BAREKENG: Jurnal Ilmu Matematika dan Terapan
BAREKENG: Jurnal ilmu Matematika dan Terapan is one of the scientific publication media, which publish the article related to the result of research or study in the field of Pure Mathematics and Applied Mathematics. Focus and scope of BAREKENG: Jurnal ilmu Matematika dan Terapan, as follows: - Pure Mathematics (analysis, algebra & number theory), - Applied Mathematics (Fuzzy, Artificial Neural Network, Mathematics Modeling & Simulation, Control & Optimization, Ethno-mathematics, etc.), - Statistics, - Actuarial Science, - Logic, - Geometry & Topology, - Numerical Analysis, - Mathematic Computation and - Mathematics Education. The meaning word of "BAREKENG" is one of the words from Moluccas language which means "Counting" or "Calculating". Counting is one of the main and fundamental activities in the field of Mathematics. Therefore we tried to promote the word "Barekeng" as the name of our scientific journal also to promote the culture of the Maluku Area. BAREKENG: Jurnal ilmu Matematika dan Terapan is published four (4) times a year in March, June, September and December, since 2020 and each issue consists of 15 articles. The first published since 2007 in printed version (p-ISSN: 1978-7227) and then in 2018 BAREKENG journal has published in online version (e-ISSN: 2615-3017) on website: (https://ojs3.unpatti.ac.id/index.php/barekeng/). This journal system is currently using OJS3.1.1.4 from PKP. BAREKENG: Jurnal ilmu Matematika dan Terapan has been nationally accredited at Level 3 (SINTA 3) since December 2018, based on the Direktur Jenderal Penguatan Riset dan Pengembangan, Kementerian Riset, Teknologi, dan Pendidikan Tinggi, Republik Indonesia, with Decree No. : 34 / E / KPT / 2018. In 2019, BAREKENG: Jurnal ilmu Matematika dan Terapan has been re-accredited by Direktur Jenderal Penguatan Riset dan Pengembangan, Kementerian Riset, Teknologi, dan Pendidikan Tinggi, Republik Indonesia and accredited in level 3 (SINTA 3), with Decree No.: 29 / E / KPT / 2019. BAREKENG: Jurnal ilmu Matematika dan Terapan was published by: Mathematics Department Faculty of Mathematics and Natural Sciences University of Pattimura Website: http://matematika.fmipa.unpatti.ac.id
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<![CDATA[EVALUATION AND USER INTERFACE DESIGN IMPROVEMENT RECOMMENDATIONS OF THE IMMIGRATION SERVICE APPLICATION USING DESIGN THINKING ]]>
<![CDATA[Alexander Ryan Hendarto]]>;
<![CDATA[Indah Werdiningsih]]>;
<![CDATA[Kartono Kartono]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0001-0018
<![CDATA[The M-Paspor application is an immigration service application. It is an application that is officially managed by the Directorate General of the Ministry of Law and Human Rights of the Republic of Indonesia. With this online service system, people who wish to apply for passports do not need to come to the office and stand in line to make passports, now they only need to access the Directorate General of Immigration's website or this mobile-based application to submit an application. This study aims to evaluate and provide recommendations for user interface improvements that can be proposed to improve the user experience of the M-Paspor application. This research used the design thinking method. Design thinking itself consists of five stages, namely empathy, define, idea, prototype, and test. Some of the problems in the user experience of the M-Paspor application are the confusing flow and interface, the loading process takes too long, the information guide is not informative, the display is boring and inconsistent. The user experience of the M-Paspor application has been tested with 15 respondents through five usability test task scenarios. The test results shown that the average aspect of effectiveness is 100%, the average aspect of efficiency is 0.133 goals/second with a range of 0.197 goals/second, and the average aspect of user satisfaction is 5.1 with a range of 2.4 (from a scale of 1 to 7).]]>
<![CDATA[A COMPARISON OF FUZZY TIME SERIES CHENG AND CHEN-HSU IN FORECASTING TOTAL AIRPLANE PASSENGERS OF SOEKARNO-HATTA AIRPORT ]]>
<![CDATA[Latifah Zahra]]>;
<![CDATA[Maiyastri Maiyastri]]>;
<![CDATA[Izzati Rahmi]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0019-0028
