bluuebunny/crossref_metadata_2025 huggingface dataset:
Foreign Policy of Pakistan: A Case Study of Z.A. Bhutto’s Policies Post 1971 Tragedy
Authors: Farooq Rimsha
Published: November 2024

Zulfikar Ali Bhutto ascended to Power when Pakistan was bleeding after the horrors of the 1971 disaster. "Rotti, kapra, makaan” was also based on this concept. Zulfikar Ali Bhutto came into power to provide equality and to make Pakistan a democratic state, where every citizen is treated equally. Zulfikar Ali Bhutto had some great achievements during his regime which include the Shimla agreement, nuclear power, and the 1973 constitution. However, his trust in Zia-Ul-Haq was the major factor in his fall from power. This paper focuses on Bhutto as a ruler, his achievements, his reforms, and his fall from power.
Pakistan’s Foreign Policy Towards Indian Revocation of Kashmir's Special Status- Modi's Grand Strategy in Abrogating Articles 35A and 370 of the Indian Constitution
Authors: Jamil Zainab
Published: November 2024

Kashmir Valley has been a subject of discussion since 1947 because of political discord between Pakistan and India. Article 370 and 35(A) of the Indian Constitution were abrogated by Indian Prime Minister Narendra Modi giving Kashmir and its inhabitants certain benefits, just as Kashmir has its own constitution. This paper scouts Pakistan's modified foreign policy towards India in the after-effect of Articles 370 and 35(A) of the Indian Constitution being abrogated. Further, owing to the critical review of available literature, the paper will seek to present how it cast the relationship between Trump and Modi which benefited Modi in making such a smooth move in occupied Kashmir. This research concentrates on what are Modi's motives and strategies behind revoking the Indian Constitution Articles 370 and 35 (A) that motivate Modi to take these steps on Kashmir now.
Dioxins in Livestock Products: Sources, Bioaccumulation, and Health Impacts
Authors: Pralas Viktorija , Vnučec Ivan , Pleadin Jelka , Jůzl Miroslav , Bendelja Ljoljić Darija , Konieczka Paweł , Stamenić Tamara , Kos Ivica
Published: November 2024

Dioxins, a group of persistent organic pollutants, are highly toxic, resistant to degradation, and primarily enter the environment through industrial processes. They include polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (DL-PCBs). Dioxins accumulate in fatty tissues of animals and humans due to their lipophilic nature, posing significant health risks, including cancer, reproductive, and developmental issues. Contaminated food, particularly from livestock production like dairy and meat products as well as fish are the primary route of human exposure. Studies show that dioxin levels in livestock depend on factors such as feed contamination and exposure duration. Cattle, sheep, and goats which are exposed to contaminated soil during grazing are particularly vulnerable. Studies have found that dioxins concentrate in liver and fat, with higher sequestration in the liver. Due to their lipophilic nature, dioxins bind to fat tissue and bioaccumulate in the bodies of animals and humans, leading to prolonged exposure. Human exposure is primarily through the consumption of animal products, with dietary intake accounting for 90-95 % of dioxin exposure. Food processing, particularly high-temperature cooking and fat removal can reduce dioxin content, although some congeners may persist. Regulatory measures have significantly reduced industrial dioxin emissions, but environmental persistence and bioaccumulation remain challenges. The European Union has set strict limits on dioxin levels in food to protect public health, with ongoing research focused on reducing exposure through improved agricultural practices and food processing methods.
Glucocorticoid receptor expression in the different cell types of the neonatal rat hippocampus and cortex
Authors: Lanshakov D. А. , Drozd U. S. , Dygalo N. N.
Published: November 2024

Glucocorticoids (GC) are crucial regulator of organism homeostasis and function. Despite severe outcome glucocorticoid therapy in neonates is widely used antenataly for accelerating fetal lung maturation in cases of preterm birth. GC action mediated via glucocorticoid receptors – ligand activated transcription factors. Despite broad range of information concerning GR expression in the brain, not so much known about GR expression in the neonatal brain in aspects of cell specificity and identity. In this work we perform comparative study of GR expression together with panel of main neuronal and astrocytic cell markers in the neonatal rat brain. We immunohistochemically studied GR expression in the hippocampal CA1 field and enthorinal cortex together with cortical projection neuron markers – SATB2, NURR1; Calretenin – interneurons marker, and GFAP – astrocytic marker. The highest calocalization coefficients observed for GR with Calrtetenin. With projection neuron markers that are also transcription factors calocalization coefficients increased to the same values as for GR-Calretenin 6h after dexamethasone injection and GR were translocated to the nucleus. Our analysis showed that in the neonatal rat brain GR are more localized in neurons than in astocytes.
Formation of thin GaAs buffer layers on silicon for light-emitting devices
Authors: Lendyashova V. V. , Ilkiv I. V. , Borodin B. R. , Kirilenko D. A. , Dragunova A. S. , Shugabaev T. М. , Cirlin G. E.
Published: November 2024

