bluuebunny/crossref_metadata_2025 huggingface dataset:
FATORES DE RISCO E ASSOCIADOS AO COMPORTAMENTO SUICIDA NO BRASIL: UMA REVISÃO SISTEMÁTICA
Authors: Rocha Lopes Luciene Oliveira , Jesus Robert Santos Messias , Souza Ronaldo Santhiago Bonfim , Teodoro Maycoln Leôni Martins
Published: July 2023

O comportamento suicida é um grave problema de saúde pública, motivado por diversos fatores de risco que incluem aspectos genéticos, psicológicos, sociais e culturais. O objetivo do estudo é analisar a literatura específica destes fatores para tentativas de suicídio no Brasil. Trata-se, portanto, de uma revisão sistemática sobre este tema. Os dados foram coletados nas principais bases de dados a partir dos seguintes descritores: “fatores associados e de risco”; “tentativa de suicídio e suicídio”; “Brasil”. Os resultados demonstraram que os fatores apresentados pela literatura mundial também estão em sua maioria presentes no Brasil. Os estudos com fatores associados e de risco para o comportamento suicida podem colaborar com programas de intervenção para grupos específicos, mas estes ainda são escassos no Brasil e são necessárias novas pesquisas que abordem esta temática.
¿Es solo un chiste? Los usos del humor hostil en la escuela y su relación con el bullying
Authors: Villota Margarita , Ferroni Paolo , Urbano Cristian , Ramirez Rueda Luisa Fernanda
Published: July 2023

Objetivo: Comprender la percepción de los estudiantes de dos colegios de Colombia sobreel uso del humor en el contexto educativo.Metodología: Estudio de caso de corte cualitativo, con alcance descriptivo. Instrumento: Matriz ad hoc sobre “rutas de convivencia escolar” enfocada en una situación de humor en la escuela. Participantes: n = 160 estudiantesadolescencia media y temprana. Resultados: Desde la perspectiva de los estudiantes, el bullying se usa como sinónimo de burla; lo que sugiere que los episodios de agresión se acompañan por un uso hostil del humor. Además, el uso del humor hostil en la escuela se relaciona con reafirmación de jerarquías, discriminación y exclusión. Conclusiones: Es importante continuar ahondando en la relación del humor hostil con el bullying para programas de intervención escolar más contextualizados y, que, usen el humor como una forma para identificar potenciales problemas de intervención evitando que se normalice expresiones más sutiles dela violencia escolar.
Pengaruh Flexible Work Arrangement (FWA), Compensation, dan Career Development terhadap Job Satisfaction dan Pengaruhnya terhadap Turnover Intention dan Job Performance
Authors: Pratama S. Kurnia Indy , Tanuwijaya Justine
Published: July 2023

The development of competition in the digital era requires reliable human resources. In this digital era, human resources have an important part in helping an organization to chase organizational goals. However, it cannot be denied that organizational competition for human resources is a concern for an organization. This competition has an impact on the turnover intention of every employee in the organization. This study aimed to analyze the effect of FWA, compensation, and career development variables on job satisfaction as well as to analyze the effect of job satisfaction on job performance and turnover intention and the effect of job performance on turnover intention. The data processing method in this study used structural equation modeling (SEM). The results of the study indicate that career development has an effect on job satisfaction, FWA and compensation have no effect on job satisfaction, job satisfaction has an effect on job performance and turnover intention, and job performance has no effect on turnover intention.
Karakteristik Manajemen dan Kepemimpinan Transformasional sebagai Penentu Kreativitas Karyawan yang Dimediasi oleh Kepuasaan Kerja
Authors: Sofyan Joel Faruk , Rianty Mardina
Published: July 2023

Many organizational top managers are increasingly aware of the importance of innovation as a precondition to maintaining sustainable organizational growth. Moreover, creativity is also often seen as the main driving force for innovation. The aim of this study is to analyze the effects of management characteristics represented by the dimensions of supervisor’s humility and abusive supervision, and transformational leadership on employee creativity mediated by employee job satisfaction. Utilizing a purposive sampling method, this study selected 260 back-office employees who work at banks in Indonesia and the online survey was administered during the period of June to July 2022. Employing PLS-SEM as an inferential analysis tool, this study found that a supervisor’s humility and transformational leadership have positive effects, whereas abusive supervision has a negative effect on employees’ job satisfaction. Furthermore, employee job satisfaction was also found to mediate the effects of supervisor’s humility, abusive supervision, and transformational leadership towards employee creativity.
Financial Distress, Audit Quality, and Earnings Management–Indonesia's Mining Sector Evidence
Authors: Wiratno Dwi Haryono , Krismiaji Krismiaji , Handayani Handayani , Sumayyah Sumayyah
Published: July 2023