<![CDATA[In some cases, the demand for flights has increased or decreased unexpectedly. Based on this airport as a service provider balance the availability of the service and the needs in the field. To balance all the provided services, the airport needs to predict the total passenger that would visit the airport on consecutive days. Thus, a form of time-series forecast is used in this research. We applied fuzzy time series (FTS) to forecasting total airplane passengers, where there are several logics in FTS including FTS Cheng’s Logic and FTS Chen-Hsu’s Logic. To determine the accuracy of the forecast, use three criteria, namely Root Mean Squared Error (RMSE), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE). In terms of modelling and forecasting data, FTS Chen-Hsu’s Logic is better than FTS Cheng’s Logic. This is shown in the value of three accuracy criteria of FTS Chen-Hsu’s Logic are smaller than FTS Cheng’s Logic. Conclusion, FTS Chen-Hsu method can be used as a forecasting model for the total passenger airplane in Soekarno-Hatta International Airport]]>
<![CDATA[WEIBULL-POISSON DISTRIBUTION AND THEIR APPLICATION TO SYSTEMATIC PARALLEL RISK ]]>
<![CDATA[Yekti Widyaningsih]]>;
<![CDATA[Rugun Ivana]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0053-0064
<![CDATA[The Weibull-Poisson distribution represents a continuous distribution type applicable to various forms of hazard, including monotone up, monotone down, and upside-down bathtub shapes that ascend. The distribution characterizes lifetimes and can effectively model failures within a series of systems, which evolves from the Exponential-Poisson distribution. This distribution emerges through the compounding of the Weibull Distribution and Zero Truncated Poisson Distribution. The compounding itself integrates several mathematical properties, such as statistical order and Taylor’s number expansion, to reach its final form. Alongside the formulation of the Weibull-Poisson distribution, this paper includes the probability density function, distribution function, rth moment, rth central moment, mean, and variance. For illustration, the Weibull-Poisson distribution is applied to guinea pig survival data after being infected with Turblece virus Bacilli.]]>
<![CDATA[DYNAMIC SYSTEM OF TUBERCULOSIS MODEL USING OPTIMAL CONTROL IN SEMARANG CITY INDONESIA ]]>
<![CDATA[Dhimas Mahardika]]>;
<![CDATA[Sopia Kartika]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0029-0042
<![CDATA[Tuberculosis is a disease which is very contagious among human. To prevent this from happening, Semarang city government has enacted vaccination for exposed individuals and treatment for the infected individuals. Vaccination and treatment are forms of control that will be applied to dynamic model systems of Tuberculosis. The present paper will describe epidemic model of Tuberculosis with control using Pontryagin Minimum Principle to find optimal solution of the control with fixed time and free end point. The optimal control will aim to reduce or minimize the number of infected populations. Numerical calculation is carried out with MATLAB software programming to illustrate and compare the graph of the dynamic model with and without optimal control. The results of dynamic modeling of Tuberculosis with control state that vaccination and treatment have succeeded in reducing the population of infected individuals.]]>
<![CDATA[COMPARISON OF LOCAL POLYNOMIAL REGRESSION AND ARIMA IN PREDICTING THE NUMBER OF FOREIGN TOURIST VISITS TO INDONESIA ]]>
<![CDATA[Bagas Shata Pratama]]>;
<![CDATA[Alda Fuadiyah Suryono]]>;
<![CDATA[Nina Auliyah]]>;
<![CDATA[Nur Chamidah]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0043-0052
<![CDATA[Indonesia is a country that has a variety of exotic tourist destinations and can attract tourists to visit. Currently, tourism is one of the sectors that plays a major role in driving the Indonesian economy. Various tourists, both domestic and foreign, are expected to continue to increase in number every year. Therefore, appropriate policies are needed from the government to develop the tourism sector so that it can be even better over time. This research aims to predict the number of foreign tourist visits to Indonesia using the Autoregressive Integrated Moving Average (ARIMA) model and local polynomial regression. The data used in this research is the number of foreign tourist visits per month from January 2017 to December 2022 obtained from the