bluuebunny/crossref_metadata_2025 huggingface dataset:
A review on computer applications in agricultural science
Authors: Usman Suleiman
Published: November 2024

Computer application in agricultural science is an advanced technology that has changed the surface of traditional agricultural systems throughout the history of human development globally. This paper aims to provide integrated information regarding the application of computers in agriculture and covers a wide range of genes that address MIS and its manifestations in science, computers and their major types and components, statistical applications, and functional services of various mobile apps in animal, extension, crop, fishery, forestry, soil and veterinary studies. Computer application affects all aspects and components of agriculture and ensures sustainable food security and economic advancement in all nations. Studies and assessments in animal science, agricultural extension, crop science, fishery, forestry and soil science have increasingly employed computer applications for different purposes. Computer application systems of various types (mainframe, minicomputer, PC, supercomputer, workstation), hardware and software, MS words, Excel and PowerPoint have played key roles in agriculture. These various types of computers deliver the most advanced interpretations of agricultural results through documentation and statistical analysis. The use of computers and computer technologies in various agricultural studies should be carefully practiced. Using agricultural computers will help ensure the accuracy of the results and technical interpretations, leading to increased food production, animal productivity, and sustainable economic development.
Assessment of Computer Vision Syndrome (CVS) Among Students
Authors: . Saurabh , Selvam S Dinesh
Published: November 2024

Extended digital screen usage poses considerable health risks, with approximately 70% of users experiencing Computer Vision Syndrome (CVS). The prevalence of CVS among students varies globally, with reports of CVS affecting up to 90% of users. This study aims to assess CVS prevalence among students at Amity University, Manesar, and examine associations between CVS and demographic factors. Using a quantitative descriptive survey design, data was gathered from 50 students through structured questionnaire. Results indicate that 20% of participants are confirmed cases of CVS, 14% are at high risk, and 26% at low risk, underscoring a pressing need for awareness and preventive strategies.
The Role of AI-Based Learning Systems in Enhancing Biology Education for Secondary School Students: Impact on Performance, Engagement, and Retention
Authors: Alhassan Najmuddeen , Lawal SB , Ibrahim Sa’adiya , Yakubu Miracle
Published: November 2024

The paper examined the Role of AI-Based Learning Systems in Enhancing Biology Education for NCE Students: Impact on Performance, Engagement, and Retention. The paper sets four objectives, four research questions and four hypotheses. The population of the study is made up of over 320 school teachers in the 40 registered secondary schools in Zaria Local Government Area of Kaduna State. The research randomly selected 5 schools for the study and 10 teachers and 20 students were randomly selected from each of the schools making a total of 150 teachers and students for the study. The research instrument used in this study was a self-constructed questionnaire designed to collect data and responses from the teachers in secondary schools in Zaria Local Government Area of Kaduna State regarding their opinions in giving information concerning the items in the questionnaire. 179 questionnaires were distributed to the respondents personally by the researchers in the sampled schools of the study area. These results were placed on a Likert four-point rating scale; 4= Strongly Agree (SA), 3= Agree (A) 2= Disagree (D), 1= Strongly Disagree (SD). The split half and Pearson product-moment correlation coefficient were used to determine the reliability of the instrument. The result of the pilot test produced an index of 0.78 which was adequate to consider the instrument reliable for the study. Statistical Package for Social Science version 27 was used to analyse the data collected. A decision rule was reached that a mean score of 2.50 and above falls under Agreed while below 2.50 falls under Disagreed. The first finding revealed that the result of the study accepted that students who use AI-based learning systems will have a significantly better understanding and retention of biology concepts compared to those who do not with a mean difference of 2.89, t value of 8.448821 and P value of 0.0001. The second finding revealed that the use of AI-based learning systems will lead to a significant improvement in students' academic performance in biology with a mean difference of 3.03, t value of 7.561322 and P value of 0.0001. The third finding revealed that AI-based learning systems will significantly enhance student engagement and motivation in learning biology with a mean difference of 3.26, t value of 6.639 and P value of 0.0001. The fourth finding revealed that students using AI-based learning systems will outperform those using traditional learning methods in biology assessments with a mean difference of 1.07, t value of 5.439 and P value of 0.0001. The study recommends that AI should be used by teachers to boost students' motivation towards their studies. This can be achieved through engaging learning mechanisms that make studying more appealing and teachers should be encouraged to use AI to identify students who are struggling and provide necessary interventions to support their academic growth.
Utilization of generative adversarial networks (GANs) in the replication and restoration of calligraphy art
Authors: Zhu Xiaojun
Published: November 2024