This paper presents the experimental results on research of growth processes of GaAs layers on silicon substrates by molecular beam epitaxy. The formation of buffer Si layer in a single growth process has been found to significantly improve the crystalline quality of the GaAs layers formed on its surface, as well as to prevent the formation of anti-phase domains both on of fcutted towards the [110] direction and on singular Si(100) substrates. It has been demonstrated that the use of cyclic thermal annealing at temperatures 350–660°C in the flow of arsenic atoms makes it possible to reduce the number of threading dislocations and increase the smoothness of the GaAs layers surface. At the same time, the article considers possible mechanisms that lead to an improvement in the quality of the surface layers of GaAs. It is shown that the thus obtained GaAs layers of submicron thickness on the singular Si(100) substrates have a mean square value of surface roughness 1.9 nm. The principal possibility of using thin GaAs layers on silicon as templates for forming on them light-emitting semiconductor heterostructures with active area based on self-organizing InAs quantum dots and InGaAs quantum well is presented. They are shown to exhibit photoluminescence at 1.2 µm at room temperature.
СУЧАСНІ ТЕНДЕНЦІЇ РОЗВИТКУ ТУРИСТИЧНИХ ПІДПРИЄМСТВ В СФЕРІ СОЦІАЛЬНО-ЕТИЧНОЇ ВІДПОВІДАЛЬНОСТІ
Authors: БЕССОНОВА Анна , БЄЛОБОРОДОВА Марія , ЗАХАРОВА Світлана
Published: November 2024

У статті розглянуто складові соціально-етичної відповідальності закладів туристичної сфери та її значення для сталого розвитку країни. Досліджено економічну, екологічну та соціальну складові соціально-етичної відповідальності. Наведено ключові аспекти соціально-етичної відповідальності у контексті туристичної діяльності. Досліджено доходність закладів туристичної сфери як фактору створення та розвитку соціально-етичної відповідальності. Розглянуто взаємозв’язок соціально-етичної відповідальності закладів туристичної сфери з Цілями сталого розвитку в Україні. Доведено взаємозв’язок різних аспектів соціально-етичної відповідальності з конкретними Цілями сталого розвитку, досліджено економічний аспект соціально-етичної відповідальності туристичних закладів України. Наведено виклики розвитку соціально-етичної відповідальності на українських підприємствах. Розглянуто принципи безбар’єрності та інклюзивності як ключові складові соціально-етичної відповідальності закладів туристичної сфери.
ІННОВАЦІЙНІ ПІДХОДИ ДО СТРАТЕГІЧНОГО УПРАВЛІННЯ ТОРГОВИМИ ПІДПРИЄМСТВАМИ
Authors: КОРЕНЮК Денис
Published: November 2024

У статті досліджено інноваційні підходи до стратегічного управління торговими підприємствами. Розглянуто поняття інновація та інноваційна діяльність, конкретизована їх роль в управління торговим підприємством. Досліджено сутність стратегічного планування, як стратегічного інструменту управління торгового бізнесу, який використовується менеджерами для досягнення поставлених цілей та задач. Охарактеризовані найбільш відомі та актуальні інноваційні підходи до стратегічного управління такі, як: гейміфікація, гнучка робоча сила, е-тендери, концепція shop-in-shop тощо. Проаналізовано досвід використання наведених підходів у зарубіжних торгових компаніях, на основі, якого слід розвивати вітчизняні торгові підприємства. Також звертаємо увагу на важливу роль персоналу у роботі підприємства, оскільки він виступає основою для побудови успішного бізнесу. Підсумовано, що для подальшого розвитку торгових підприємств слід продовжувати дослідження інноваційних підходів до стратегічного управління, зважати на зарубіжний досвід і тестувати його для вітчизняних реалій.
From ethnic settlement agglomerations to housing complexes: A history of changing urban spaces in Makassar, Indonesia
Authors: Ahmadin
Published: November 2024

This article contributes to research on urban dynamics and residential spatial change. This research presents a case study of an Indonesian city located in South Sulawesi Province, Makassar, which was originally formed from an agglomeration of ethnic-based villages. Along with the growth and development of the city, these ethnic-based settlements were overhauled and replaced by profession-based housing complexes, subsidized housing complexes, and others. This research is a descriptive qualitative sociological research both in the type of data and analysis. The research approach is historical sociology with synchronic and diachronic thinking methods. This article explores the process of ethnic-based settlement reshuffling that begins with the emergence of a series of government policies in development and the pressure of global capitalism from economic actors of poverty that intervene in the process and direction of urban development. The financial impact and the social, economic and cultural implications are also examined. This phenomenon shows that urban modernization is a necessity for cities in the future and will certainly have far-reaching consequences for city residents.
Morphological characterization of sweat glands in three bovine racial groups under tropical conditions
Authors: Campos Romulo , Avila Héctor , Esquinas Paula , Manzano José Luis , Velez-Terranova Mauricio
Published: November 2024