the Kemenparekraf website. This data is fluctuating so that the method a local polynomial approach is appropriate for this study. The data analysis method used are local polynomial regression and ARIMA model. In the ARIMA model there are assumptions that must be met. In this study, the ARIMA model obtained has met the assumption of residual normality but does not meet the assumption of homoscedasticity so that ARIMA modeling cannot be continued and analysis is only carried out with local polynomial regression. The result of this study is a prediction of future tourist visits. The MAPE value of the local polynomial regression approach is 1.43% which is categorized as a prediction with high accuracy because the value is less than 10%. Thus, the local polynomial regression approach is very well used to predict the number of foreign tourist visits to Indonesia.]]>
<![CDATA[ALGEBRAIC STRUCTURES ON A SET OF DISCRETE DYNAMICAL SYSTEM AND A SET OF PROFILE ]]>
<![CDATA[Ananda Ayu Permatasari]]>;
<![CDATA[Ema Carnia]]>;
<![CDATA[Asep Kuswandi Supriatna]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0065-0074
<![CDATA[A discrete dynamical system is represented as a directed graph with graph nodes called states that can be seen on the dynamical map. This discrete dynamical system is symbolized by , where is a finite set of states and the function g is a function from to . In the dynamical map, the discrete dynamical system has a height where the number of states in each height is called a profile. The set of discrete dynamical systems has an addition operation defined as a disjoint union on the graph and a multiplication operation defined as a tensor product on the graph. The set of discrete dynamical systems and the set of profiles are very interesting to observe from the algebraic point of view. Considering operation on the set of discrete dynamical systems and the set of profiles, we can see their algebraic structure. By recognizing the algebraic structure, it will be easy to solve the polynomial equation in the discrete dynamical system and in the profile. In this research, we will investigate the algebraic structure of discrete dynamical systems and the set of profiles. This research shows that the set of discrete dynamical system has an algebraic structure, which is a commutative semiring and the set of profiles has an algebraic structure, which is a commutative semiring and -semimodule. Moreover, both sets have the same property, which is isomorphic to the set of non-negative integers.]]>
<![CDATA[SIGNIFICANT FACTORS INFLUENCING HYPERBILIRUBINEMIA AT SANTO YUSUF MOTHER AND CHILD HOSPITAL, NORTH JAKARTA USING BINARY LOGISTIC REGRESSION ]]>
<![CDATA[Elsa Anna Pratiwi]]>;
<![CDATA[Nunung Nurhayati]]>;
<![CDATA[Idha Sihwaningrum]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0075-0084
<![CDATA[Hyperbilirubinemia is a problem that often occurs in newborns. The cause of hyperbilirubinemia is multifactorial including maternal, perinatal or environmental factors that can be risk factors in newborns. Hyperbilirubinemia that occurs in infants is usually due to high bilirubin levels. High bilirubin can be a poison that causes brain damage so hyperbilirubinemia must be treated appropriately so as not to cause chronic complications. This study aims to identify significant factors affecting hyperbilirubinemia in infants at Santo Joseph Mother and Child Hospital, North Jakarta using binary logistic regression. This research was conducted at Santo Joseph Mother and Child Hospital for the first time. Factors that are thought to influence are gestational age, birth weight, childbirth, breastfeeding, and infection status. The results showed that the significant factors affecting hyperbilirubinemia in infants were the process of childbirth, milk feeding and infection status. Based on the odds ratio value for each variable, it can be concluded that babies with abnormal birth processes have a risk of hyperbilirubinemia of 2.9628 times greater than babies with normal births. Meanwhile, formula-fed infants have a risk of hyperbilirubinemia of 4.2854 times less than breastfed babies. Furthermore, infants affected by infection have a risk of developing hyperbilirubinemia of 5.5752 times greater than infants who do not get infection.]]>
<![CDATA[COMPARISON OF APARCH-TYPE MODELS: DOES THE CONTINUOUS AND JUMP COMPONENTS OF REALIZED VOLATILITY IMPROVE THE FITTING? ]]>
