bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dimensiones actuales en la investigación del trabajo infantil en Argentina: Una sistematización teórica
Authors: Miño María Gabriela , Gómez Raimundo Elías 
Published: August 2022

El artículo presenta los resultados de un análisis cualitativo sobre las principales dimensiones del trabajo infantil actualmente estudiadas en Argentina. Considerando los abordajes y perspectivas presentes en las investigaciones de los últimos 5 años sobre el tema, se retomaron los siguientes ejes de discusión: 1) los procesos macro-económicos estructurales como principales condicionantes del trabajo infantil; 2) la importancia del contexto sociocultural y los estudios que reivindican la agencia de los niños y las niñas como posibles informantes; 3) las posturas que inciden en los riesgos, considerando el trabajo infantil como una forma de desprotección estatal y 4) los estudios que representan cuestiones de género, como variable diferencial en las trayectorias infantiles. En cuanto a su metodología, el trabajo se fundamenta en una revisión sistemática de fuentes bibliográficas secundarias de los repositorios SCOPUS, SCIELO, DIALNET y REDALYC, utilizando el software MAXQDA. A modo de conclusión sugerimos que las investigaciones actuales sobre trabajo infantil en Argentina presentan desafíos en relación a sus abordajes, interpelándonos a una necesaria reconceptualización situada de sus categorías en estudio.
The Influence of Work Diversity on Organizational Performance in the Hospitality Sector in the UAE: The Moderating Role of HR Practices
Authors: Khassawneh Osama , Mohammad Tamara 
Published: August 2022

<p>The structure of workplace in hospitality sector has become apparently diverse. As a vital step in defining how diversity affects organizational performance, we suggested training as a mediator over which diversity in income level and race indirectly affects organizational performance. We also emphasized two human resource practices, namely, rewards and performance appraisal, as important possibilities that moderate the impact of employee diversity on training and organizational performance. A sequential regression analysis was applied on performance appraisal data including information from directors, unit managers, supervisors, low level workers, and customers, as well as financial outcomes from 167 organizations in the United Arab Emirates (UAE) (683 full time employees) in the hospitality sector including hotels, restaurants, theme parks, travel agents, recreational centers, and museums, which assisted in supporting the hypotheses. The findings provide unique practical and theoretical understandings into the effective management of employee diversity.</p>
ABOUT CONNECTION AUTOIMMUNE THYROIDITIS WITH MANIFESTATION OF IRON DEFICIENCY ANEMIA IN A CONDITION OF HYPOTHYROIDISM IN GENERAL CLINICAL PRACTICE. CLINICAL CASE
Authors: Nikolaienko-Kamyshova T. P. , Akhe E.A. 
Published: August 2022

Summary: Anemia is a global public health problem that needs to be identified. When determining the algorithms for examination and treatment of anemic syndrome, it is necessary to carefully study the risk factors for its development, taking into account comorbidity. Carrying out of diagnostic search in several directions will allow to specify mechanisms of development of an anemic syndrome which at a combination worsen a clinical condition.
Special attention should be paid to patients with manifestations of anemic syndrome on the background of endocrine pathology, namely autoimmune thyroiditis in hypothyroidism, as the incidence rate among women of childbearing age has increased significantly, which determines the direction of research and aim of this publication.
The article presents a clinical case of observation and treatment of a patient with chronic autoimmune thyroiditis in a state of hypothyroidism and adenomyosis, accompanied by abnormal uterine bleeding, which was complicated by iron deficiency anemia. Because the patient initially considered uterine bleeding to be the main problem, she was observed by a gynecologist; at the same time changes of indicators of the general analysis of blood in favor of anemia are established. Treatment of endometriosis and the appointment of iron supplements led to improvement with the normalization of laboratory parameters. For 6 months the patient did not consult a doctor, no laboratory control was performed. If she felt worse, the patient consulted a family doctor. Careful examination with the involvement of an endocrinologist allowed to diagnose chronic autoimmune thyroiditis in a state of hypothyroidism and prescribe adequate therapy, which helped to normalize the patient's condition.
Conclusion. Manifestations of anemic syndrome require determining the causes of its occurrence with the development of algorithms for examination and monitoring of treatment. The general practice physician should be the main coordinator in studying the causes of anemia and the management of patients in the outpatient phase with the involvement of physicians of other specialties.
LEFT VENTRICULAR REMODELING IN HEART FAILURE (PART I): CURRENT UNDERSTANDING OF PATHOMECHANISMS AND RELATED MYOCARDIAL DYSFUNCTION
Authors: Chursina T.Ya. , Kravchenko A.M. , Mikhaliev K.O. 
Published: August 2022