This paper describes research that investigated the association between financial distress (Dist) and accrual earnings management (AEM), and the role played by audit quality (AQ) in that association. Financial distress is measured by The Modified Altman Z-Score for emerging markets (EMZ score), earnings management is measured by discretionary accrual, and audit quality is measured by audit-firm size (Big4). Data analysis was performed with Pooled Least Square. Using data from Indonesian Mining Sector for 2016–2020, the research finds empirical evidence that financial distress firms involve in income-increasing accrual earning management, but such involvement is lower when firms are audited by Big 4 audit firms. This research contributes to previous literature about similar issues, specifically about the impact of financial distress on accrual earnings management. It also presents evidence about the role of audit quality in such an effect.
influência da moda na dominação dos corpos femininos e a ruptura do preconceito
Authors: Barbosa Bibiana Paschoalino , Kazmierczak Luiz Fernando
Published: July 2023

O estudo sobre a influência da moda na dominação dos corpos femininos vai muito além da compreensão do que é considerado feminino ou masculino. Entender essa relação é desvelar conceitos intrínsecos aos costumes da moda enquanto manifestações de comportamentos machistas perpetrados e legitimados por uma cultura androcêntrica. Para tanto foi utilizado o método hipotético-dedutivo aliado a estudos bibliográficos e ao método de análise de conteúdo empregado no exame qualitativo de campanhas publicitárias de moda. Referida metodologia levou a conclusão de que a moda pode ser utilizada como mecanismo de ruptura de preconceitos de gênero.
A tributação 4.0 e a sustentabilidade do sistema previdenciário brasileiro
Authors: Marchetti Filho Gilberto Ferreira , Ribeiro Juliana de Oliveira Xavier , Alves Corrêa Láua Carolina
Published: July 2023

O sistema tributário do Estado é sua base de fonte de custeio. Esse sistema, modernamente, precisa atender não só as despesas regulares do Estado, mas sustentar políticas públicas que visam o bem-estar e qualidade de vida da população. Dentro desses aspectos, esse sistema deve custear de maneira satisfatória o sistema previdenciário social. Entrementes, a modernidade, plasmada na globalização e virtualização, trouxe a revolução 4.0 na indústria e no comércio, o que tem impactado o tradicional sistema tributário, que consegue acompanhar essa evolução. Seguindo essa linha, em revisão bibliográfica e da legislação, observando a metódica exploratória descritiva, esta pesquisa objetiva analisar a tributação 4.0 e a contribuição previdenciária das empresas sobre a folha de salário, principalmente na sua desoneração. Pretende demonstrar a necessidade de uma reforma tributária, dentro do campo da tributação 4.0, para auxiliar na manutenção do custeio do sistema previdenciário, sem onerar ou sobrecarregar demais as empresas.
O princípio da livre iniciativa e a efetivação dos direitos fundamentais como ferramentas do desenvolvimento sustentável
Authors: Arakaki Allan Thiago Barbosa , Ribeiro Maria de Fátima
Published: July 2023

A corrente pesquisa objetiva tratar da possibilidade de se conciliar ou não o princípio da livre iniciativa e a efetividade dos direitos fundamentais como instrumentos do desenvolvimento sustentável. Para tanto, é empreendida uma pesquisa bibliográfica e o método aplicado é o dedutivo. O referencial teórico utilizado neste trabalho se centra na Análise Econômica do Direito, máxime no que concernir aos conceitos de eficiência de Pareto, sem prejuízo da utilização da teoria do desenvolvimento articulada por Amartya Sen. O estudo avança ao constatar que a ponderação, a proporcionalidade e a eficiência de Pareto podem atuar conjugadas para se alcançar o equilíbrio entre as necessidades presentes e futuras. Como resultado, constatou-se que, por meio da técnica da ponderação, o princípio da livre iniciativa admite restrições, tendo por norte o desenvolvimento socioeconômico sustentável.
Tem gente com fome: interfaces do ODS12 da agenda 2030, o Código de Defesa do Consumidor e o desperdício de alimentos
Authors: Gonçalves Vinícius Viana , Silveira Sheila Stolz
Published: July 2023

A Agenda 2030 da Organização das Nações Unidas propõe objetivos e metas importantes largamente debatidas no que foi o processo de consulta mais amplo e participativo da história da ONU. Os Objetivos de Desenvolvimento Sustentável (ODS) que compõe a Agenda 2030, têm como metas primordiais a erradicação da pobreza (ODS 1) e a eliminação da fome e da desnutrição (ODS 2), o que implica a interconexão destes objetivos com os demais e requer, entre outras prerrogativas, o consumo e produção responsáveis e sustentáveis (ODS 12). Logo, o acesso equânime de toda a população brasileira à alimentação adequada além de observar as diretrizes estipuladas pela Agenda 2030, é um direito fundamental de todas (os) consumidoras (es) previstos no Artigo 6° da Constituição Federal de 1988 (CF/1988) e no Código de Defesa do Consumidor de 1990 (CDC). Os estudos e investigações desenvolvidas e parcialmente transcritas neste artigo, têm por objetivo analisar as interconexões entre a Agenda 2030 e o Artigo 18 do Código de Defesa do Consumidor (CDC) como garantidores de Direitos Humanos.
Challenges and Best Practices Solution of Agile Project Management in Public Sector: A Systematic Literature Review
Authors: Abdullah Puja Putri , Raharjo Teguh , Hardian Bob , Simanungkalit Tiarma
Published: July 2023