<![CDATA[Didit B. Nugroho]]>;
<![CDATA[Nur I. M. Urosidin]]>;
<![CDATA[Hanna A. Parhusip]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0085-0094
<![CDATA[This study aims to extend an APARCH-X(1,1) model to the APARCH-CJ(1,1) by separating the exogenous variable X into two components: continuous and discontinuous (jump). The study was based on the application of models to 1-min intraday high-frequency data from the Tokyo Stock Price Index from 2004 to 2011, where its dependent variable is daily return and its exogenous variability is Realized Volatility. As a basic framework, the return errors follow a Normal distribution. An Adaptive Random Walk Metropolis (ARWM) method was constructed in the Markov Chain Monte Carlo algorithm to estimate model parameters so that the model fits the observed return time series. By visual inspection, the parameter trace plots showed good convergence of the Markov chains, indicating that the ARWM method is efficient in estimating the studied models. Based on the results of the Akaike Information Criterion for model fitting to data, this study found that APARCH-CJ(1,1) is inferior to APARCH(1,1).]]>
<![CDATA[IMPLEMENTATION OF THE BIDIRECTIONAL GATED RECURRENT UNIT ALGORITHM ON CONSUMER PRICE INDEX DATA IN INDONESIA ]]>
<![CDATA[Andjani Ayu Cahaya Tanjung]]>;
<![CDATA[Dewi Retno Sari Saputro]]>;
<![CDATA[Nughthoh Arfawi Kurdhi]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0095-0104
<![CDATA[The Consumer Price Index (CPI) is the main index in measuring the inflation rate. Changes in the CPI from time to time reflect inflation and deflation, namely the higher the CPI value, the higher the inflation rate. This study aims to apply Birectional Gated Recurrent Unit (BiGRU) model to the CPI data in Indonesia. BiGRU comprises two GRU layers so it captures sequences that are ignored by the GRU. The research data is in the form of CPI data in Indonesia from January 2006 to December 2022 sourced from the website of the Central Bureau of Statistics totaling 204 data. The data is divided into training data and testing data. Training data was taken from January 2006 to July 2019 as many as 163 data. Data testing was taken from August 2019 to December 2022 as many as 41 data. Before the data is processed, a sliding window process is carried out by dividing the data into segments to reduce the error value. The window size value used is 10. In the sliding window process, the number of segments is 194 data segments. Based on the experiment results, it was concluded that the application of BiGRU to the CPI data was carried out in an experiment with 20 BiGRU architectures. BiGRU architecture was obtained which produced the lowest MAPE value, namely an architecture with two BiGRU layers having 256 neurons and 400 units, and one dense layer. In addition, the epochs used are 200 epochs, the ReLU activation function, and Adam optimization. The experimental results of the BiGRU architecture obtained a MAPE value of 0.24% which indicates that the architectural performance is very good.]]>
<![CDATA[SCHEDULING ANALYSIS BEDUGUL VILLA CONSTRUCTION PROJECT USING PERT AND CPM METHODS ]]>
<![CDATA[Kiswara Agung Santoso]]>;
<![CDATA[Ade Ratna Yusnita]]>;
<![CDATA[Agustina Pradjaningsih]]>
<![CDATA[ BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application ]]>
Publisher : <![CDATA[PATTIMURA UNIVERSITY ]]>
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DOI: 10.30598/barekengvol18iss1pp0105-0116
<![CDATA[Scheduling in construction projects is necessary so that the planned time to complete the project can be achieved on time. the methods used in optimizing project scheduling are the Project Evaluation Review Technique (PERT) method and the Critical Path Method (CPM) method. Bedugul Villa is one of the projects that has been carried out with a work contract for 175 calendar days and the scheduling of which will be optimized in this study. The optimal duration for scheduling with the PERT method is to produce an optimal duration of 170 calendar days. The duration is 5 days faster than the existing schedule prepared by the project construction contractor, which is 175 calendar days. The probability of completion of the project is 87.7%. Calculations using the CPM method are 168 calendar days or 7 days earlier than the existing schedule made by the contractor.]]>