Aim: to provide a literature review of the current data on various pathomechanisms of left ventricular (LV) remodeling in heart failure (HF) patients and their role in the development and progression of myocardial dysfunction. This paper is a first part of the review, devoted to the current state of pathophysiology of LV remodeling in HF.
Material and methods. The thematic scientific papers, published during the last decade, constituted the study material. The research methodology involved bibliosemantic method and structural and logical analysis.
Results and discussion. LV remodeling is the result of complex changes at the molecular, cellular and tissue levels, affecting the myocardial mass, geometry and performance, and ultimately leading to HF development and progression. LV systolic dysfunction occurs through the numerous mechanisms, including the defects in sarcomere function, abnormal excitation-contraction coupling and calcium homeostasis, ion channel dysfunction, mitochondrial and metabolic abnormalities, depressed cardiomyocytes survival signaling, redox pathobiology, inflammation and inadequate vasculogenesis. The term «LV diastolic dysfunction» covers the alterations in diastolic distensibility, filling or relaxation of the LV, regardless of whether LV (global) systolic function is normal or abnormal, and regardless of whether the patient has clinical manifestations of HF. The up-to-date pathophysiological paradigm of the development and progression of HF with LV diastolic dysfunction and preserved LV (global) systolic function considers systemic inflammation as a key pathomechanism of structural and functional changes of the myocardium, promoted by various cardiovascular and extracardiac conditions. In its turn, the systemic inflammation promotes endothelial dysfunction, contributing to multiple end-organ damage.
Conclusion. The deepening one`s knowledge of various pathomechanisms of LV remodeling and related myocardial dysfunction in HF patients is an important prerequisite for identifying new perspectives on further fundamental research аnd more rational designing of future clinical trials.
THE EFFECT OF SELF-EFFICACY AND EMOTIONAL INTELLIGENCE ON PROJECT-BASED LEARNING IN VOCATIONAL EDUCATION
Authors: Martanto Rohmat , Sudira Putu , Mutohhari Farid , Nurtanto Muhammad , Astuti Melinda 
Published: August 2022

Project-based learning does not only require hard skills, but requires a balance of soft skills and student self-development. This study aims to analyze how much influence self-efficacy and emotional intelligence have on the quality of product outcomes in project-based learning and analyze the determinant factors. A total of 228 vocational education students were involved in this study. Data were collected through questionnaires measuring self-efficacy and emotional intelligence, and product evaluation observation sheets. Data were analyzed using multiple linear regression analysis and confirmatory factor analysis. The results showed that self-efficacy and emotional intelligence had a significant effect on the quality of students' products. The level of experience, social skills, and quality of materials are the determinants of each variable. Various student self-development efforts to foster self-efficacy are very important to do to improve product quality. In addition to strengthening students' emotional intelligence, it is also very important to improve the quality of project-based learning outcomes. AbstrakPembelajaran berbasis proyek tidak hanya membutuhkan keterampilan keras, tetapi membutuhkan keseimbangan soft skill dan pengembangan diri siswa. Studi ini bertujuan untuk menganalisis seberapa besar pengaruh self-efficacy dan kecerdasan emosional terhadap kualitas hasil produk dalam pembelajaran berbasis proyek dan menganalisis faktor penentu. Sebanyak 228 siswa pendidikan kejuruan terlibat dalam penelitian ini. Data dikumpulkan melalui kuesioner yang mengukur self-efficacy dan kecerdasan emosional, dan lembar pengamatan evaluasi produk. Data dianalisis menggunakan analisis regresi linier berganda dan analisis faktor konfirmasi. Hasil penelitian menunjukkan bahwa self-efficacy dan kecerdasan emosional memiliki efek yang signifikan pada kualitas produk siswa. Tingkat pengalaman, keterampilan sosial, dan kualitas bahan adalah penentu dari setiap variabel. Berbagai upaya pengembangan diri siswa untuk menumbuhkan self-efficacy sangat penting dilakukan untuk meningkatkan kualitas produk. Selain memperkuat kecerdasan emosional siswa, juga sangat penting untuk meningkatkan kualitas hasil pembelajaran berbasis proyek.
QUANTITATIVE STUDY OF TAXPAYER COMPLIANCE IN JAKARTA
Authors: Amalia Aan 
Published: August 2022