Applying Agile methodologies in the public sector is nothing new. In recent years, governments worldwide have moved towards Agile development, especially with the Pandemic that requires governments to move and make decisions quickly. However, the difference between the government system and the private sector, such as holding the principle of a hierarchy of authority, still challenges Agile application. This study aims to explore challenges and provide solutions for applying Agile project management in the public sector by conducting a systematic literature review (SLR) using the PRISMA method. The literature used in the SLR was obtained from four paper databases, namely Scopus, IEEE Xplore, ACM, and Emerald Insight. Five hundred ninety-five papers were found, and 18 suitable papers were obtained, which were then analyzed and obtained a total of 43 challenging issues. Each of these issues is grouped based on eight project performance domains of PMBOK 7th edition, and the solution for each challenge is obtained from the mapping results from the SLR papers and PMBOK 7th edition Guide. The results showed that the most issues were in the Development Approach and Lifecycle and Project Work domain categories, with 8 issues each. Followed by Team with 7 issues, Stakeholder with 6 issues, Delivery with 5 issues, Measurement with 4 issues, Planning with 3 issues, and Uncertainty with 2 issues. This research can be useful for academics or practitioners as a reference in facing the challenges of implementing Agile project management in the public sector
A Framework for Malay Computational Grammar Formalism based-on Enhanced Pola Grammar
Authors: Mohamed Hassan , Abdul Fataf Nur Aisyah , Tengku Sembok Tengku Mohd
Published: July 2023

In the era of IR4.0, Natural Language Processing (NLP) is one of the major focuses because text is stored digitally to code the information. Natural language understanding requires a computational grammar for syntax and semantics of the language in question for this information to be manipulated digitally. Many languages around the world have their own computational grammars for processing syntax and semantics. However, when it comes to the Malay language, the researchers have yet to come across a substantial computational grammar that can process Malay syntax and semantics based on a computational theoretical framework that can be applied in systems such as e-commerce. Hence, we intend to propose a formalism framework based on enhanced Pola Grammar with syntactic and semantic features. The objectives of this proposed framework are to create a linguistic computational formalism for the Malay language based on theoretical linguistic; implement templates for Malay words to handle syntax and semantic features in accordance with the enhanced Pola Grammar; and create a Malay Language Parser Algorithm that can be used for digital applications. To accomplish the objectives, the proposed framework will recursively formalise the computational Malay grammar and lexicon using a combination of solid theoretical linguistic foundations such as Dependency Grammar. A Malay parsing algorithm will be developed for the proposed model until the formalised grammar is deemed reliable. The findings of this indigenous Malay parser will help to advance Malay language applications in the digital economy.
Classification of Malaria Cell Image using Inception-V3 Architecture
Authors: Minarno Agus Eko , Aripa Laofin , Azhar Yufis , Munarko Yuda
Published: July 2023

Malaria is a severe global public health problem caused by the bite of infected mosquitoes. It can be cured, but only with early detection and effective, quick treatment. It can cause severe conditions if not properly diagnosed and treated at an early stage. In the worst scenario, it can cause death. This study aims at focusing on classifying malaria cell images. Malaria is classified as a dangerous disease caused by the bite of the female Anophles mosquito. As such, it leads to mortality when immediate action and treatment fails to be administered. In particular, this study aims to classify malaria cell images by utilizing the Inception-V3 architecture. In this study, training was conducted on 27,558 malaria cell image data through Inception-V3 architecture by proposing 3 scenarios. The proposed scenario 1 model applies the SGD optimizer to generate a loss value of 0.13 and an accuracy value of 0.95; scenario 2 model applies the Adam optimizer to generate a loss value of 0.09 and an accuracy value of 0.96; and lastly scenario 3 implements the RMSprop optimizer to generate a loss value of 0.08 and an accuracy value of 0.97. Applying the three scenarios, the results of the study apparently indicate that the Inception-V3 model using the RMSprop optimizer is capable of providing the best accuracy results with an accuracy of 97% with the lowest loss value, compared to scenario 1 and scenario 2. Further, the test results confirms that the proposed model in this study is capable of classifying malaria cells effectively.
Utilization of Business Analytics by SMEs In Halal Supply Chain Management Transactions
Authors: Marjudi Suziyanti , Setik Roziyani , Raja Lope Ahmad Raja Mohd Tariqi , Wan Hassan Wan Azlan , Md Kassim Aza Azlina
Published: July 2023