The number, size, and distribution of sweat glands are involved in cattle adaptation and thermoregulation mechanisms. Similarly, variations among different racial groups during grazing merit a morphometric study. The present work aimed to compare sweat glands and hair follicles in three cattle breed groups under low trophic conditions. This study was conducted in a tropical inter-Andean valley located between 3'30 and 4'10 N and between 76'21 and 76'46 W, with three breed groups. They were Holstein (Bos taurus), Cebu (Bos indicus), and animals of the Harton del Valle breed, Colombian Creole cattle (Bos taurus). From each breed, seven animals were analyzed, and each individual had a skin biopsy taken from the cervical area, close to the scapular joint. For the histological assemblies, optical microscopy was used to analyze the thickness of the glandular epithelium, counting the number of sweat glands per square millimeter, sebaceous glands, and hair follicles. The statistical analysis included descriptive statistics and one-way analysis of variance to determine the effect of racial group. The analysis revealed that neither the thickness of the glandular epithelium nor the number of sweat glands varied among the three racial groups, whereas the number of sebaceous glands and the number of hair follicles significantly differed. Compared with zebu cattle, Creole Harton del Valle cattle presented a lower number of hair follicles, sweat glands and sebaceous glands.
Evaluating compliance and monitoring practices: A comprehensive review of auditing surgical safety checklists against regulatory standards and guidelines
Authors: Patne Shruti , Kanyal Deepika
Published: November 2024

Patient safety during surgical procedures is paramount in healthcare. Surgical safety checklists (SSCs) have become integral tools for enhancing safety practices and mitigating risks associated with surgeries. These checklists standardize processes, promote effective communication, and prevent errors that could jeopardize patient safety. The World Health Organization's (WHO) Surgical Safety Checklist, introduced in 2008, has significantly reduced complications and mortality rates globally. However, the effectiveness of SSCs relies on consistent and proper implementation, necessitating regular compliance audits and monitoring.Compliance audits are crucial for identifying non-compliance, evaluating protocol effectiveness, and identifying areas for improvement. Regular audits ensure SSCs are utilized effectively, enhancing patient outcomes and reducing adverse events. Studies demonstrate that proper SSC implementation leads to reduced surgical site infections, improved communication, and fewer postoperative complications. Compliance audits provide insights into practical implementation, identify barriers, and facilitate process refinements. They are also essential for continuous quality improvement and risk management, enabling healthcare organizations to proactively address risks and ensure adherence to best practices.This review examines the regulatory frameworks and industry standards governing SSCs, highlighting guidelines from authoritative bodies like the WHO and the Joint Commission. It explores audit methodologies, data collection techniques, and the interpretation of audit findings. Additionally, the review addresses barriers to conducting compliance audits and explores strategies and best practices for overcoming these challenges. The role of technology in facilitating audits through electronic checklists and data analytics is also discussed. By analyzing existing literature and best practices, this review aims to equip healthcare professionals and regulatory bodies with comprehensive knowledge to enhance patient safety and quality of care through effective compliance audits and monitoring of SSCs.
Mediating invasion conflict by the UN: Case of the invasion of Ukraine
Authors: Gunawan Yordan , Reza Yusuf Prasetyo
Published: November 2024

This paper critically assesses the role of the United Nations (UN) in mediating the war between Russia and Ukraine, focusing on the organization's problems and limits in sustaining international peace and security. The study is based on a detailed review of secondary sources, including UN papers, official reports, academic journals, and news items, using a normative legal research technique in conjunction with a qualitative descriptive approach. The main goal is to evaluate the roles and responsibilities of important UN entities, notably the Security Council and the Secretary-General, in their attempts to mediate the dispute in conformity with the UN Charter. The findings show that, despite various mediation efforts, such as those facilitated by the Organization for Security and Cooperation in Europe (OSCE) and recommendations by the United Nations General Assembly, the effectiveness of these efforts has been significantly hampered by the realpolitik of the Security Council's permanent members and the broader dynamics of global politics. These constraints have hindered the UN's ability to act aggressively in ending the crisis. To improve the mediation process, the research suggests including neutral foreign parties such as China, Turkey, India, and South Africa, who may bring a more balanced approach to negotiation. It also emphasizes the need of closer collaboration with regional and global organisations, as well as a larger role for UN agencies like as the UNHCR, WHO, and OCHA in supporting long-term peace initiatives. These stages are critical for ensuring that diplomatic efforts are supplemented by strong humanitarian and development activities, eventually leading to a long-term settlement of the conflict.
A brief review of practical use of artificial intelligence in surgery in the current era
Authors: Bobade Shubham , Asutkar Sheetal , Nagpure Devesh , Kadav Amar
Published: November 2024

