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Redaksi BAREKENG: Jurnal ilmu matematika dan terapan, Ex. UT Building, 2nd Floor, Mathematic Department, Faculty of Mathematics and Natural Sciences, University of Pattimura Jln. Ir. M. Putuhena, Kampus Unpatti, Poka - Ambon 97233, Provinsi Maluku, Indonesia Website: https://ojs3.unpatti.ac.id/index.php/barekeng/ Contact us : +62 85243358669 (Yopi) e-mail: barekeng.math@yahoo.com

BAREKENG: Jurnal Ilmu Matematika dan Terapan

barekeng
Website

Published by Universitas Pattimura

ISSN : 19787227 EISSN : 26153017 DOI : https://search.crossref.org/?q=barekeng

Core Subject : Economy, Science, Education, Engineering,

Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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

Arjuna Subject : Matematika - Matematika Terapan

Articles 40 Documents

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Search results for , issue "Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan" : 40 Documents clear

COMPARISON OF AUTOREGRESSIVE MODEL WITH MISSING DATA TREATED USING ORDINARY LEAST SQUARES AND INTERPOLATION WITH WEIGHTING METHOD Syifani Akmaliah; Dianne Amor Kusuma; Budi Nurani Ruchjana
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Bandung is committed to contributing to the achievement of the Sustainable Development Goals (SDGs) in Indonesia. One of the efforts that can be made to support the 13th pillar of SDGS regarding climate change is to forecast the air temperature of Bandung City in the future. One of the models that can be used for forecasting air temperature data in Bandung is the Autoregressive (AR) model. Based on BMKG data, often the time series data obtained has missing data. Therefore, in order to do a good time series analysis, it is necessary to make an effort to correct the missing data. The purpose of this research was to examine the procedure for overcoming missing data in the AR model using the Ordinary Least Squares (OLS) method and Interpolation with Weighting, which was applied to forecasting the average air temperature data in the city of Bandung. The research methodology followed the Box-Jenkins 3-step procedure. The first-order AR estimation parameter model was estimated using the OLS method and then used to overcome missing data using both methods with weighting using R software. Both methods resulted in an estimated value of 0.9991 and the same Mean Average Percentage Error (MAPE) value of 2,459% with very accurate criteria. Therefore, to overcome the missing data on the average air temperature data in the city of Bandung with a parameter estimator close to one, we got the same result for both methods.

PREDICTING DIABETES MELLITUS USING CATBOOST CLASSIFIER AND SHAPLEY ADDITIVE EXPLANATION (SHAP) APPROACH Novia Permatasari; Shafiyah Asy Syahidah; Aldo Leofiro Irfiansyah; M. Ghozy Al-Haqqoni
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Diabetes mellitus as a metabolic disease characterized by hyperglycemia can be dangerous if it cannot be handled properly. Early detection of existing symptoms can reduce the impact of delays in treatment. This study aims to carry out early-detection patients with diabetes mellitus using a machine learning approach through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score). By using Shapley Additive Explanation (SHAP) which enables prioritization of feature that determine compound classification, this study shows that the CatBoost classifier has 14 features that significantly can be used for classification with feature ‘d1_glucose_max’ or the highest glucose concentration of the patient in their serum or plasma during the first 24 hours of their unit stay has the highest impact to classify diabetes mellitus patients, then followed by age and glucose APACHE. The selected features are then classified and get the validation AUC score of 86.86%.

DYNAMICS OF THE RUMOR SPREADING MODEL OF INDONESIA TWITTER CASE Arrival Rince Putri; Muthiah As Saidah; Mahdhivan Syafwan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The study of the spreading of a rumor is significantly important to obtain scientific information and better strategies in reducing its negative impact. Twitter has become a medium for spreading rumors or hoaxes spatially and chronologically because it has a unique community structure. This study demonstrates the model of spreading rumors by considering credibility, correlation, and mass classification based on personality is discussed. The behavior of a model solution around equilibrium points is investigated with the Jacobian matrices. The stability also corresponds to a threshold number indicating the rumor fades away or continues to spread in the population. The analytical results are confirmed by actual data from Twitter in Indonesia with #SahkanRUUPKS. The simulation results show that the free rumor equilibrium point is stable and the threshold number is less than 1. Our study shows that the number of spreaders does not increase and the #SahkanRUUPKS rumor will vanish.