Taxes are the main source of income and are the driving force for development, so the central and local governments need to take real action in increasing public awareness in paying taxes. This research actually wants to see and analyze how the determining factors in creating awareness of paying taxes, including the motivation to pay taxes, tax services organized by the government, sanctions and the ability to pay taxes. In the proof, this research uses quantitative method with path regression analysis. The research was conducted at Jakarta tax office with a total of 100 respondents. Respondents in this study were Jakartans who were registered as taxpayers in South Jakarta. In taking the sample, a simple random technique was used, namely taxpayers who were willing to fill out a questionnaire. In the results of the study, it can be seen that, either in partial or joint models, there is a strong relationship between motivation, sanctions, economic/financial conditions of taxpayers, tax services and awareness of paying taxes. However, the most dominant thing from all models is that people will be more aware of paying taxes if there are sanctions in the form of administrative fines.Keywords: Tax Awareness, Tax Obedience, The Spirit of Paying Taxes, Financial Condition, Tax Services
Digital technologies as a factor in increasing the competitiveness of educational services in the context of the spread of online learning
Authors: Frolova E. V. , Rogach O. V. 
Published: August 2022

Ensuring the high quality of online learning is one of the most significant factors in the competitiveness of universities in the educational market. The purpose of the article is to analyze the specifics of online learning for students in the context of the epidemiological crisis, to study the role of digital technologies, digital competence of teachers in improving the competitiveness of educational services. The authors used a set of methods, which included: a questionnaire survey of students of Russian universities conducted in May 2020 (N = 146 people), the focus group method (12 full-time students). A drop in the level of self-organization and self-control of students has been established, students reduce the requirements for themselves as active participants in the educational process. The conclusion is confirmed that the interest of students in online learning is connected with the teacher’s charisma, his ability to teach, while entertaining, as well as with the teacher’s active use of digital innovative technologies. The conducted research allowed us to conclude that there are a number of restrictions that limit the preservation of the quality of educational services in the context of online learning: digital inequality, insufficient development of the digital infrastructure of universities and the use of digital systems for organizing educational activities. Certain risks for maintaining the competitiveness of the university in the long term are: the inability of universities to develop high-end, comprehensive, scalable digital solutions, the request for simplification of educational work by young people due to the general availability of information materials on the Internet, high costs for updating information systems, maintaining a developed digital educational environment.
COMPARISON OF MULTILAYER PERCEPTRON’S ACTIVATION AND OP-TIMIZATION FUNCTIONS IN CLASSIFICATION OF COVID-19 PATIENTS
Authors: Pardede Doughlas , Firmansyah Ichsan , Handayani Meli , Riandini Meisarah , Rosnelly Rika 
Published: August 2022