Artificial Intelligence (AI) is increasingly transforming the field of surgery by enhancing precision, improving patient outcomes, and optimizing surgical workflows. This article explores the practical applications of AI in contemporary surgical practices, including advancements in AI-assisted diagnostic tools, robotic surgery, predictive analytics, and decision-support systems. AI technologies, such as deep learning models and convolutional neural networks, have demonstrated significant improvements in diagnostic accuracy, particularly in medical imaging, pathology, and disease classification. Robotic surgical systems, augmented by AI, offer enhanced precision, control, and dexterity, leading to reduced complications, minimal invasive procedures, and faster recovery times for patients. Predictive analytics powered by AI aids in surgical planning and risk management by forecasting potential complications, personalizing treatment plans, and optimizing surgical outcomes based on patient-specific data. Decision-support systems provide real-time assistance during surgeries, analyzing live data from various sources to offer actionable insights, recommendations, and alerts, thereby enhancing surgical safety and efficiency. Despite these advancements, challenges remain, including the need for diverse and high-quality datasets, ethical considerations regarding data privacy and algorithmic bias, and the seamless integration of AI technologies with existing surgical practices and healthcare systems. In a nutshell, the exciting future of AI in surgery holds great promise and potential for further refinements in surgical techniques, automation, and personalized medicine. Ongoing research, continuous validation, regulatory oversight, and collaboration between AI developers, clinicians, and healthcare policymakers are essential to addressing these challenges and maximizing the benefits of AI in surgical practice, ensuring that these transformative technologies are safe, effective, and accessible to all.
Green brand communication and the profitability of manufacturing firms: The moderating role of environmental commitment
Authors: Akude Derrick Nukunu , Akuma John Kwame , Kwaning Emmanuel Addai , Avevor Peter Besa
Published: November 2024

This study investigates the moderating role of environmental commitment in the relationship between green brand communication and the profitability of manufacturing firms. It seeks to explore how a firm’s dedication to environmental sustainability influences the effectiveness of green brand communication strategies in enhancing profit-generating capabilities, with a particular focus on manufacturing entities in emerging markets. Using a self-administered questionnaire methodology, the survey successfully collected a total of 268 completed responses. These responses were carefully gathered to ensure comprehensive data for analysis. The collected data was  thoroughly analyzed utilizing Smart PLS-SEM (version 4), a sophisticated statistical tool, to test the hypotheses and derive credible insights related to the research objectives, ensuring robust and reliable results. The inquiry identified the presence of a substantial affirmative correlation between the communication strategy and profitability. Additionally, a significant positive influence was observed relative to consumer engagement and profitability. Conversely, the relationship between digital communication and profitability did not reveal statistical significance. Furthermore, it was determined that environmental commitment exerts a notable moderating effect on the relationship between communication strategy and profitability. In addition, environmental commitment demonstrates a significant moderating influence on the interplay between consumer engagement and profitability. Nonetheless, environmental commitment did not exhibit a statistically significant moderating effect concerning the relationship between social media communication and profitability. This research contributes to the academic discourse by elucidating the importance of embedding environmental commitment to fortify the connection between green brand communication and profitability, thereby illuminating their ramifications for theoretical frameworks, managerial practices, and corporate success.
A BUSINESS PROCESS REENGINEERING AT MULYOAGUNG VILLAGE COMMUNITY SERVICE OFFICE
Authors: Djamarullah Ahmad Raihan , Hamsyurah Budiman , Nuryasin Ilyas
Published: November 2024

The Mulyoagung Village Office is a community service office in Mulyoagung Village. One of the services offered at the Mulyoagung village office is a system for making ID cards at the village office using the SiPeduli Desa website, but after analyzing the percentage of throughput efficiency obtained is still 30.85%. There are several processes that require a long waiting time and also manual processing processes so that this condition is still less efficient. Therefore, changes in business processes need to be made to improve the old system that is currently running into a more optimal system. This significant change in business processes is called Business Process Reengineering. The concept of reengineering was born to solve the shortcomings of the old system or legacy system in a business process. Completion of a business process with Business Process Reengineering is done by eliminating processes that do not provide added value and changing manual processes into automated processes by utilizing information technology. The results of this study are business process designs that increase throughput efficiency from 30.85% in the previous process to 89.61% in processes that have been carried out by Business Process Reengineering. The application of Business Process Reengineering can help provide the design of a new business recommendation model that is obtained after an analysis of old business processes and analysis of redesign alternatives is carried out. Business Process Reengineering is also able to improve old processes both in terms of service and speed.
Intrusion Detection System on Nowaday's Attack using Ensemble Learning
Authors: Ndolu Fajar Henri Erasmus , Harwahyu Ruki
Published: November 2024

Attacks on computer networks are becoming more and more widespread nowadays, making this an important issue that must be considered . These attacks can be detected with the Intrusion Detection System (IDS). However, at this time there are new attacks that have not been detected by IDS. Therefore, ensemble learning is used. This research we used Random Forest algorithm for attack detection as an increase in the ability of IDS to detect cyber attacks. The use of the CSE-CIC-IDS2018 dataset is used in this research as a current representative dataset for cyber attack detection. The results of this study we get a binary classification accuracy of 99.6856% and an f1-score of 99.5803% and a multiclass classification accuracy of 99.6944 and an f1-score of 97.8032% with a data ratio ratio dataset of 3:1 normal class to attack class.
A Development of Learning Media in Fluids in Higher Education Based on Android
Authors: Negara Teguh Puja
Published: November 2024

