infection and susceptible subpopulations. Two stages in infection subpopulation were an HIV-positive with consuming ARV such that this subpopulation can survive longer and an HIV-positive not consuming ARV. The susceptible subpopulation was divided into two, uneducated and educated susceptible subpopulations. The transmission coefficients from educated and uneducated subpopulations to infection stages were where (( and ) > ( and )) In this paper, we consider the case of and were zero. We investigated local stability of the model solutions according to the basic reproduction number as a threshold of disease transmission. The disease-free and endemic equilibrium points were locally asymptotically stable when and respectively. To support the analytical results, numerical simulation was conducted.</p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/10312Trace of Positive Integer Power of Squared Special Matrix2021-05-30T09:54:04+07:00Rahmawati Rahmawatirahmawati@uin-suska.ac.idAryati Citraaryaticitra1@gmail.comFitri Aryanikhodijah_fitri@uin-suska.ac.idCorry Corazon Marzukicorry@uin-suska.ac.idYuslenita Mudayuslenita.muda@uin-suska.ac.id<p>The rectangle matrix to be discussed in this research is a special matrix where each entry in each line has the same value which is notated by <em>An</em>. The main aim of this paper is to find the general form of the matrix trace <em>An </em>powered positive integer <em>m</em>. To prove whether the general form of the matrix trace of <em>An</em> powered positive integer can be confirmed, mathematics induction and direct proof are used. </p><p> </p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/10455Distance and Areas Weighting of GWR Kriging for Stunting Cases In East Java2021-05-30T09:54:05+07:00Deby Ardiantiard.dianti@gmail.comHenny Pramoedyohennyp@ub.ac.idNurjannah Nurjannahnj_anna@ub.ac.id<p>Spatial heterogeneity shows the characteristic location from one location to others location and it is the main assumption in Geographically Weighted Regression. The location becomes a weight on GWR model, There are two groups of location weight namely based on distance and area. The weight considers the closeness between the location. The accuracy weighted is needed because the weighting represents the data location. The aim of this research was to get a suitable weighting method for stunting data. This research used secondary data about stunting and the influence factors of stunting such as coverage visiting of pregnant women (K1), consumption of FE tablet, exclusive of breastfeeding, immunization coverage, and clean & health behaviour. Those data obtained from the Healthy Ministry of East Jawa.Based on the results of this research show that the goodness weighting for GWR modell is Adaptive Bisquare Kernel (distance weighting). The predicted mapping stunting is showed by interpolation Kriging with a range of 27% to 49,5%.</p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/10827Dynamical of Ratio-Dependent Eco-epidemical Model with Prey Refuge2021-05-30T09:54:07+07:00Adin Lazuardy Firdiansyahadin.lazuardy@gmail.com<p class="Abstract">This paper discusses the dynamic analysis of three species in the eco-epidemiology model by considering the ratio-dependent function and prey refuge. The prey refuge is applied under the fact that infected prey has protection instincts that allow it to reduce predation risk. Here, we get the boundedness and three equilibrium points where are existence under certain conditions. In the model, three equilibrium points are locally asymptotically stable and one of the equilibrium points is globally asymptotically stable. We find that the system undergoes Hopf bifurcation around the interior equilibrium point by choosing as a bifurcation parameter. We also find a condition for uniform persistence. Finally, several simulations of numerical are performed not only to illustrate the analytical results but also to illustrate the effect of the prey refuge. </p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/10871Poverty in Central Java using Multivariate Adaptive Regression Splines and Bootstrap Aggregating Multivariate Adaptive Regression Splines2021-05-30T09:54:08+07:00Ria Dhea Layla Nur Karismariadhea@uin-malang.ac.idJuhari Juharijuhari@uin-malang.ac.idRamadani A Rosaramadaniauiyanarosa@gmail.com<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>Population poverty is one of the serious problems in Indonesia. The percentage of population poverty used as a means