Halal supply chain management has transformed beyond food and beverage certification. However, extant literature shows that Halal transaction management still has much to improve in terms of transaction permissibility, with the main gap in understanding Halal businesses and their transactions limited to a system that separately defines e-commerce and financial technology data into its IT business environment. This study aims to demonstrate the usefulness of managing Halal transactions and its permissibility analysis through a proposed Halal Supply Chain Management Transactions (HSCMT) model and prototype by applying a business analytic approach to integrate both e-commerce and financial technology data. The study uses literature analysis to ensure the correct structure of the integrated datasets, before modeling the transaction's permissibility and prototyping its analytics into decision-making analytics. The developed HSCMT prototype uses a payment gateway that can be embedded into a Halal SME owners' e-commerce site. This creates a holistic Halal Financial technology (FinTech) transaction permissibility dashboard, increasing the effectiveness of HSCMT for Malaysia Halal SME Owners (MHSO) by an average usability score of 83.67%. Results also indicate that the key basic mechanisms to verify transactional permissibility are the source of the transaction, the use of the transaction, transaction flow, and transaction agreement. Furthermore, its mechanisms must be mapped onto a submodule post-transformation and modeling of the transaction dataset. Further improvements in multisource data points can be further considered, as this research only focuses on local data points from one payment gateway service. This is due to restrictions in data policy when involving overseas supply chain and transaction documentation. This research utilizes available data in business through data management, optimization, mining, and visualization to measure performance and drive a company's growth. The competency of business analytics can be beneficial to Halal SMEs players because it can provide them with insights into the permissibility decision-making process.
Value-based modeling and simulation for sustainable ICT4D
Authors: Omotola Akindoyo Oluwatosinloba , Waishiang Cheah , Khairuddin Muhammad Asyraf bin , Jalil Nurfauza binti , Phang Eaqerzilla
Published: July 2023

ICT4D is an acronym for information and communication technologies for development. This acronym represents the many initiatives that are now being carried out in underdeveloped countries all around the globe. These technology-oriented initiatives aim to promote the growth and prosperity of the regions they serve. People from the local community often volunteer their time to serve as program managers when NGOs or governments give funding. The term "sustainability" describes an information and communications technology's capacity to carry out a development project even after the initial funding has run out. The e3value technique will be broken down in this article so that we may better understand how it works. Using various tools for value-based modeling, this method is utilized to create an e-Business model. However, one of the main problems with e-business technologies is that they often get insufficient data to be effective. This study aims to examine the procedures that must be followed to learn more about an e-Business concept and mold it into a form that would allow for its implementation in a technologically and commercially practical manner. In order to gather information on the Long Lamai community's economic activities, a survey is being used in this research. The net value sheet for each of their businesses is then stimulated utilizing the data using E3 value. Initial findings indicate that 5 out of 13 enterprises' net incomes are negative, and each of those five businesses has its roots in a local enterprise. However, the figure does not consider labor costs, taxes, or long-term investments made with government money. We continued the stimulation with sensitivity analysis and scenario-based analysis, which results in total revenue of 1,410,000 for the five enterprises in the fourth year after accounting for taxes and fees in the sensitivity analysis. This opens the door for further research into how discrepancies in wealth and income may arise in the simulation of an economy due to the right use of ICT for long-term development and prosperity. Profitability sheets may be created if certain business model assumptions are specified, such as the monetary value of the commodities produced, distributed, and consumed. These may be used to decide if the project can become profitable for all parties concerned.
Implementation of CRNN Method for Lung Cancer Detection based on Microarray Data
Authors: Khoirunnisa Azka , Adiwijaya - , Adytia Didit
Published: July 2023

Lung Cancer is one of the cancer types with the most significant mortality rate, mainly because of the disease's slow detection. Therefore, the early identification of this disease is crucial. However, the primary issue of microarray is the curse of dimensionality. This problem is related to the characteristic of microarray data, which has a small sample size yet many attributes. Moreover, this problem could lower the accuracy of cancer detection systems. Various machines and deep learning techniques have been researched to solve this problem. This paper implemented a deep learning method named Convolutional Recurrent Neural Network (CRNN) to build the Lung Cancer detection system. Convolutional neural networks (CNN) are used to extract features, and recurrent neural networks (RNN) are used to summarize the derived features. CNN and RNN methods are combined in CRNN to derive the advantages of each of the methods. Several previous research uses CRNN to build a Lung Cancer detection system using medical image biomarkers (MRI or CT scan). Thus, the researchers concluded that CRNN achieved higher accuracy than CNN and RNN independently. Moreover, CRNN was implemented in this research by using a microarray-based Lung Cancer dataset. Furthermore, different drop-out values are compared to determine the best drop-out value for the system. Thus, the result shows that CRNN gave a higher accuracy than CNN and RNN. The CRNN method achieved the highest accuracy of 91%, while the CNN and RNN methods achieved 83% and 71% accuracy, respectively.
An Overview Diversity Framework for Internet of Things (IoT) Forensic Investigation
Authors: Rizal Randi , Selamat Siti Rahayu , Masâ€™ud Mohd. Zaki
Published: July 2023