Abstract: Patient’s symptoms could be used as features in Covid-19 classification. Using multi layer perceptron, the classification uses data set that contains patient’s diagnosis which has Covid-19 symptoms dan processes the data set to see if the patient is Covid-19 positive or not. This paper compare four activation function such as identity, logistic, ReLu and tanh and combined them with optimizer such as L-BFGS-B, SGD and Adam. Using 5-fold and 10-fold cross validation technique to get the accuracy, F1, precision and recall values, the result that we get is that logistic function with L-BFGS-B optimizer and ReLu function with L-BFGS-B optimizer are the best combinations. The logistic function with SGD optimizer, ReLu function with Adam optimizer and tanh function with Adam optimizer are the worst combinations according to their accuration values. The logistic function with SGD optimizer is the worst combination according to its F1 value. The logistic function with SGD optimizer and tanh function with L-BFGS-B optimizer are the worst combinations according to their precision values. The logistic function with SGD optimizer, ReLu function with Adam optimizer and tanh function with Adam optimizer are the worst combinations according to their recall values. Keywords: activation function, covid-19; multi layer perceptron; optimizer algorithm Abstrak: Diagnosa gejala yang dialami pasien dapat digunakan sebagai fitur dalam klasifikasi penderita Covid-19. Dengan multi layer perceptron, klasifikasi dilakukan menggunakan data set yang berisi hasil diagnosa pasien yang memiliki gejala Covid-19 dan selanjutnya diolah untuk melihat apakah memang pasien tersebut menderita Covid-19 atau tidak. Penelitian ini membandingkan fungsi aktivasi identity, logistic, ReLu dan tanh yang dikombinasikan dengan algoritma optimasi L-BFGS-B, SGD dan Adam. Hasil evaluasi cross validation menggunakan 5-fold dan 10-fold digunakan sebagai dasar menentukan kombinasi yang terbaik dan terburuk, dengan hasil yang menunjukkan bahwa kombinasi fungsi logistic dengan optimasi L-BFGS-B dan fungsi ReLu dengan optimasi L-BFGS-B merupakan kombinasi terbaik. Kombinasi fungsi logisctic dengan optimasi SGD, fungsi ReLu dengan optimasi Adam dan fungsi tanh dengan optimasi Adam merupakan yang terburuk dari nilai accuracy. Kombinasi fungsi logistic dan optimasi SGD merupakan kombinasi terburuk dari nilai F1. Kombinasi fungsi logistic dengan optimasi SGD dan fungsi tanh dan optimasi L-BFGS-B merupakan yang terburuk dari nilai precision. Kombinasi fungsi logisctic dengan optimasi SGD, fungsi ReLu dengan optimasi Adam dan fungsi tanh dengan optimasi Adam merupakan kombinasi terburuk dari nilai recall. Kata kunci: algoritma optimasi; covid-19; fungsi optimasi; multi layer perceptron
ANALYSIS OF SVM AND NAIVE BAYES ALGORITHM IN CLASSIFICATION OF NAD LOANS IN SAVE AND LOAN COOPERATIVES
Authors: Riyadi Sugeng , Siregar Muhammad Mizan , Margolang Khairul fadhli Fadhli , Andriani Karina 
Published: August 2022