for a statistical instrument to be guidelines to create standard policies and evaluations to reduce poverty. The aims of the research are to determine model population poverty using MARS and Bagging MARS then to understand the most influence variable population poverty of Central Java Province in 2018. The result of this research is the Bagging MARS model showed better accuracy than the MARS model. Since, GCV value in the Bagging MARS model is 0,009798721 and GCV value in the MARS model is 6,985571. The most influential variable poverty population of Central Java Province in 2018 in the MARS model is the percentage of the old school expectation rate (X9). Then, the most influential variable in the Bagging MARS model is the number of diarrhea (X1).</span></p></div></div></div>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/11254Invertibility of Generalized Space-Time Autoregressive Model with Random Weight2021-05-30T09:54:09+07:00Yundari Yundariyundari@math.untan.ac.idSetyo Wira Rizkisetyo.wirarizki@math.untan.ac.id<p>The generalized linear process accomplishes stationarity and invertibility properties. The invertibility property must be having a series of convergence conditions of the process parameter. The generalized Space-Time Autoregressive (GSTAR) model is one of the stationary linear models therefore it is necessary to reveal the invertibility through the convergence of the parameter series. This article studies the invertibility of model GSTAR(1;1) with kernel random weight. The result shows that the model GSTAR(1;1) under kernel random weight fulfills the invertibility property and obtains a finite order of Generalized Space-Time Moving Average (GSTMA) process. The other result obtained is the time order of the finite orde . On the Triangular kernel resulted in the relatively great value <em>n</em>, so that it does not apply to the kernel with a finite value <em>n</em>.</p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/11472Analysis of The Rosenzweig-MacArthur Predator-Prey Model with Anti-Predator Behavior2021-05-30T14:52:49+07:00Ismail Djakariaiskar@ung.ac.idMuhammad Bachtiar Gaibm.tiargaib@gmail.comResmawan Resmawanresmawan@ung.ac.idThis paper discusses the analysis of the Rosenzweig-MacArthur <em>predator-prey</em> model with <em>anti-predator</em> behavior. The analysis is started by determining the equilibrium points, existence, and conditions of the stability. Identifying the type of Hopf bifurcation by using the divergence criterion. It has shown that the model has three equilibrium points, i.e., the extinction of population equilibrium point (E0), the non-<em>predator</em><em>y</em> equilibrium point (E1), and the co-existence equilibrium point (E2). The existence and stability of each equilibrium point can be shown by satisfying several conditions of parameters. The divergence criterion indicates the existence of the supercritical Hopf-bifurcation around the equilibrium point E2. Finally, our model's dynamics population is confirmed by our numerical simulations by using the 4th-order Runge-Kutta methods.2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/11482Bayesian Generalized Self Method to Estimate Scale Parameter of Invers Rayleigh Distribution2021-05-30T09:54:11+07:00Ferra Yanuarferrayanuar@yahoo.co.idRahmi Febriyuniraahmifebriyuni@gmail.comIzzati Rahmi HGizzatirahmihg@gmail.com<p>The purposes of this study are to estimate the scale parameter of Invers Rayleigh distribution under MLE and Bayesian Generalized square error loss function (SELF). The posterior distribution is considered to use two types of prior, namely Jeffrey’s prior and exponential distribution. The proposed methods are then employed in the real data. Several criteria for the selection model are considered in order to identify the method which results in a suitable value of parameter estimated. This study found that Bayesian Generalized SELF under Jeffrey’s prior yielded better estimation values that MLE and Bayesian Generalized SELF under exponential distribution.</p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/11484Strongly Summable Vector-Valued Sequence Spaces Defined by 2-modular2021-05-30T14:54:58+07:00Burhanudin Arif Nurnugrohoburhanudin@pmat.uad.ac.idPuguh Wahyu Prasetyopuguh.prasetyo@pmat.uad.ac.id<p class="Abstract">Summability is an important concept in sequence spaces. One summability concept is strongly Cesaro summable. In this paper, we study a subset of the set of all vector-valued sequence in 2-modular space. Some facts that we investigated in this paper include linearity, the existence of modular and completeness with respect to these modular.