The increasing utilization of IoT technology in various fields creates opportunities and risks for investigating all cybercrimes. At the same time, many research studies have concentrated on security and forensic investigations to collect digital evidence on IoT devices. However, until now, the IoT platform has not fully evolved to adjust the tools, methods, and procedures of IoT forensic investigations. The main reasons for investigators are the characteristics and infrastructure of IoT devices. For example, device number variations, heterogeneity, distribution of protocols used, data duplication, complexity, limited memory, etc. As a result, resulting is a tough challenge to identify, collect, examine, analyze, and present potential IoT digital evidence for forensic investigative processes effectively and efficiently. Indeed, there is not fully used and adapted international standard for the perfect IoT forensic investigation framework. In the research method, a literature review has been carried out by producing previous research studies that have contributed to further facing challenges. To keep the quality of the literature review, research questions (RQ) were conducted for all studies related to the IoT forensic investigation framework between 2015-2022. This research results highlight and provides a comprehensive overview of the twenty current IoT forensic investigation framework that has been proposed. Then, a summary or contribution is presented focusing on the latest research, grouping the forensic phases, and evaluating essential frameworks in the IoT forensic investigation process to obtain digital evidence. Finally, open research issues are presented for further research in developing IoT forensic investigative framework.
Face Recognition Using Convolution Neural Network Method with Discrete Cosine Transform Image for Login System
Authors: Setiawan Ari , Sigit Riyanto , Rokhana Rika
Published: July 2023

These days, the application of image processing in computer vision is becoming more crucial. Some situations necessitate a solution based on computer vision and growing deep learning. One method continuously developed in deep learning is the Convolutional Neural Network, with MobileNet, EfficientNet, VGG16, and others being widely used architectures. Using the CNN architecture, the dataset consists primarily of images; the more datasets there are, the more image storage space will be required. Compression via the discrete cosine transform technique is a method to address this issue. We implement the DCT compression method in the present research to get around the system's limited storage space. Using DCT, we also compare compressed and uncompressed images. All users who had been trained with each test 5 times for a total of 150 tests were given the test. Based on testing findings, the size reduction rate for compressed and uncompressed images is measured at 25%. The case study presented is face recognition, and the training results indicate that the accuracy of compressed images using the DCT approach ranges from 91.33% to 100%. Still, the accuracy of uncompressed facial images ranges from 98.17% to 100%. In addition, the accuracy of the proposed CNN architecture has increased to 87.43%, while the accuracy of MobileNet has increased by 16.75%. The accuracy of EfficientNetB1 with noisy-student weights is measured at 74.91%, and the accuracy of EfficientNetB1 with imageNet weights can reach 100%. Facial biometric authentication using a deep learning algorithm and DCT-compressed images was successfully accomplished with an accuracy value of 95.33% and an error value of 4.67%.
The Gamification of E-learning Environments for Learning Programming
Authors: Garcia Villegas Christian , Lemos Aguero Nilson Augusto
Published: July 2023

Gamification is the most active methodology utilized in the E-learning environment for teaching-learning in computing; however, this does not restrict its use in other areas of knowledge. Gamification combines elements of play and its design techniques in a non-ludic context, achieving a motivation factor for the students. This systematic study aimed to collect and synthesize scientific evidence from the gamification field for learning programming through the E-learning environment. In order to do this, a systematic literature review was done, following the guidelines proposed by Petersen, which propose the definition of questions, search strategies, inclusion/exclusion criteria, and characterization. As a result of this process, eighty-one works were completely reviewed, analyzed, and categorized. The results revealed favorable learning among the students, the most used platforms and gamification elements, the most used languages and focuses of programming, and the education level, where gamification is most used to learn to program in an E-learning environment. These findings evidenced that gamification is a good active strategy for introducing beginning students to programming through an E-learning environment. Within this context, Learning programming through the use of gamification is a topic that is growing and taking force, and after what occurred during the pandemic, it is projected that there will continue to be more students who are focused on understanding its implementation and the impact it has on the different levels of education and the areas of knowledge.
Multipath Routing Implementation in SD-IoT Network Using OpenFlow-based Routing Metrics
Authors: Atthariq Muhammad Daffa , Hidayat Rizky Fauzi Ari , Sadida Medina Kaulan , Syafa'ah Lailis , Sumadi Fauzi Dwi Setiawan
Published: July 2023

The implementation growth of the Internet of Things (IoT) may increase the complexity of the data transmission process between smart devices. The route generation process between available nodes on the network will burden the intermediary node. One of the possible solutions for resolving the problem is the integration of Software Defined Networks and IoT (SD-IoT) to provide network automation and management. The separation of networking control and data forwarding functions may provide a multipath delivery path between each node in the IoT environment. In addition, the controller can directly extract the resource usage of the intermediary devices, which can be utilized as the routing metric variable in order to maintain the resource utilization on the intermediary devices. Instead of using traditional routing, this paper aims to develop multipath routing based on Deep First Search (DFS) and Dijkstra algorithms for acquiring an efficient path using OpenFlow-based routing metrics. The traffic monitoring module delivered the metrics extraction process, which obtained the variables using Port and Aggregate Flow Statistic features. The metrics calculation aimed to provide the multipath, which was constructed based on switches resource usage. Each selected path was chosen based on the smallest cost and probability provided by the group table feature in OpenFlow. The results showed that the Dijkstra algorithm could create the multipath more swiftly than DFS with a time difference of 0.6 s. The Quality of Service (QoS) results also indicated that the proposed routing metric variables could maintain the transmission process efficiently.
Industry 4.0: The New Quality Management Paradigm in Era of Industrial Internet of Things
Authors: DurakoviÄ‡ Benjamin , Halilovic Maida
Published: July 2023

