bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transformasi Literasi Sains melalui Video Pembelajaran IPA Berbantuan Aplikasi Doratoon
Authors: Sihombing Jesika Merdisinta , Ananda Lala Jelita , Perangin-Angin Laurensia Masri , Usman Khairul , Nasution Yusra 
Published: June 2024

Penelitian ini bertujuan untuk mengetahui kelayakan, kepraktisan dan keefektifan video pembelajaran IPA menggunakan aplikasi Doratoon berbasis literasi sains. Jenis penelitian ini menggunakan penelitian pengembangan atau research and development (R&D) dengan model ADDIE yang terdiri dari 5 tahapan yaitu tahap analisis, perancangan, pengembangan, implementasi, dan evaluasi. Subjek pada penelitian ini adalah peserta didik berjumlah 29 orang dan 1 orang guru kelas V SDN 173175 Simarpinggan. Teknik pengumpulan data menggunakan teknik wawancara, dokumentasi, angket, dan tes. Hasil validasi oleh ahli materi dan ahli media adalah “Sangat Layak”. Uji kepraktisan oleh praktisi pendidikan menyatakan bahwa video pembelajaran “Sangat Praktis” dan hasil respon peserta didik diperoleh pada uji coba perorangan dan uji coba kelompok kecil menunjukkan bahwa video pembelajaran “Sangat Praktis”. Berdasarkan hasil uji keefektifan diketahui bahwa setelah menggunakan video pembelajaran yang dikembangkan terlihat peningkatan hasil belajar masing-masing peserta didik. Dilihat dari rata-rata nilai peserta didik berada pada kategori ‘Tuntas’ dan “Efektif” setelah menggunakan video pembelajaran. Dari penelitian dan data yang ditemukan dapat disimpulkan bahwa video pembelajaran IPA menggunakan aplikasi Doratoon berbasis literasi sains layak untuk digunakan dalam pembelajaran.
Karakterisasi Fisikokimia dan Organoleptik Tablet Effervescent Ashitaba (Angelica keiskei)
Authors: Laitupa Fajriyanti Azzura , Dewi Ardhia Deasy Rosita , Erawati Christina Mumpuni , Kusumawardhany Prita Ayu , Widjaja Lanny Kusuma , Iswadi Hazrul 
Published: June 2024

Ashitaba (Angelica keiskei) merupakan tanaman yang mengandung senyawa flavonoid (kalkon) dan tanin yang dapat berperan sebagai antioksidan. Kandungan antioksidan pada ashitaba akan mudah dikonsumsi dalam bentuk sediaan tablet effervescent. Penelitian ini bertujuan untuk mengetahui formula terbaik tablet effervescent ashitaba. Tablet effervescent merupakan bentuk sediaan yang menghasilkan gelembung gas karbondioksida sebagai hasil dari reaksi kimia dalam larutan yang mengandung senyawa asam dan senyawa karbonat atau bikarbonat hingga terdapat rasa sparkly pada minuman setelah tablet larut sempurna dalam air. Proses pembuatan diawali dengan ekstraksi senyawa flavonoid dengan metode maserasi dalam pelarut etanol 70%, lalu dikeringkan menggunakan spray dryer dengan maltodekstrin sebagai drying aid. Tablet effervescent dibuat berdasarkan formula yang telah ditentukan menggunakan penambahan ekstrak sebesar 10; 15; 20; 25% (b/v). Berdasarkan hasil analisis statistik karakteristik fisikokimia yang telah dilakukan, ditemukan adanya perbedaan signifikan. Perlakuan dengan penambahan ekstrak 15% merupakan perlakuan terbaik menurut uji indeks efektivitas dengan aktivitas antioksidan sebesar 29,43±1,84%, kadar air 3,68±0,28%, waktu larut 40±0,99 detik dan warna tablet kuning merah.