The impact of the corona virus pandemic has disrupted all activities in Indonesia, especially in teaching and learning activities in universities. The lecture process has changed, such as the ban on face-to-face meetings, which has an impact on the learning system on campus. Therefore, the government has implemented an online learning system to overcome the massive spread of the virus while maintaining lectures. One of the issues at issue is practicum activities which require students to come directly to the laboratory, so a solution is needed, namely learning media that can support distance learning to remain effective. The learning media in this study used the Multimedia Development Life Cycle (MDLC) method using Frame by Frame, Low-poly modeling and Shader Graph techniques. The results of this study are an Android-based fluid case learning medium, where, in the application, users can try simulations in the form of 3D animations and work on practice questions and post-tests. Thus, users can better understand fluid materials without the need to do practical work in a physics laboratory.
Voice Control Turn-Based Role Playing Game Development Using Unity Speech Recognition
Authors: Sebastian Sebastian , Dirgantara Harya Bima
Published: November 2024

This research endeavors to create and develop a turn-based role-playing video game utilizing speech recognition as an innovative means to introduce a novel experience in video games. The game is designed and implemented using the Unity game engine. The game prototype produced in this study is intended to provide a unique experience when playing games, namely using voice recognition to try to beat opponents. The researcher adopts the Extreme Programming methodology, compassing four stages: Planning, Design, Develop and Testing/Release. The culmination of this research is a turn-based role-playing game featuring speech recognition controls intended for Windows computers equipped with a microphone. The game offers players fresh and innovative gameplay by incorporating speech recognition. Based on the closed beta trial on three respondents, the result was that there was an influence from the playing room. Two words are difficult for the game to detect: "molten spear" with an average detection rate of 40% and "chakra magic" with an average detection rate of 33%.
Implementation Analytical Hierarchy Process Algorithm for Design and Development Website Hero Mage Recommendation for Mobile Legends
Authors: Lay Ferry , Tobing Fenina Adline Twince
Published: November 2024

Mobile Legends is a Multiplayer Online Battle Arena genre game that is currently hot. There are 122 heroes in Mobile Legends which are divided into 6 roles. The currently popular role is mage, where this mage role occupies 3 of the 5 most used in the MPL S11 tournament. Purchasing heroes can be done with a currency called battlepoints amounting to 32,000. The collection of battlepoints is limited to one week, and there is no refund feature for hero purchases, meaning that if the player makes the wrong hero purchase, the player has to collect the currency again to be able to buy another hero. The Mobile Legends mage hero recommendation system is a system that can provide assistance in purchasing heroes that suit user preferences. Recommendation results are provided based on input provided by the user and processed using the Analytical Hierarchy Process method. The evaluation results using the End User Computing Satisfaction method obtained a percentage of 88.64%, which indicates that the system has been well developed and can be used to provide mage hero recommendations for the Mobile Legends game.
Implementation of AHP Algorithm for Design and Development Halal Food Recommendation System at Cirebon Regional
Authors: Geneva Erick Abraham , Kusnadi Adhi , Tobing Fenina Adline Twince
Published: November 2024

Cirebon is one of the cities in Indonesia that has a variety of unique culinary delights. One of the most famous Cirebonese halal culinary delights is nasi jamblang. However, the many choices of halal Cirebonese food can make tourists struggle to choose food that suits their taste and preferences. This research aims to design and build a halal Cirebonese food recommendation system using the Analytical Hierarchy Process (AHP) method. The AHP method is used to determine the weights of the factors that influence the selection of halal Cirebonese food. This recommendation system is built using PHP and JavaScript programming languages, as well as Laravel, React, and MySQL frameworks. This recommendation system has been tested by distributing questionnaires using End User Computing Satisfaction method with google form to 35 respondents The test results show that this recommendation system produces a user satisfaction value of 87.92%. This value indicates that this recommendation system has met user expectations.
Implementation of Backpropagation Method with MLPClassifier to Face Mask Detection Model
Authors: Wijaya Wendy Hendra , Oetama Raymond Sunardi , Halim Fransiscus Ati
Published: November 2024

Corona Virus Disease 2019 (COVID-19) is a virus that has spread widely and has become a global pandemic. The virus also can be spread through droplets made from coughs or sneezes. The Minister of Health of the Republic of Indonesia has issued a decision regarding this COVID-19 pandemic case, one of which is "Using personal protective equipment in the form of a mask that covers the nose and mouth to the chin”. This research aim is to detect masks on the face using the CRISP-DM framework and the backpropagation neural network method with MLPClassifier. The dataset is using RMFD (Real-World Masked Face Dataset. The dataset contains photos of human faces using mask and human faces without using mask. The result showed that the backpropagation neural network method can be used to detect mask on human faces with 94.4% accuracy. The accuracy from this research is outperform DNN algorithm. This research is expected to broaden the insight regarding the detection of masks to prevent the spread of COVID-19.
INDONESIAN ANALYSIS SENTIMENT ON NON FUNGIBLE TOKEN (NFT)
Authors: Erfina Adhitia , Mahardika Dinda Tasya
Published: November 2024