Advanced technologies such as Big Data, the Internet of Things, artificial intelligence, robotics, cloud computing, and additive manufacturing are enablers of the industry 4.0 revolution and signify intense transformations in socio-economic systems. This work investigates the enabling nature of certain technologies in the emergence and development of different quality paradigms. Each enabling technology is related to a certain industrial revolution; consequently, a certain quality paradigm has been developed. Where is quality management now, in which direction its development is going, and what can be expected in the future is discussed in this paper. The research focuses on the most important factors discussed in the literature that influenced quality development throughout history. Results are presented in written and graphical form and include newly established theories based on recent innovations. Since this is a cumulative overview of different quality methods, it only briefly discusses the most important theories. It was observed that with Industry 4.0 enabling technologies, we are currently experiencing a transformation in this discipline, reaching a higher level in the competition for market positioning. Particularly, meeting explicit customer needs is upgraded with latent customer needs - linked to the customer's emotional responses (delight) to products/services. This paper contributes to a new field of research that is becoming increasingly popular.
Mining Opinions on a Prominent Health Insurance Provider from Social Media Microblog: Affective Model and Contextual Analysis Approach
Authors: Rasyada Ihda , Barakbah Ali Ridho , Amalo Elizabeth Anggraeni
Published: July 2023

Social media plays a significant role in enhancing communication among organizations, communities, and individuals. Besides being a mode of communication, the data generated from these interactions can also be leveraged to assess the performance of an institution or organization. People may evaluate public companies based on the opinions of their users. However, user-supplied information is brief and written in natural language. In addition to being brief, the process of sending messages or engaging in other social media interactions contains a great deal of context information. This multiplicity of context can be utilized to conduct a more in-depth analysis of user opinion. This study presents a new approach to opinion mining for social media microblogging data by applying an affective model and contextual analyses. The affective model is applied for sentiment analysis to measure the degree of each adjective from user opinion by evaluating adjectives according to their varying levels of pleasure and arousal. The contextual analysis in this paper is modeled based on topic, user, adjective, and personal characteristics. The contextual analysis has four main features: (1) Temporal keyword sentiment context, (2) Temporal user sentiment context, (3) User impression context, and (4) Temporal user character context. Our affective model outperformed 75.6% the accuracy and 74.98% of F1-score, rather than SVM. In the experiment, the contextual analysis performed graph visualization of output results for each query feature for future development. Feature one to four successfully processes the query to produce a visualization graph.
Early Detection of Asymptomatic Covid-19 Infection with Artificial Neural Network Model Through Voice Recording of Forced Cough
Authors: Nisa Aisyah Khairun , Wijaya I Gede Pasek Suta , Aranta Arik
Published: July 2023

SARS-CoV-2 is a virus that spreads the infection known as COVID-19, or Coronavirus 2019. According to data from the World Health Organization as of March 15, 2021, Indonesia has 1,419,455 cumulative cases and 38,426 cumulative deaths, ranking third among countries in terms of fatalities, behind Iran and India. Because COVID-19 was disseminated through direct contact with respiratory droplets from an infected individual, it spread swiftly and widely. According to the American Centers for Disease Control and Prevention, more than 50% of transmission rates are anticipated from asymptomatic individuals. The antigen tests have an accuracy of results ranging from 80â€“90% and are utilized for early detection of COVID-19. The cost of the antigen test is set to increase as of September 3, 2021, with prices ranging from IDR 99.000 to IDR 109.000; however, researchers are steadfastly searching for the best alternate methods for the early diagnosis of COVID-19. According to MIT News Office, a forced cough recording can identify an asymptomatic COVID-19 infection. Through the vocal recording of a forced cough, this study uses an artificial neural network (ANN) deep learning model to identify asymptomatic COVID-19 patients. The Artificial Neural Network (ANN) can distinguish asymptomatic people from forced cough recordings with an accuracy of up to 98% and a loss value of less than 3% by employing oversampling data. This model can be applied as a free, universal method for the early identification of COVID-19 infection.
Managing Information Technology Risks to Achieve Business Goals: A Case of Pharmaceutical Company
Authors: Ramadani Luthfi , Izzati Berlian Maulidya , Tarigan Yosephine Mayagita , Rosanicha Rosanicha
Published: July 2023

Extant literature has shown that sectoral characteristics play a critical role in business value creation through information technology (IT). Therefore, managing IT and its associated risks needs to consider specific industrial traits to understand the distinct business nature and regulations that shape IT-enabled business value creation. This study presents an in-depth analysis of business goals, IT processes, and IT risks in the case of a pharmaceutical company through which appropriate controls are designed to ensure business value creation through IT. Drawing on a case study of a pharmaceutical company in Indonesia, we found that managing IT risks in the pharmaceutical industry entails two main objectives: 1) ensuring compliance with external laws and regulations as well as internal policies, 2) supporting the optimization of business functions, processes, and costs. Throughout one year of engagement during the project, this study identified ten risks associated with the operation of business processes. Risks are dominated by moderate levels given the current state of controls and appetite, most of which emerge from the companyâ€™s existing internal processes. Internal actors are involved in all risks, with most events occurring due to laws and regulations. Further, the study designs and elaborates IT risk controls by drawing from COBIT 5 Seven Enablers. Overall, IT risk management through cascading processes of analysis ensures the alignment of IT risk controls with achieving business goals in the pharmaceutical industry.
An Artificial Neural Networks (ANN) Approach for 3 Degrees of Freedom Motion Controlling
Authors: Cong My Truong , Dang Khanh Le , Minh Thao Pham
Published: July 2023