Ashitaba (Angelica keiskei) is a plant that contains flavonoid compounds (chalcone) and tannins which can act as antioxidants. The antioxidant content in ashitaba can be easily consumed in the form of effervescent tablets. This research aims to determine the best formula for ashitaba effervescent tablets. Effervescent tablets are a dosage form that produces carbon dioxide gas bubbles as a result of a chemical reaction in a solution containing acid compounds and carbonate or bicarbonate compounds so that there is a sparkly taste in the drink after the tablet dissolves completely in water. The manufacturing process begins with the extraction of flavonoid compounds using the maceration method in 70% ethanol solvent, then dried using a spray dryer with maltodextrin as a drying aid. Effervescent tablets are made based on a predetermined formula using an extract addition of 10; 15; 20; 25% (w/v). Sample treatment with the addition off 15% extract was the best treatment according to the effectiveness index test with antioxidant activity of 29.43 ± 1.84%, water content of 3.68 ± 0.28%, dissolving time of 40 ± 0.99 seconds and colour of the tablet was yellow red.
Profil Resistensi Isolat Klebsiella pneumoniae, Haemophilus sp. dan Streptococcus viridans dari Sputum Pasien ISPA terhadap Amoksisilin
Authors: Raharjo Dian Natasya , Islamie Ridho , Wahjudi Mariana , Apriyani Dhea Orinta , Wartini Luh Risma , Dewi Ni Putu Nila Sulistia 
Published: June 2024

Infeksi Saluran Pernapasan Akut (ISPA) merupakan radang akut yang disebabkan oleh infeksi mikroorganisme dengan angka kejadian cukup tinggi di Indonesia. Sebanyak total 49 bakteri yang terdiri dari 13 isolat Klebsiella pneumoniae, 18 isolat Haemophilus sp., dan 18 isolat Streptococcus viridans koleksi laboratorium setempat diperoleh dari sputum pasien ISPA di berbagai puskesmas di Kota Surabaya selama bulan Desember 2022. Penelitian ini bertujuan untuk mengetahui resistensi dari 49 koleksi isolat tersebut terhadap amoksisilin. Pengujian dilakukan untuk memperoleh MIC (Minimum Inhibitory Concentration) amoksisilin menggunakan metode agar dilution pada media Mueller Hinton Agar. Nilai MIC kemudian dibandingkan dengan MIC breakpoints pada Clinical and Laboratory Standards Institute (CLSI) dan European Committee on Antibiotic Susceptibility Testing (EUCAST). Hasil penelitian menunjukkan 61,54% (8/13) isolat Klebsiella pneumoniae, 100% (18/18) isolat Haemophilus sp., dan 11,11% (2/18) isolat Streptococcus viridans resisten terhadap amoksisilin. Oleh karena itu dapat disimpulkan perlunya rekomendasi antibiotik alternatif sebagai pengganti amoksisilin untuk pengobatan ISPA.

Acute Respiratory Infection (ARI) is an acute inflammation caused by microorganism infection with a high incidence in Indonesia. The local microbiology laboratory had successfully collected 49 bacterial isolates from the ARI patient's sputum in various Public Health Centers in Surabaya, Indonesia during December 2022. The isolates consisted of 13 isolates of Klebsiella pneumoniae, 18 isolates of Haemophilus sp., and 18 isolates of Streptococcus viridans. This study aimed to determine the resistance of the 49 isolates to amoxicillin. Testing was carried out to obtain the MIC (Minimum Inhibitory Concentration) of amoxicillin using the agar dilution method on Mueller Hinton Agar media. The MIC value was then compared with the MIC breakpoints at the Clinical and Laboratory Standards Institute (CLSI) and the European Committee on Antibiotic Susceptibility Testing (EUCAST). The results showed that 61.54% (8/13) of Klebsiella pneumoniae isolates, 100% (18/18) of Haemophilus sp. isolates, and 11.11% (2/18) of Streptococcus viridans isolates were resistant to amoxicillin. Therefore, it can be concluded that it is necessary to recommend alternative antibiotics as a substitute for amoxicillin for the treatment of ARI.
“When the immigrants faced the Statue of Liberty”: Critical Discourse Analysis of National Narratives in Greek Parliament
Authors: Panagaki Nikoletta , Tsami Vasia , Tzortzatou Kyriakoula 
Published: June 2024