NFT or Non-Fungible Token is a unique token attached to a digital asset that is connected to the blockchain system. Various assets, digital art, music, tweeters, memes, sold as NFT, NFT has been widely discussed on various social media, one of which is Youtube. NFT has become a new trend for the Indonesian people, based on the fact that someone who sells  selfie photos at the Open Sea is viral because people think it is a trivial thing but why do they produce it, but people actually accept the trend as a mistake, they intentionally upload their identity on the platform. This Open Sea, this happened because there was little information related to NFT and the public did not really understand that NFT could be a bridge for criminals. But in this case, many people as artists have been greatly helped in the marketing of their art. And even when the stock market is down, NFT remains one of the digital assets that attracts the attention of the world community, therefore this study was made to analyze the public's response with sentiment analysis, data obtained from Youtube content comments and then classified into Positive, negative, and neutral classes with TF IDF for the process of word weighting and classification using the Naïve Bayes Classifier algorithm. The test is carried out by calculating accuracy, precision, recall and F1-score, using a variety of training data and test data. And the accuracy results are 64%, for positive prediction class precision is 63%, neutral class precision is 83%, while for negative prediction is 0% and recall obtained from positive is 99%, neutral recall is 0.7% while negative is 0%. These results are the data obtained on Youtube comment
COBIT 5.0: IT Governance Measurement on Reputable Bank in Indonesia
Authors: Priyono Eric Bagus Saputra , Wella Wella
Published: November 2024

PT X is required to ensure that IT governance runs well. The maturity level of IT governance needs to be measured to determine what factors each company can improve on. The purpose of this study is to assess the level of capability of PT X, which will be measured using the COBIT 5.0 framework from ISACA, as well as to provide recommendations regarding governance and management of information technology that can build PT X. Measurements were carried out on BAI09 (Manage Assets) and DSS03 (Manage Problems). The results obtained are the BAI09 process and the DSS03 process both stop at Level 4 (Predictable Process), with an average value of 81.30% for the BAI09 process and an average value of 81.84% for the DSS03 process.
Enterprise Resource Planning (ERP) SAP Business One Evaluation and Improvement Recommendation using Customized Odoo
Authors: Nurrohmah Winda Maulidina , Wiratama Jansen
Published: November 2024

The goal of this research is to carry out and understand the evaluation of the success rate on SAP Business One, and the results of the evaluation are developed into the configuration and customization activities of the Odoo ver 15.0 open-source ERP system, because they do not have access rights to perform customization in the SAP Business One system. As a result, Odoo is one of the open-source ERP systems that can accommodate research recommendations and outcomes. The goal of this research is to determine the issues that arise throughout the company's use of the SAP Business One system. It is then anticipated to be a solution to company difficulties and to suit the firm's needs.
Implementation of Simple Additive Weighting on Decision Support System for Accoustic Guitar with Web-Based (Study Case: Chaniago Sport)
Authors: Imanuel Frans , Tobing Fenina Adline Twince
Published: November 2024

The acoustic guitar is one of the most popular musical instruments because music itself is a universal language that everyone can understand. Acoustic guitars are available in many choices such as wood types, brands, prices, and  many  sizes. Many people who want to buy a guitar are often confused when they have to choose an acoustic guitar that suits their  needs, this happens because there are many aspects of an  acoustic guitar that must be considered as already mentioned. The demands of work and the busyness of today’s society This makes many people unable to choose and see the acoustic guitar according to their needs in music stores. Therefore, this system was created as an acoustic guitar recommendation system, so  that people can choose an acoustic guitar that suits their needs and buy an acoustic guitar online based on people’s preferences. The recommendations given by this system are obtained from calculations using the simple additive weighting method or known as the weighted addition method. This simple additive weighting method has been tested in this study and can be implemented correctly and as needed. End-user satisfaction is also obtained using the end-user computing satisfaction (EUCS) method so that the recommendation system that has been successfully built can be said to be very good for users in providing acoustic guitar recommendations.
Design and Development of a Learning Style Identification Application for JPTK Students using the K-Nearest Neighbor
Authors: Ramadhan Firdaus Ditio , Liantoni Febri , Prakisya Nurcahya Pradana Taufik
Published: November 2024

Learning styles are crucial for all students, as the chosen learning style can greatly assist them in learning. The data source for this research originates from questionnaire results distributed to JPTK students of the 2019-2021 cohorts, which were used to assess the effectiveness of a learning style product on the students' JPTK website. This study employs the K-Nearest Neighbor approach, which utilizes the principle of nearest neighbors to categorize students' learning styles based on provided features. The data used in this research is derived from the website that students use to input information about their preferred learning styles. Various elements, including visual, auditory, and kinesthetic preferences, are present in the questionnaire on the website. Subsequently, the data is processed and fed into a Python K Nearest Neighbor model to predict students' learning styles and nearest neighbors. The evaluation results indicate that the developed classification model achieves a reasonably high accuracy level of 93%, making it a useful tool for effectively and efficiently identifying students' learning styles. It is hoped that implementing this learning style classification model will benefit the field of education. By understanding students' learning styles, educators can create more tailored lesson plans, enhance learning outcomes, and reduce the likelihood of knowledge loss.
REAL-TIME TOMATO QUALITY DETECTION SYSTEM USING YOU ONLY LOOK ONCE (YOLOv7) ALGORITHM
Authors: Muarofah Isna Ayu , Vikri Muhammad Jauhar , Sa’ida Ita Aristia
Published: November 2024