Maritime simulation systems provide opportunities to acquire technical, procedural, and operational skills without the risks and expenses associated with on-the-job training. Maritime simulation systems are tools used to simulate real-world scenarios for training and research purposes, in which they are used to train seafarers in a safe and controlled environment. These systems are used to simulate different scenarios, such as navigation, maneuvering, and ship handling. The simulation systems allow users to learn and practice different scenarios without exposing themselves to real-life risks. However, at the moment, Vietnam's maritime simulators are dependent on other nations, which results in a lack of technological autonomy, a lengthy transfer of technology, high expenses, and a reduction in national security. Therefore, there is a lot of interest in developing a domestic maritime simulation system. With a rotation angle of Î± = [Î±1 Î±2 Î±3]T from the PLC controlling the DC/Servo system, the motion platform of the marine simulation system is built on the Stewart platform design principle. Due to the use of conventional control methods, this system suffers from a time delay of up to 1200ms, which prevents it from reacting to real-time control. In this paper, we investigate a novel technique for controlling the dynamic model with three degrees of freedom (3 DOF) of a cockpit cabin deck using artificial neural networks. The findings demonstrate that the reaction to real-time control, rotation error, and drive/servo system movement are all greatly improved.
Vehicles Speed Estimation Model from Video Streams for Automatic Traffic Flow Analysis Systems
Authors: Arriffin Maizatul Najihah , Mostafa Salama A. , Khattak Umar Farooq , Jaber Mustafa Musa , Baharum Zirawani , Defni - , Gusman Taufik
Published: July 2023

Image and video processing have been widely used to provide traffic parameters, which will be used to improve certain areas of traffic operations. This research aims to develop a model for estimating vehicle speed from video streams to support traffic flow analysis (TFA) systems. Subsequently, this paper proposes a vehicle speed estimation model with three main stages of achieving speed estimation: (1) pre-processing, (2) segmentation, and (3) speed detection. The model uses a bilateral filter in the pre-processing strategy to provide free-shadow image quality and sharpen the image. Gaussian filter and active contour are used to detect and track objects of interest in the image. The Pinhole model is used to assess the real distance of the item within the image sequence for speed estimation. Kalman filter and optical flow are used to flatten vehicle speed and acceleration uncertainties. This model is evaluated with a dataset that consists of video recordings of moving vehicles at traffic light junctions on the urban roadway. The average percentage for speed estimation error is 20.86%. The average percentage for accuracy obtained is 79.14%, and the overall average precision of 0.08.
Students Demography Clustering Based on The ICFL Program Using K-Means Algorithm
Authors: Andreswari Rachmadita , Fauzi Rokhman , Izzati Berlian Maulidya , Widartha Vandha Pradwiyasma , Pramesti Dita
Published: July 2023

Independent Campus, Freedom to Learn (ICFL) Program is one of the manifestations of student-centered learning. This program can help students reach their full potential by allowing them to pursue their passions and talents. This study aims to see how the segmentation of students participating in the ICFL program is based on demographic data. This research is based on survey responses from students participatingÂ in theÂ ICFLÂ program. The method used in this study is input data preparation, pre-processing, data cleansing, and data analysis. The information will be pre-processed before being utilized and evaluated. To help produce better outcomes in data clustering, the K-Means clustering approach is used, which is processed using the Python computer language. The data is clustered using the K-Means clustering approach based on gender characteristics, Grade Point Average (GPA), university entrance selection, ICFL category, and year or semester when participating in ICFL.Â This study resulted in three clusters with each of its criteria. The dominant gender is found in clusters 2 (100% female) and 3 (100% male). Software Development was the most popular ICFL category among students in cluster 1, accounting for 67%, while Design and Analysis Information Systems was the most popular in clusters 2 and 3. The most dominant ICFL program is found in three clusters. ICFL - Internship program in which at least 40% of participants come from each cluster. The research results are expected to assist stakeholders in evaluating the implementation of the ICFL program.Â Â
k-Means Cluster-based Random Undersampling and Meta-Learning Approach for Village Development Status Classification
Authors: Ilham Ahmad , Assaffat Luqman , Khikmah Laelatul , Safuan Safuan , Suprapedi Suprapedi
Published: July 2023