Abstract: Non-performing loan (NPL) is a risk that credit unions must face and to avoid that, prospective debtors need to be surveyed. With previous loan data, support vector machine and naïve bayes can be used as classification methods to give a decision about NPL. We use a data set with 61 data and process the data with orange 3.30 application to see the difference between SVM using linear (SVM-L), polynomial (SVM-P), RBF (SVM-R) and sigmoid (SVM-S) kernel with naïve bayes. We use a cross validation technique with various folds to measure the classification results and a convusion matrix to measure the data training classification results. Naïve bayes scores the highest in terms of accuracy and SVM-R scores the highest in terms of F1, precision and recall. SVM-P scores the lowest in terms of accuracy, F1, precision and recall. Naïve bayes scores the highest in terms of proportion of predicted for true negative class and proportion of actual for true positive class. SVM-S scores the highest in terms of proportion of predicted for true positive class and proportion of actual for true negative class. SVM-P scores the lowest in both proportion of predicted and proportion of actual. Keywords: classification; naïve bayes; non-performing loan; support vector machine Abstrak: Kredit macet merupakan resiko yang sering dialami koperasi simpan pinjam, sehingga perlu dilakukan survei terhadap calon debitur agar kredit menjadi sehat. Dengan menggunakan data pemberian kredit sebelumnya, support vector machine dan naïve bayes digunakan sebagai metode klasifikasi untuk memberikan keputusan macet atau tidaknya kredit anggota koperasi Mutiara Sejahtera. Data set yang berjumlah 61 data diolah menggunakan aplikasi Orange 3.30 dan dilihat perbandingan antara metode SVM dengan kernel linear, polynomial, RBF dan sigomoid dengan metode naïve bayes. Cross validation dengan jumlah fold bervariasi digunakan sebagai nilai ukur klasifikasi dan convusion matrix digunakan sebagai nilai ukur klasifikasi data training. Hasil yang diperoleh adalah naïve bayes memiliki nilai accuracy tertinggi dan SVM kernel RBF memiliki nilai F1, precision dan recall tertinggi. SVM kernel polynomial memiliki nilai terendah untuk accuracy, F1, precision dan recall. Naïve bayes memiliki nilai tertinggi untuk proportion of predicted (PoP) kelas true negative dan proportion of actual (PoA) kelas true positive. SVM kernel sigmoid memiliki nilai tertinggi untuk PoP kelas true positive dan PoA kelas true negative. SVM kernel polynomial memiliki nilai terendah baik untuk PoP maupun PoA true negative dan kelas true positive. Kata kunci: klasifikasi; kredit macet; naive bayes; SVM
DEVELOPMENT OF A SYSTEM FOR FORECASTING THE AMOUNT OF DODOL SALES USING THE WEIGHTED MOVING AVERAGE METHOD
Authors: Sindia Rindi , Siregar Iqbal Kamil , Ihsan MHD 
Published: August 2022

Abstract: Dodol is a type of sweet food made from palm sugar that is processed with various flavors and takes a long time to complete. Dodol is also a type of food in great demand by the public due to its elasticity and characteristic taste. The manufacture and sale of this lunkhead are produced by UD. Maya Sari is located in the Kisaran area, especially in the Tanjung Alam Village, Dusun 3, Asahan Regency. Forecasting (forecasting) is thinking about a quantity, for example. The number of product requests for the future. Difficulties in forecasting inventory are often experienced by businesses, including UD. Maya Sari is difficult to predict the supply of lunkhead for the future. The research conducted by this author aims to build a system that can predict sales for the future in increasing a business's income. The system is well designed with PHP and UML for system workflow. Keywords: Dodol sales; Forecasting System; Weighted Moving Average Method Abstrak: Dodol merupakan salah satu jenis makanan manis berbahan dasar gula aren yang diolah dengan berbagai rasa dan membutuhkan waktu yang lama dalam pembuatannya. Dodol juga merupakan jenis makanan yang banyak diminati oleh masyarakat karena kekenyalan dan rasa yang khas. Pembuatan dan penjualan dodol ini diproduksi oleh UD. Maya Sari yang berada di kawasan Kisaran khususnya di Desa Tanjung Alam Dusun 3 Kabupaten Asahan. Peramalan (forecasting) adalah memikirkan kuantitas. Misalnya Jumlah permintaan produk untuk masa yang akan datang. Kesulitan dalam peramalan persediaan seringkali dialami oleh para pelaku usaha, termasuk UD. Maya Sari sulit memprediksi pasokan dodol untuk masa depan. Penelitian dilakukan. Hal ini bertujuan untuk membangun sebuah sistem yang dapat memprediksi penjualan dimasa yang akan datang guna meningkatkan pendapatan usaha. Sistem ini dirancang dengan baik dengan PHP dan UML untuk alur kerja sistem. Kata Kunci : Metode Weighted Moving Average; Penjualan dodol; Sistem Peramalan