Abstract
The increased arrival of immigrant/refugee populations often leads to public debates. These debates about immigrant/refugee policies are often raised in parliament. Inside parliament, speakers use specific arguments to persuade their audience, aiming to construct specific national identities, and to promote the national homogenizing discourse. To accomplish this, the politicians often exploit narratives and more specifically, national narratives, reframing aspects of history in order to shape the national conscience. The aim of this research is to analyze how two political leaders of opposite Greek parties, Kyriakos Mitsotakis and Yanis Varoufakis, use narratives on the Greek immigration/refugee movement to the USA in the 1920s to argue about the contemporary Greek policy toward immigrant/refugee issues. To analyze their narratives, we utilize the model of positioning suggested by Bamberg (1997), drawing a distinction between three levels: the narrative world, where we focus on how the characters are positioned in relation to one another within the reported events; the narrative interaction, where we examine how the narrator positions him/herself in relation to the audience through specific argumentative strategies (Reisigl and Wodak 2001); and the broader socio-ideological framework, which concerns the positioning of the narrator toward the Discourses, namely, toward the ideologically defined ways of representing reality. According to our findings, at the level of the narrative world the two politicians construct differently the USA immigrant/refugee policy. These constructions result to different arguments at the level of the narrative interaction, where Mitsotakis promotes as a norm the exclusion of the Others, while Varoufakis promotes their assimilation. Given that both the exclusion and the assimilation of the Others comprise homogenizing practices, we realize that, at the level of the broader socio-ideological framework, both political leaders, each from a different perspective, reinforce the national discourse.
Technological Strategies for Reducting Food Waste
Authors: Neagoe Iulia Elena , Grădinaru Giani 
Published: July 2024

Abstract
In recent years, the concepts of circular economy and sustainable lifestyle have taken concrete form. The United Nations has outlined a set of targets, called Sustainable Development Goals (SDGs), through which the level of development of society can be more easily analysed. By following the 17 development directions, lifestyles can be improved, with an appropriate relationship with the rest of society. The current situation of food waste is reflected in at least five of the SDGs, to eradicate hunger, to improve climate actions by minimizing greenhouse gas emissions, to facilitate safe drinking water, for the conservation and sustainable use of oceans, seas, and marine resources, for restoring, and promoting sustainable use of terrestrial ecosystems and for responsible consumption on households and corporate level. The paper aims to highlight, incorrect practices and conventional and technologically innovative solutions to minimize food waste as much as possible, as these activities can reduce the carbon footprint and support existing models of a sustainable green economy. The results will highlight the critical intersection of circular economy principles, sustainable living, and the United Nations' Sustainable Development Goals (SDGs) in the context of food waste. By examining current practices and proposing both conventional and technologically innovative solutions, the study underscores actionable measures.
Are Firms from European Union Financially-Stressed Countries More Credit Constrained?
Authors: Dumitru Ionuţ , Dumitru Ionela 
Published: July 2024

Abstract
Using a large microdata database from the European Commission and European Central Bank survey (Survey on Access to Finance of Enterprises), we investigate in this paper what factors are playing a significant role in explaining why companies from European Union are credit constrained, and if the firms from financially stressed countries are more credit constrained. We found that smaller companies are more likely to be more credit constrained than larger companies in all our estimated models. The impact of the age of the firm on credit access is found to be mixed. A positive performance in terms of profitability seems to come hand in hand with a lower likelihood of being credit constraints. A deterioration of the outlook of the firm in terms of sales and profitability or business plan there will trigger a higher likelihood of being credit constrained, the impact being stronger for stressed economies. Not in the last, the access to public financial support, including guarantees, has a “grease” effect on access to bank loans, reducing the probability of being credit constrained, the positive impact being stronger in stressed countries.
Labor Market Challenges from an European Union with Diversified Human Resources
Authors: Petre Patricia Petronela , Trasca Daniela Livia 
Published: July 2024