There is a significant imbalanced class in the village development index (called IDM - Indeks Desa Membangun) dataset, marked by the number of self-supporting classes more than the disadvantaged class. The traditional classifiers are able to achieve high accuracy (ACC) by training all cases of the majority class but forsaking the minority class, so that possible for the classification results to be biased. In this study, a random under-sampling technique was employed based on k-means cluster (KMC) and a meta-learning approach to improving ACC of the village status classification model. Furthermore, the AdaBoost and Random Forest were used as meta technique and base learner, respectively. The proposed model has been evaluated using the area under the curve (AUC), and experimental results showed that it yielded excellent performance compared to the prior studies with the AUC, ACC, precision (PR), recall (RC), and g-mean (Gm) values of 95.50%, 95.52%, 95.5%, 95.5%, and 92.95%, respectively. Similarly, the result of the t-test also showed the proposed model yielded excellent performance compared to previous studies. It can be concluded that the AdaBoost algorithm improved misclassification and changed the distribution of data loss function in random forests. It indicates that the proposed model effectively deals with imbalanced classes in the village development status classification model.Â
SELF-EFFICACY KARIR DAN DUKUNGAN KELUARGA DENGAN ADAPTABILITAS KARIR SISWA SMA
Authors: Tarina Rahmaningtiyas  , Wiwik Sulistiani  , Dewi Mahastuti
Published: July 2023

The current study examined the relationship between career self-efficacy and family support with with career adaptability indepedenly among students of SMAN 1 Pandaan. The number of respondents was 206 students of twelve grade SMAN 1 Pandaan, recruited through nonprobability sampling. The measuring instrument were CAAS (Career Adapt Adaptability Scale), Career Decision Making Self-Efficacy Scale (Indonesia Version) and family support scale from House & Khan. Data were analyzed using multiple correlation techniques. The results of the study show that there is a relationship between career self-efficacy and career adaptability of class XII students of SMAN 1 Pandaan, the direction of the relationship is positive. Other results show that there is no relationship between family support and career adaptability for class XII students of SMAN 1 Pandaan.
La sostenibilità come valore aggiunto aziendale
Authors: Prisco Chiara
Published: July 2023

Il presente capitolo ha lo scopo di inquadrare il contesto storico e geologico in cui le imprese operano attualmente, per arrivare a delineare due particolari definizioni di sostenibilità. Sarà spiegato perché la finanza è il punto di partenza per la transizione sostenibile e per la creazione di un ecosistema improntato sulla sostenibilità. Infine, sarà brevemente descritto il caso di Banca Etica, come prova del fatto che, ponendo la sostenibilità e non il profitto al primo posto, è possibile generare valore e che quest’ultimo è addirittura superiore rispetto a quello delle imprese tradizionali.
Startup, scaleup e unicorni
Authors: Pontoni Gianluca
Published: July 2023

Infinityhub è una startup innovativa in forte espansione e con grandi prospettive future. Tuttavia, per comprendere al meglio il suo percorso, i suoi pregi, i valori e le immense prospettive di crescita che la attendono, è necessario spiegare cos’è una startup. Verranno spiegate le fasi che, solitamente, sono necessarie per farla crescere, il suo naturale ciclo di vita e come, attraverso l’innovazione, apporti valore per il cliente e per la società. Il massimo traguardo per tutte le startup è quello di diventare un unicorno, ossia un’azienda che ha raggiunto un miliardo di dollari di valutazione.
Crossing the Border A Comparative Study of the Forest in the Poems of Gennadij Ajgi and in the Actions ofKollektivnye Dejstvija
Authors: Sala Roberta
Published: July 2023

In my article, I provide a comparative analysis of the forest in the production of the Russian poet Gennadij Ajgi (1934-2006) and in the performances of the artistic groupKollektivnye DejstvijaКоллективные Действия  (Collective Actions, 1976-89). Relying on the principles of environmental ethics, I stress the creative value of marginality, related to both the neutral space of the forest in Soviet ideologized society and the selected authors’ exclusion from the official culture. Besides, I focus on the deep transformation of the lyrical subject who, by crossing the forest border, establishes a creative dialogic exchange with nature.
Rendimiento deficiente en las matemáticas: un estudio en la Universidad Autónoma de Guerrero
Authors: Zaratoga Martínez Jesús , Memije Alarcón Norma Yadira , Ventura Ramos Perla Elizabeth
Published: July 2023

Se presenta un estudio descriptivo y trasversal con el objetivo de conocer la relación entre reprobación de las matemáticas, proceso de enseñanza aprendizaje y relaciones sociales entre estudiantes de la Escuela Superior de Ciencias Económicas de la Universidad Autónoma de Guerrero, México. Los datos que generaron la información se adquirieron por medio de la aplicación de un cuestionario. Se demuestra que para desarrollar un nivel matemático adecuado existen factores relacionados con el proceso de enseñar y aprender y con las múltiples relaciones sociales que existen de manera concomitante en este proceso y que involucran a estudiantado, profesorado e instituciones educativas.
Ficha Técnica/ Publication Data
Authors: Sadio-Ramos Fernando José , Ortiz-Molina María Angustias
Published: July 2023

Contém todos os dados legais da revista, assim como toda a Equipa de Trabalho e os "sites" em que está alojada / indexada

It contains all the legal data of the Journal, as well as all the Work Team and the "sites" in which it is housed / indexed