Real-time object detection is a crucial aspect of computer vision. With the increasing prominence of the big data field, it has become easier to gather data from various sources. Over the past few decades, computer vision inspection systems have become essential tools in agricultural operations, and their usage has seen a significant rise. Computer vision automation-based technology in agriculture is increasingly being employed to enhance productivity and efficiency. Tomato is a widely utilized crop commodity, finding applications in food, cosmetics, and pharmaceuticals. Consequently, tomato farming continues to evolve and has become one of the nation's export commodities. YOLO is an algorithm capable of real-time object detection and recognition. In this study, the YOLOv7-tiny architecture, which has lower computational overhead, was utilized. For quality detection of tomatoes, they were categorized into three classes: ripe, unripe, and defective. The trained model yielded a recall score of 0.97, precision of 1.0, a PR-curve of 0.838, and an F1-score of 0.81, indicating that the model learned effectively. The research achieved an accuracy of 90.6% on original images with an average IoU of 0.90 and a detection time of 2.7 seconds. In images with added light disturbance, the average accuracy was 91.2%. Images with reduced light yielded an average accuracy of 92%, while images with blur disturbance had an average accuracy of 78.2%. In real-time testing, ripe tomatoes were detected up to a maximum distance of 90cm, unripe tomatoes at 90cm, and defective tomatoes at 70cm.
Sentiment Analysis on Song Lyrics for Song Popularity Prediction Using BERT
Authors: Agatha Hana , Putri Farica Perdana , Suryadibrata Alethea
Published: November 2024

The increasingly competitiveness in music industry is giving some musicians disadvantages. Musicians need to pay more attention to the factors that influence the popularity of a song, so their song can be popular and they can gain a lot of profit. One of the various factors that can affect a song popularity is the lyrics. The influence of the lyrics can be explored through sentiment analysis. Sentiment analysis is a computing study that identify sentiments or emotions in a text. By conducting sentiment analysis on the lyrics, song popularity can be predicted. Based on the prediction result, songwriters can evaluate their lyrics, so their song can be popular. Bidirectional Encoder Representations from Transformers (BERT) is an excellent algorithm in terms of sentiment analysis. In this study, a BERT model was developed to predict the song popularity, based on the sentiment analysis of the song lyrics. The popularity class of a song will be predicted, based on the results of lyrics sentiment analysis. The developed model is a model that has been trained with English songs. Based on the experiment, the model that used oversampling method achieved accuracy by 87%, precision by 88%, recall by 87%, and f1-score by 87%.
Development of a Mouse Pad Selection Recommendation System Using the Simple Additive Weighting (SAW) Approach
Authors: Kandoko Charoline , Waworuntu Alexander
Published: November 2024

In the current era of technological advancement and growth, especially in the realm of virtual entertainment, specialized equipment like mouse pads has become increasingly essential. Often, the vast array of mouse pad types and brands available can be overwhelming, making it challenging for consumers to choose one that meets their specific needs. This research aims to design and develop a mouse pad recommendation system to assist individuals in selecting the most suitable mouse pad. The study employs the Simple Additive Weighting method, a weighted sum approach for problem-solving, enabling users to receive tailored recommendations based on criteria such as size, thickness, stitching, material, and price across various brands. User satisfaction was measured using the End User Computing Satisfaction (EUCS) method, achieving a satisfaction percentage of 88.67%. This indicates that the system is effective as a mouse pad recommendation tool. The mouse pad recommendation system has been successfully constructed using the Simple Additive Weighting method, following a comprehensive process of design, development, and system testing.
A Comparative Study of Body Motion Recognition Methods for Elderly Fall Detection: A Review
Authors: Apriantoro Roni , Setyawan Muhammad Adriano Khairur Rizky , Lavindi Eri Eli
Published: November 2024

To maintain the welfare of the elderly, intensive and effective monitoring is needed to ensure their safety. Conventional elderly activity monitoring has several limitations (i.e., space and time) due to human abilities. This problem can be overcome by applying real-time monitoring methods using Wireless Body Area Networks (WBAN) and Artificial Intelligence (AI). Several methods have been used and tested, including artificial intelligence implementations from sensor data-based to computer vision-based pattern recognition for body motion classification. Several methods that have been studied show accurate results in classifying elderly body motions/gestures. However, the Human Activity Recognition (HAR) method performs better for elderly activity monitoring applications and makes fall classification more accurate.
Comparing Karate Framework with Others for Automated Regression Testing: A Case Study of PT Fliptech Lentera Inspirasi Pertiwi
Authors: Dayanti Afina Putri , Tony Tony
Published: November 2024