Abstract
The European continent is going through a period when uncertainty is the key word: a war on its eastern borders, increasing flows of migrants, a labor market in transition to a green economy, technological trend threatening the viability of human resources and, economic difficulties. In this scenario, the labor market must accommodate an increasing number of immigrants with non-European origin, on a job market where qualification requirements are not covered by human resources that must prove their relevance in competition with the artificial intelligence and automation in more and more areas of economy. In order to determine the level of integration of immigrants, the most relevant indicator was and remains their employment rate. This paper aims to make an analysis of the European labor market, subject of these pressures, through a comparative analysis between native-born human resources and that of non-European origin. The time frame covers the period 2014-2022. The system of analyzed indicators includes: the employment rate, the job retention rate, the schooling level, the types of targeted jobs and the qualification for them. We expect to identify an increasing level of employment among non-EU immigrants, as well as a widening gap between labor market requirements and labor supply.
Artificial Intelligence Text Processing Using Retrieval-Augmented Generation: Applications in Business and Education Fields
Authors: Posedaru Bogdan-Stefan , Pantelimon Florin-Valeriu , Dulgheru Mihai-Nicolae , Georgescu Tiberiu-Marian 
Published: July 2024

Abstract
The article studies the current text processing tools based on Artificial Intelligence. A literature review is done emphasizing the dynamic evolution of AI-powered text analytics, having as its central tool ChatGPT and its capabilities. The focus is centered on the techniques and methods that are using embeddings in order to improve large language models (LLMs).
In this paper is analyzed the current situation of the literature in terms of text processing using Retrieval-Augmented Generation and is highlighted the potential of this technology to enhance the interpretability and trust in applications critical, such as those related to education or business. AI has revolutionized natural language processing (NLP), which facilitated the machines to interpret and generate text efficiently and accurately. In addition, large language models with external knowledge bases have been developed. These are used to produce more accurate and contextually relevant text responses. This approach is called Retrieval-Augmented Generation (RAG is one of the most significant recent advancements in this field.
Based on our study, two use cases are implemented to show the applicability of our study: one related to education and one related to business IT-related documents. The methodology describes the techniques used. This includes retrieval-augmented generation and embedding stored using vector databases. Our custom models are evaluated by comparing them to the general ones, without embeddings, showing superior performance.
The article highlights remarkable progress in Retrieval-Augmented Generation (RAG), which is used for AI text processing with a focus on business and education fields. Further in this paper, many of the most significant highlights are presented, which include a scalable framework for AI applications, a new integration of Retrieval-Augmented Generation and embeddings, practical application demonstrations, bridging gaps in the analysis op AI text, significant development in AI performance and optimizing educational and business processes.
A Quantitative Analysis of Default Risk Using Machine Learning and SHAP Value Interpretation
Authors: Tanasuica Zotic Coralia 
Published: July 2024

Abstract
In finance, creating a model that balances risk reduction with opportunity is essential. This investigation addresses the necessity for risk evaluation frameworks that combine efficiency with adaptability, thus preserving opportunities for transactions critical to some organizations. The present study identifies, within a factoring process involving two key players: the invoice seller and the debtor, the essential variables that determine the likelihood of the debtor defaulting on the invoice payment. The event of non-payment is most often associated with the debtor's inability to pay due to insolvency, making it crucial in this type of activity to emphasize an efficient credit scoring system capable of proactively highlighting a debtor company with a high risk of default. Nonetheless, some companies pass this filter and enter the factoring process, but end up being unable to pay. The study identifies them based on a set of real data and uses supervised machine learning techniques to select the optimal classification model, also highlighting the variables with a major impact on the target. The specialized literature is focused on identifying the models that perform best in the credit scoring activity or studies that identify the non-payment behavior of clients. What this work adds is the combination of these two dimensions, for example, it provides an additional filter to credit scoring, using parameters identified as essential in determining defaulters and using them as inputs for an unsupervised learning model, thus classifying the entire population of companies in Romania to identify clusters containing the highest proportion of non-payment companies.
The Applicability of Some Machine Learning Algorithms in the Prediction of Type 2 Diabetes
Authors: Vîrgolici Oana , Tănăsescu Laura Gabriela 
Published: July 2024