FORECASTING OF CURRENCY CIRCULATION IN INDONESIA USING HYBRID EXTREME LEARNING MACHINE Mujiati Dwi Kartikasari
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Forecasting currency circulation, including inflow and outflow, is one of Bank Indonesia's strategies to maintain the Rupiah value's stability. The characteristic of inflow and outflow data is that they have seasonal variations. This study proposes a hybrid model by combining decomposition techniques and Extreme Learning Machine to overcome data that has seasonal variations. The forecasting results of the proposed model are compared with the original Extreme Learning Machine. The comparison results show that the forecasting results with the hybrid model have the smallest errors. Thus, the hybrid model can predict data with seasonal variations better than the original Extreme Learning Machine.

MATHEMATICS PRE-SERVICE TEACHERS’ DIGITAL LITERACY AND THEIR READINESS TOWARDS 21ST CENTURY LEARNING: A MIXED METHOD STUDY Pranata Lulus Soeparno; Christina Ismaniati
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The rapid advancement of technology in Indonesia seems not in line with its utilization, especially in the educational field. According to studies, Indonesian teachers are not ready to implement ICT in their classrooms. Furthermore, most elderly teachers are not sensitive enough to technology changes. When it comes to emergency teaching and learning in the pandemic era, teachers as predicted do not have enough capacity to maximize the use of ICT as the only source. This study aims to find out: (1) if the lack of digital literacy skills already happened in college, and (2) pre-service teachers' readiness to face 21st century education. As the result, this study could not prove that the lack of digital skills occurs in college. The digital literacy skills of pre-service are good (77,6%) and they have received multimedia learning subject from university. Related to their readiness toward 21st century learning, most of them claimed not yet ready because of the lack of skills and knowledge in implementing ICT and because of the lack of ICT facility support.

OPTIMIZING THE PROCESS OF PICK-UP AND DELIVERY WITH TIME WINDOWS USING ANT COLONY AND TABU SEARCH ALGORITHMS Imas Saumi Amalia; Toni Bakhtiar; Jaharuddin Jaharuddin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The provision of goods shuttle services sometimes faces several constraints, such as the limitation on the number of vehicles, vehicle capacity, and service time, or the vehicle used has single transport access. To avoid losses, a strategy is needed in determining the optimal route and policy for arranging goods in the vehicle especially if there are two types of goods involved. Traveling Salesman Problem and Pick-up and Delivery with Handling Costs and Time Windows (TSPPDHTW) is a model of an optimization problem that aims to minimize the total travel and goods handling costs in the goods pick-up and delivery with the constraints previously mentioned. Solving that model using the exact method requires a very long computation time so it’s not effective to be implemented in real-life. This study aims to develop a (meta)heuristic based on Ant Colony Optimization (ACO) and Tabu Search (TS) to be ACOTS to solve TSPPDHTW with reasonable computation time. The development is carried out by adding functions of clustering, evaluating constraints, cutting tours, arranging of goods, and evaluating moves on the TS, as well as modifying transition rules. The result has a deviation of about 22% and 99.99% less computational time than the exact method.

CUSTOMER SATISFACTION ANALYSIS ON SALES ENGINEERING SERVICE USING SERVQUAL AND FACTOR ANALYSIS IN PACKAGING INDUSTRY Rheza Vahlepy; Winarno Winarno; Fahriza Nurul Azizah; Dimas Nurwinata Rinaldi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

To achieve client satisfaction, every company must be able to do its best. Companies must be able to provide services that meet or surpass their consumers' expectations to achieve customer satisfaction. As a result, the goal of this research is to look at client satisfaction with the Sales Engineer services that have been delivered. Reliability, responsiveness, assurance, empathy, and tangible customer satisfaction at PT XYZ are the characteristics used in this study. 150 consumers who were served by Sales Engineers provided the data for this study. To perform data processing, this research used SERVQUAL and Factor Analysis for determining customer satisfaction. Based on the findings of the data processing with SERVQUAL, it has been determined that two variables, Assurance, and Empathy, are capable of bringing consumer satisfaction. Based on the overall analysis using Factor Analysis, it can be concluded that the majority of the services provided by the Sales Engineer are able to meet the expectations of customers, particularly in terms of the most important factor in the emergence of customer satisfaction, to encourage these customers to be loyal to the company. Customers, as well as being responsible for and the ultimate action taken by sales in response to consumer complaints.

