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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
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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 1,369 Documents

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AN ORDINAL LOGISTIC REGRESSION MODEL FOR ANALYZING RISK ZONE STATUS OF COVID-19 SPREAD Dewi, Tessya Mutiara; Kusumawati, Rosita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Coronavirus disease 2019 (COVID-19) is a new type of virus that has been found to have infected human since it first appeared in Wuhan, China, in December 2019. This study aims to determine the factors that influence the risk zone status of COVID-19 spread in Indonesia using ordinal logistic regression. The ordinal logistic regression model in this study uses proportional odds model because the researcher assumes probability of predictor variable coefficients is the same for each respond category. The response variable is secondary data from the COVID-19 Handling Task Force, namely the status of the risk zone for the spread of COVID-19 who has 4 categorical levels, namely high, medium, low, and no cases. Predictor variables are elderly population, COVID-19 referral hospital, diabetes mellitus, hypertension, hand washing behavior, male population, and smoking habits. Based on results of the analysis, variables that significantly affect the risk zone status of COVID-19 spread in Indonesia are elderly population and diabetes mellitus. The Odds proportional figure shows that the higher percentage of the elderly population, the higher chance of an area with high-risk zone status (OR=1.171). The higher percentage of comorbidities diabetes mellitus, the higher chance of an area with high-risk zone status (OR=1.569).

MULTILEVEL NON-LINIER REGRESSION FOR REPEATED MEASURMENT DATA AS STUDY OF PEANUT GROWTH Purwanto, Arie; Aiman, Umul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Peanut is one of the most important legume commodities in Indonesia. In its implementation, a lot of research has been done related to this plant. However, in studies conducted by growth models, it is very rarely studied. Therefore, researchers are interested in modeling the growth of peanuts. One of the models that can be used is a multilevel regression model for the case of repeated measurement data. Multilevel regression was chosen because it is considered to provide more information than other regression models. On the other hand, the nonlinear model was chosen based on the tendency of the initial plot of the data obtained. The research method used is a case study in the study of peanut growth. This study aims to build the best model based on the tested model. The Restricted Estimator Maximum Likelihood (REML) parameter estimation method was chosen because it is considered to have unbiased parameter estimates. The best model is based on the lowest Akaike Information Criterion (AIC) generated from a predetermined model. The results obtained indicate that the multilevel parabolic regression model is the model with the best AIC size. In addition, it was found that there was an Interclass Correlation (ICC) of 81.19% which indicated a difference in variability between levels.

ON THE IRREGULARITY STRENGTH AND MODULAR IRREGULARITY STRENGTH OF FRIENDSHIP GRAPHS AND ITS DISJOINT UNION Apituley, Fredrylo Alberth Noel Joddy; Talakua, Mozart W.; Lesnussa, Yopi Andry
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

For a simple, undirected graph G with, at most one isolated vertex and no isolated edges, a labeling f:E(G)→{1,2,…,k1} of positive integers to the edges of G is called irregular if the weights of each vertex of G has a different value. The integer k1 is then called the irregularity strength of G. If the number of vertices in G or the order of G is |G|, then the labeling μ:E(G)→{1,2,…,k2} is called modular irregular if the remainder of the weights of each vertex of G divided by |G| has a different value. The integer k2 is then called the modular irregularity strength of G. The disjoint union of two or more graphs, denoted by ‘+’, is an operation where the vertex and edge set of the result each be the disjoint union of the vertex and edge sets of the given graphs. This study discusses about the irregularity and modular irregularity strength of friendship graphs and some of its disjoint union, The result given is s(Fm ) = m + 1, ms(Fm ) = m + 1 and ms(rFm ) = rm + ⌈r/2⌉, where r denotes the number of copies of friendship graphs