Abstract
Type 2 diabetes is a metabolic disease that causes abnormal high levels of glucose in the blood. The pancreas is healthy, but the body doesn’t respond properly to its own insulin. The principal culprit is obesity, too much high fat tissue. So, measuring the body mass index or the waist circumference is a step to estimate the risk for this disease. Many people have no symptoms and the disease develops silently, causing serious problems with eyes, feet, heart and nerves. The prediction of diabetes is a very topical problem. In addition to medical guides, more and more machine learning models appear, trained on different databases. The purpose of these models is to predict diabetes, based on different parameters, not all of them coming from medical analyses. In the paper we present four diabetes prediction models, respectively based on the decision tree, support vector machine, logistic regression and k-nearest neighbors’ algorithms. All models are trained and tested on a database with approximately 65,000 records (divided into 70% for training and 30% for testing), which contains two blood markers (haemoglobin A1c and glucose), an anthropometric parameter (body mass index), age, gender and three categorical parameters (smoking status, hypertension, heart disease). We identify that Haemoglobin A1C and glucose are the most influential predictors. The models are evaluated in terms of accuracy score and confusion matrix and a ranking is presented at the end. The results obtained are very encouraging for all the presented models.
The Role of AI for Business and Companies’ Leadership and Internationalization in Globalization: A Background with Analysis
Authors: Benabed Anis , Bujor Dragoș , Manita Bulareanu Alexandra , Constantin Ene Andreea Bianca 
Published: July 2024

Abstract
This paper analyzes and describes an analytical approach on the role of Artificial intelligence for business and companies leadership within the outlines of globalization. The research methodology focused first on a literature review by reviewing some previous relevant articles to the research topic and focusing on the relevant points. The reviewed articles provided in the part of references below were from different databases. The literature review was followed by a descriptive analysis that based on data interpretation and analysis according to the illustrations of the available data in the created figures that are showed in the part of analysis and results. The results showed that the potential of artificial intelligence may help companies to control their internal and external systems to bid and trade well in the markets. Artificial intelligence can help companies advance with their businesses by offering their services, products, operations or whatever offers in forms of e-sales with the help of artificial intelligence. Under the outlines of globalization and digitalization that are intertwined, competitiveness becomes increasingly stronger because companies business holders compete with companies that apply technology and innovation, delivering increasingly better products, operations, services and offers with the possibility of high costs for the third world countries and lower costs for developed countries and the Companies that internationalize their processes greatly need artificial intelligence, which has already become a leader in leading some businesses. In conclusion, many companies are clear that artificial intelligence is the next step in digital transformation for business and companies’ leadership since AI is needed for their services, offers and internationalization processes to compete strongly in the foreign markets.
Slowbalization: Rising Trends for the Global Economy and Business
Authors: Benabed Anis , Moncea Madalina 
Published: July 2024

Abstract
This paper investigates and analyzes the paradigm of slowbalization and the new direction of globalization and how they can expose business to more challenges. The research methodology mainly focused on literature review with a focus on a descriptive data analysis in the content of the paper. The results showed that factors such as economic decoupling that may transform to a real difficult reality for companies, the economic consequences of the geopolitical conflicts, the pandemic caused by Covid-19 divergence in US-China relations globally, political economic instability, rising inflation rates and other risks such as cyber-attacks have always posed a threat to economies, companies, businesses and markets. Slowbalization as a word does not exist in literature or language roots but it illustrates the recoil of globalization due to some of the previous stated factors. In conclusion, the end of globalization seems to be impossible since it appeared in the fourth industrial revolution that witnessed the appearance of digitalization, computer and internet. It is possible that a new phase of globalization is being reshaped or a new road towards its sustainable aspects. On the contrary, the introduction of a new international order is always a potential probability.