</p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/11591Modeling Plant Stems Using the Deterministic Lindenmayer System2021-05-30T09:54:13+07:00Juhari Juharimuhammadroziqinlina@gmail.comMuhammad Zia Algharmuhammadzia1904@gmail.com<p class="Abstract">Plant morphology modeling can be done mathematically which includes roots, stems, leaves, to flower. Modeling of plant stems using the Lindenmayer System (L-system) method is a writing returns that are repeated to form a visualization of an object. Deterministic L-system method is carried out by predicting the possible shape of a plant stem using its iterative writing rules based on the original object photo. The purpose of this study is to find a model of the plant stem with Deterministic Lindenmayer System method which will later be divided into two dimensional space three. The research was conducted by identifying objects in the form of pine tree trunks measured by the angle, thickness, and length of the stem. Then a deterministic and parametric model is built with L-system components . The stage is continued by visualizing the model in two dimensions and three dimensions. The result of this research is a visualization of a plant stem model that is close to the original. Addition color, thickness of the stem, as well as the parametric writing is done to get the results resembles the original. The iteration is limited to less than 20 iterations so that the simulation runs optimal.</p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/11758Regularized Ordinal Regression with Elastic Net Approach (Case Study: Poverty Modeling in Yogyakarta Province 2018)2021-05-30T09:54:14+07:00Pardomuan Robinson Sihombingrobin_sihombing@yahoo.comYudhie Andriyanarobin_sihombing@yahoo.comBertho Tantularrobin_sihombing@yahoo.comGenerally, modeling poverty aims to obtain the best criteria for assessing poverty status. There are two approaches to model the factors that affect poverty, namely consumption approach and discrete choice model. The advantage of the discrete choice model compared to the consumption approach is that the discrete choice model provides a probabilistic estimate for classifying samples into different poverty categories. This study aims to examined how the factors that affect poverty in Yogyakarta through Regularized Ordinal Regression with elastic net approach both for parallel, non-parallel, and semi-parallel models. The data used in this study is Susenas March 2018 for Yogyakarta provinces. The result of this study shows that the best discrete choice model for Yogyakarta’s modelling is the parallel model. Households that live in villages, have a large number of household members, are headed by women, have elderly household heads, have low education, and work in the primary sector tend to be more vulnerable to poverty. Therefore, a simultaneous policy with inclusive economic development is needed to reduce cross-border, cross-gender, and cross-sector inequality2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHYhttps://ejournal.uin-malang.ac.id/index.php/Math/article/view/10639Spatio Temporal Modelling for Government Policy the COVID-19 Pandemic in East Java2021-05-30T09:54:06+07:00Atiek IrianyAtiekiriany@ub.ac.idNovi Nur Aininovinuraini613@gmail.comAgus Dwi Sulistyonoagusdwisulistyono@gmail.com<p>COVID-19 has cursorily spread globally. Just in four months, its status altered into a pandemic. In Indonesia, the virus epicenter is identified in Java. The first positive case was identified in West Java and later spread in all Java. The Large-scale Social Restrictions are seemingly inefficient as the SARS-CoV-2 transmission remains. As such, the government is struggling to find anticipatory policies and steps best to mitigate the transmission. In this particular article, we used a Spatio-temporal model method for the total COVID-19 cases in Java and forecasted the total cases for the next 14 days, allowing the stakeholders to make more effective policies. The data we were using were the daily data of the cumulative number of COVID-19 cases taken from <a href="http://www.covid19.go.id/">www.covid19.go.id</a>. Data modelling was conducted using a generalized spatio-temporal autoregressive model. The model acquired to model the COVID-19 cases in Java was the GSTAR(1)(1,0,0) model.</p>2021-05-30T14:35:53+07:00Copyright (c) 2021 CAUCHY