BINARY LOGISTICS REGRESSION MODEL TO IDENTIFY FACTORS ASSOCIATED WITH LOW BIRTH WEIGHT (LBW) (CASE STUDY: BABY DATA AT DR. M. HAULUSSY HOSPITAL AMBON) Sari, Yunita Puspita; Noya Van Delsen, Marlon S.; Lesnussa, Yopi Andry
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Low birth weight (LBW) is one of the risk factors for increasing baby mortality. LBW is characterized by a baby's birth weight of fewer than 2500 grams which is weighed within the first hour after birth. The case of LBW is of special concern because it can have a serious impact on the quality of future generations, which will slow down the growth and development of children and affect the decline in intelligence. In this study, identification was carried out to determine the factors that influence the status of BBL in RSUD Dr. M. Haulussy Ambon in 2020, the data used in this study is medical record data from RSUD Dr. M. Haulussy Ambon in 2020 with a total sample of 183 respondents with predictor variables covering nine variables and one response variable. The analysis used is a binary logistic regression method with the response variables of BBL status which are categorized as normal and low. The results of this study obtained a binary logistic regression model in which the factors that influence the case of low birth weight are maternal gestational age and parity with a classification accuracy of 91.8.

FUZZY LOGIC APPLICATION ON EMPLOYEE ACHIEVEMENT ASSESSMENT (CASE STUDY: EDUCATION QUALITY ASSURANCE INSTITUTE OF MALUKU PROVINCE) Nurhidayah, Nurhidayah; Lesnussa, Yopi Andry; Leleury, Zeth Arthur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Employee achievement assessment in an agency is essential for agency planning and evaluation. Therefore, the Employee achievement assessment must be carried out with a good and appropriate method so that it can guarantee fair and satisfactory treatment for the assessed employees. The value of employee achievement is determined by 60% of the target value of employee achievement and 40% of the average employee behavior value consisting of service orientation, integrity, commitment, discipline, and cooperation. The writing and discussion of this research are about the application of the fuzzy logic Mamdani method using MATLAB software in determining the work performance value of the Maluku Education Quality Assurance Institution (LPMP) employees based on the target value of employee achievement and behavioral values. The Mamdani method’s calculation level of truth is 94%, so it can be concluded that the fuzzy logic of the Mamdani method can be used to measure the performance value of employees.

QUOTIENT SEMINEAR-RINGS OF THE ENDOMORPHISM OF SEMINEAR-RINGS Fatimah, Meryta Febrilian; Hasnani, Fitriana; Puspita, Nikken Prima
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

A seminear-ring is a generalization of ring. In ring theory, if is a ring with the multiplicative identity, then the endomorphism module is isomorphic to . Let be a seminear-ring. Here, we can construct the set of endomorphism from to itself denoted by . We show that if is a seminear-ring, then is also a seminear-ring over addition and composition function. We will apply the congruence relation to get the quotient seminear-ring endomorphism. Furthermore, we show the relation between c-ideal and congruence relations. So, we can construct the quotient seminear-ring endomorphism with a c-ideal.

SURVIVAL ANALYSIS OF DENGUE HEMORRHAGIC FEVER PATIENTS (DHF) Khairunnisa, Firza; Saumi, Fazrina; Amelia, Amelia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Dengue Hemorrhagic Fever (DHF) is a dangerous disease transmitted by the Dengue virus. In 2020, along with the occurrence of the Covid-19 pandemic in Indonesia, the number of dengue cases in Indonesia was high. One of the provinces recorded as the highest suspected dengue fever area is North Sumatra. This is evidenced in October 2019 North Sumatra became the province with the highest suspected dengue fever in Indonesia with a total of 250 cases. Based on the medical record data of patients with DHF at the Dr. Pirngadi General Hospital, Medan in 2019, the factors thought to affect the rate of survival of DHF patients were age, gender, platelet count, and hematocrit levels. Furthermore, survival analysis was carried out using the Kaplan-Meier method and Cox Proportional Hazard Regression with the suspected factors to determine the estimated survival function for patients with DHF and to determine the factors that affect the recovery rate of patients with DHF. Based on the survival function curve, it was found that the curve decreased slowly because many patients with DHF were censored and it was found that the chances of survival of patients with DHF were relatively high, ranging from 1 to 0.6352. Based on the selection of the best model, it was found that only the age variable had a significant effect on the model.

ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBAN Mahmudah, Nur; Anggraini, Fetrika
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Cervical cancer is the most common cancer that causes death in women. This cancer is mainly caused by Human Papilloma Virus (HPV). It is estimated that 52 million of Indonesian women are at risk of having cancer, and 36% of female cancer patients suffer from cervical cancer. This type of cancer cannot be diagnosed immediately as there is several years of pre-malignancy phase; thus, early detection or screening is needed to prevent it from turning into malignant. Pap test as a screening program can detect cancer, precancer, and normal condition. To understand the predicting factors of the test results, a comprehensive mathematical modelling was created using the link function of Bayesian Ordinal Logistic Regression. This study observed several possible factors that may affect Pap test results in Tuban regency, namely Age (X1), Education (X2), Childbirth Experience (X3), Use of Contraceptives (X4), Menstrual Cycle (X5), Age of First Menstruation (X6), History of Miscarriage (X7), Anemia (X8) and Number of Sexual Partners (X9) . The outcomes indicated that the predicting factors of Pap cervical cancer results are Age (X1), Education (X2), Childbirth Experience (X3), Use of Contraceptives (X4), Menstrual Cycle (X5), and Anemia (X8). In this model, there is an inexplainable error dependency as indicated by the varied constance values of alpha.

COMPARISON OF ARIMA AND GARMA'S PERFORMANCE ON DATA ON POSITIVE COVID-19 CASES IN INDONESIA Sofro, A'yunin; Khikmah, Khusnia Nurul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

The development of methods in statistics, one of which is used for prediction, is overgrowing. So it requires further analysis related to the goodness of the method. One of the comparisons made to the goodness of this model can be seen by applying it to actual cases around us. The real case still being faced by people worldwide, including in Indonesia, is Covid-19. Therefore, research comparing the autoregressive integrated moving average (ARIMA) and the Gegenbauer autoregressive moving average (GARMA) method in positive confirmed cases of Covid-19 in Indonesia is essential. Based on the results of this research analysis, it was found that the best model with the Aikake's Information Criterion measure of goodness that was used to predict positive confirmed cases of Covid-19 in Indonesia was the Gegenbauer autoregressive moving average (GARMA) model.

PERFORMANCE COMPARISON OF GRADIENT-BASED CONVOLUTIONAL NEURAL NETWORK OPTIMIZERS FOR FACIAL EXPRESSION RECOGNITION Nurdiati, Sri; Najib, Mohamad Khoirun; Bukhari, Fahren; Revina, Refi; Salsabila, Fitra Nuvus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

A convolutional neural network (CNN) is one of the machine learning models that achieve excellent success in recognizing human facial expressions. Technological developments have given birth to many optimizers that can be used to train the CNN model. Therefore, this study focuses on implementing and comparing 14 gradient-based CNN optimizers to classify facial expressions in two datasets, namely the Advanced Computing Class 2022 (ACC22) and Extended Cohn-Kanade (CK+) datasets. The 14 optimizers are classical gradient descent, traditional momentum, Nesterov momentum, AdaGrad, AdaDelta, RMSProp, Adam, Radam, AdaMax, AMSGrad, Nadam, AdamW, OAdam, and AdaBelief. This study also provides a review of the mathematical formulas of each optimizer. Using the best default parameters of each optimizer, the CNN model is trained using the training data to minimize the cross-entropy value up to 100 epochs. The trained CNN model is measured for its accuracy performance using training and testing data. The results show that the Adam, Nadam, and AdamW optimizers provide the best performance in model training and testing in terms of minimizing cross-entropy and accuracy of the trained model. The three models produce a cross-entropy of around 0.1 at the 100th epoch with an accuracy of more than 90% on both training and testing data. Furthermore, the Adam optimizer provides the best accuracy on the testing data for the ACC22 and CK+ datasets, which are 100% and 98.64%, respectively. Therefore, the Adam optimizer is the most appropriate optimizer to be used to train the CNN model in the case of facial expression recognition.

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

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Location Kota ambon, Maluku INDONESIA

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

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yopi_a_lesnussa@yahoo.com

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+6285243358669

Journal Mail Official
barekeng.math@yahoo.com

Location
Kota ambon,

Maluku

INDONESIA