In the rapidly evolving digital era, applications, and software systems increasingly rely on Application Programming Interfaces (APIs) to enable interaction, integration, and functionality extension. However, manual testing of APIs is often inefficient and challenging to reuse when changes occur. To address this, automation testing has become a more effective choice, where test scripts can verify and execute tests repeatedly, easily adapting to API changes. Essentially, automation testing plays a vital role in software maintenance, particularly in regression testing, which tests modified or upgraded software versions to ensure that their core functions remain unchanged and unaffected. One approach to automation testing is employing the Software Testing Life Cycle (STLC), which follows a systematic series of stages conducted by the testing team to ensure software product quality. This paper utilizes PT Fliptech Lentera Inspirasi Pertiwi’s public API to conduct testing on 25 scenarios from two modules. The objective is to utilize the Karate Framework to conduct these automated regression tests, resulting in an impressively short testing duration, averaging only 42.645 seconds, or approximately 1.706 seconds per scenario. A comparison with the Behave framework, using the same scenarios but with differences in steps, reveals that Behave achieves a duration of 18.762 seconds, or 0.750 seconds per scenario, making it 127.295% faster than Karate. However, in terms of the number of steps, Behave covers only 188, while Karate includes 543. This means that Behave requires 0.100 seconds per step, while Karate necessitates 0.079 seconds per occurrence. Karate provides more detailed results by 188.830% per step or 26.582% in terms of step duration. The primary goal is to enhance testing efficiency, expedite issue identification and resolution, provide a clearer testing process, and potentially improve overall software quality.
U-TAPIS Sal-Tik : Typing Error Detection Using Random Forest Algorithm
Authors: Overbeek Marlinda Vasty , Glennardy Bryan , Mediyawati Niknik , Nusantara Samiaji Bintang , Sutomo Rudi
Published: November 2024

The development of technology in the field of journalism has grown very rapidly. However, in the field of journalism there are still frequent deviations from the language on online news portals. This can be seen from the aspect of spelling and word usage. Spelling mistakes that occur in the news can cause the information contained in the news to be unclear and ambiguous. Based on these problems, a study was conducted to create a model to detect type error in Indonesian. This model is created using the random forest algorithm. random forest is an algorithm that works by building several decision trees and then combining the decisions from each tree that has been built and taking the most votes from the predictions of each tree so that it will produce stable and accurate predictions. The results of the accuracy of the model in the research that has been done is 100%. However, it should be noted that this 100% result is that the model is able to detect words that are already contained in the dataset. Based on the evaluation results that have been carried out, because the detected word is contained in the dataset, the accuracy issued is 100%. The built model successfully detects type error in Tribunnews news articles.
Sentiment Analysis of IMDB Movie Reviews Using Recurrent Neural Network Algorithm
Authors: Saputra Aryasuta , Tobing Fenina Adline Twince
Published: November 2024

IMDb is a well-known platform that provides user reviews and ratings of various movies. The number of reviews found on IMDb is quite large, reaching thousands of reviews. Although a movie can have a high overall rating, it is still possible to receive negative reviews from some viewers. Therefore, the purpose of this sentiment classification system is to provide a benchmark for the level of sentiment contained in the movie, and hope that filmmakers can use this information as a reference in the development of their next movie. In this research, reviews from IMDb users are classified into two types, namely positive reviews and negative reviews. The program was created using the Python language with the LSTM (Long Short-Term Memory) classification model of the RNN (Recurrent Neural Network) algorithm. The purpose of using this algorithm is to measure the level of prediction accuracy in the classification process. The results of three test ratios, namely 60:40, 70:30, and 80:20, show that in the scenario of 80% data training and 20% data testing has better performance with the results accuracy of 96%, precision of 97%, recall of 98%, f1-score of 97%.
Public Sentiment Analysis on the Transition from Analog to Digital Television Using the Random Forest Classifier Algorithm
Authors: Samudera Elfajar Bintang , Waworuntu Alexander , Lumba Ester
Published: November 2024

Television is one of the most popular media for entertainment and information. Analog television is the most widely used type among the public. However, with technological advancements, analog television is becoming obsolete and is being replaced by digital television, which offers better performance. On November 2, 2022, the Government officially mandated the transition from analog to digital broadcasting. This Analog Switch Off program has elicited various pro and con opinions among the public. Twitter, a widely used social media platform, facilitates rapid communication and information dissemination among users. This study aims to classify public sentiment regarding the Analog Switch Off policy as either positive or negative. The classification model used is the Random Forest algorithm, with the Lexicon Inset for data labeling, Count Vectorizer and TF-IDF Vectorizer for data vectorization and weighting, and various train-test data splits. The study achieved the best classification performance using the Count Vectorizer method, with an 80%:20% train-test data ratio, yielding an accuracy of 88%, precision of 88%, recall of 88%, and an F1-score of 88%.
Index Terms—Analog Television; Digital Television; Sentiment; Twitter; Random Forest