THE IMPACT OF BANK-SPECIFIC FACTORS ON NON-PERFORMING LOAN IN INDONESIA: EVIDENCE FROM ARDL MODEL APPROACH Lexy Janzen Sinay; Sanlly J Latupeirissa; Shelma M Pelu; Meilin I Tilukay
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Non-performing Loan (NPL) is an indicator that is generally used to determine the ability of bank management to manage non-performing loans. This study aims to analyze the impact of bank-specific factors on NPL. The bank-specific factors are Capital Adequacy Ratio (CAR), Return on Assets (ROA), Operating Expenses on Operating Income (BOPO), and Loan to Deposit Ratio (LDR). The data used is monthly time series data, a case study on Commercial Banks in Indonesia from January 2015 to August 2020. The model used to analyze these problems is Autoregressive Distributed Lag (ARDL). The results obtained are ARDL(1,6,0,1,1) model is the best model. The model shows that bank-specific factors have a direct impact on NPL. Specifically, the ARDL bounds test offers the analysis results, which show that the ability of bank-specific factors to explain the NPL of commercial banks in Indonesia is 84%. At the same time, 16% are other factors outside the model. The analysis results show a long-run cointegration relationship between NPL and specific characteristics, CAR, ROA, and BOPO. Then, only CAR, BOPO, and LDR impact NPL in the short-run relationship. The equilibrium correction obtained is significant and confirms a long-run relationship. The equilibrium correction indicates a high velocity towards stability after a shock. It means that the performance of Commercial Banks in Indonesia is outstanding during the COVID-19 Pandemic because the ability to recover from shock is relatively faster

ROBUST CLUSTERING OF COVID-19 PANDEMIC WORLDWIDE Rizki Agung Wibowo; Khoirin Nisa; Hilda Venelia; Warsono Warsono
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

COVID-19 pandemic is described as the most challenging crisis that humans have faced since World War II. From December 2019 until August 2021 based on the dataset provided by WHO, globally 219 countries in the world are affected by this virus. There are 205.338.159 cases cumulative total and 4.333.094 death cumulative total caused by this virus. In this paper, the data of 219 countries are analyzed using a robust clustering method namely K-Medoids cluster analysis. Based on the result, 219 countries in the world can be divided into five clusters based on four COVID-19-related variables, i.e. the number of cases cumulative total, death cumulative total, positive cases per capita, and case fatality rate. The distribution of the countries in five clusters was as follows; the first cluster contained 48 countries, the second cluster contained 3 countries, the third and fourth clusters contained 16 and 89 countries respectively, and the last cluster contained 63 countries. The largest cluster is the fourth one, containing countries that form a cluster with a centroid below the world average, and the smallest cluster is the second cluster with the high cases in all attributes, consisting of the USA, India, and Brazil.

FUNCTION GROUP SELECTION OF SEMBUNG LEAVES (BLUMEA BALSAMIFERA) SIGNIFICANT TO ANTIOXIDANTS USING OVERLAPPING GROUP LASSO kusnaeni kusnaeni; Agus M Soleh; Farit M Afendi; Bagus Sartono
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Functional groups of sembung leaf metabolites can be detected using FTIR spectrometry by looking at the spectrum's shape from specific peaks that indicate the type of functional group of a compound. There were 35 observations and 1866 explanatory variables (wavelength) in this study. The number of explanatory variables more than the number of observations is high-dimensional data. One method that can be used to analyze high-dimensional data is penalized regression. The overlapping group lasso method is a development of the group-based penalized regression method that can solve the problem of selecting variable groups and members of overlapping groups of variables. The results of selecting the variable groups using the overlapping group lasso method found that the functional groups that were significant for the antioxidants of sembung leaves were C=C Unstructured, CN amide, Polyphenol, Sio2.

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Yopi Andry Lesnussa, S.Si., M.Si

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+6285243358669

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barekeng.math@yahoo.com

Location
Kota ambon,

Maluku

INDONESIA

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Home Page

OAI Link

Editorial Team

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Reviewer

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Contact Name Yopi Andry Lesnussa, S.Si., M.Si

Contact Email yopi_a_lesnussa@yahoo.com

Phone +6285243358669

Journal Mail Official barekeng.math@yahoo.com

Location Kota ambon, Maluku INDONESIA

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Contact Name
Yopi Andry Lesnussa, S.Si., M.Si

Contact Email
yopi_a_lesnussa@yahoo.com

Phone
+6285243358669

Journal Mail Official
barekeng.math@yahoo.com

Location
Kota ambon,

Maluku

INDONESIA