With the continuous integration of culture and technology, the replication and restoration of calligraphy art has become a new direction in the restoration of traditional calligraphy and painting. The research on the replication and restoration of calligraphy art is of great significance in contemporary art. However, the accuracy and authenticity of the replicas in the process of replication and restoration calligraphy art are not high, and there are significant differences in material selection. This paper started with GAN (Generative Adversarial Network), collected a large amount of image data from calligraphy art works, trained a generative adversarial network, and used the trained model to process calligraphy art works. Compared with traditional replication techniques, the cost, restoration efficiency, and cultural inheritance and recognition of the two in calligraphy art replication were analyzed. Research has found that the highest score for the restoration of calligraphy art quality using traditional methods can only reach 89.9 points (out of a total of 100 points), while the highest score for GAN can reach 96.4 points. Moreover, the application of GAN can save the cost of calligraphy art for restoration, improve restoration efficiency, and enable flexible application in different scenarios.
Feature selection for intrusion detection based on an improved rime optimization algorithm
Authors: Peng Qingyuan , Wang Xiaofeng , Tang Ao
Published: November 2024

With the rapid development of information technology, cybersecurity issues have become increasingly prominent, posing serious threats to national security, economic growth, and personal privacy. Intrusion detection systems have been widely applied to ensure network security and prevent malicious cyber-attacks. In intrusion detection, redundant and irrelevant features not only slow down the classification process but also hinder classifiers from making accurate decisions, resulting in decreased system performance. Addressing the problem of low accuracy in intrusion detection systems due to high-dimensional datasets, we propose a network intrusion detection method based on an enhanced Rime Optimization Algorithm for feature selection. Firstly, building upon the traditional Rime Optimization Algorithm, we introduce Cauchy mutation and differential mutation operations to improve both global and local search capabilities. Cauchy mutation introduces a heavy-tailed distribution to increase the probability of escaping local optima, while differential mutation, through the differential operator, further enhances solution diversity and algorithm convergence speed. Combining the two mutation operations, the optimization algorithm achieves a good balance between global search and local search, effectively avoids premature convergence and falling into local optimum, and effectively improves the feature selection results. Secondly, the improved Rime optimization algorithm (IRIME) was applied to the feature selection process of intrusion detection system, and it was combined with the decision tree classifier to construct a wrapper feature selection algorithm, which could directly optimize the classification task and avoid the mismatch between feature selection and classifier. The optimized algorithm can quickly select the most representative feature subset from the high-dimensional feature space, significantly reducing the computational cost. At the same time, the selected feature subset can more accurately reflect the inherent law of the data set, thereby improving the prediction accuracy of the classifier. Finally, NSL-KDD and UNSW-NB15 datasets were used for performance evaluation. Experimental results show that compared with several feature selection algorithms, the proposed method achieves the best binary classification performance after feature selection. Specifically, it is superior to other algorithms in terms of precision, accuracy, F1 score and recall of all evaluation metrics.
Study the Impact of Banking Management Choices on Disclosing Future Profits and the Impact of Bank Characteristics on Management Choices
Authors: KAREEM AHLAM HAMEED , Mabrouk Houda Ben
Published: November 2024

As we are in the process of keeping pace with globalization and challenging global markets, attention must be paid to two important aspects, the first of which is attention to practical activities and the second of which is adequate accounting disclosure in the financial reports and providing them to the concerned authorities and stakeholders inside and outside the company, and placing this disclosure within a framework with which the financial reports in companies can be compared, This study aims to uncover and measure earnings management practices in the Iraqi banking environment, and attempt to measure earnings management practices. To achieve this goal, a sample of fifteen Iraqi banks listed on the stock market and stock exchange was used for the period (2010 - 2020), The study tested the impact of earnings management practices using the modified Jones model on future profits and the operating cash flows that make up current profits. The modified Jones model (Jones: 1991) is one of the models used to measure earnings management through the use of a regression model to measure optional accruals. Several hypotheses were used for the study: The effect of optional dues on future profits, The larger the bank, the greater the impact of receivables on future profits., The greater the bank’s debt ratio, the greater the impact of optional receivables on future profits, The greater the ratio of the market value to the book value of the bank’s shares, the greater the impact of optional dues on future profits, The greater the bank’s revenue growth, the greater the impact of optional accruals on future profits, The greater the deviation in the bank’s operational activity, the greater the impact of optional accruals on future profits, This study reached important results, including: There is a positive relationship between optional entitlements and future levels of profits. Optional benefits are the least sustainable component of current profits in the future.
Comparison of Deep Learning Algorithms for Retail Sales Forecasting
Authors: Ahmed Rana Shakeel , Hasnain Muhammad , Mahmood Muhammad Hamza , Mehmood Muhammad Abid
Published: November 2024

We investigate the use of deep learning models for retail sales predictions in this research. Having a proper sales forecasting can lead to optimization in inventory management, marketing strategies, and other core business operations. This research proposed to assess deep learning models such as Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Multilayer Perceptron and hybrid CNN-LSTM model. The models are further improved by using some dense layers to embed daily sales data from the biggest pharmaceutical firm in the study. Models are then trained on 80% of the dataset and tested on remaining 20%. The accuracy of the proposed research is compared using evaluation metrics like Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results indicate that the CNN-LSTM model outperforms the others, achieving the lowest RMSE and MAE values, making it the most suitable for sales forecasting in the given context. This research contributes to the field by demonstrating the superiority of hybrid models in handling complex, temporal data for predictive analytics. Future work will explore the integration of additional data sources and advanced deep learning architectures to further improve forecasting accuracy and applicability.
Enhancing Ocular Health Precision: Cataract Detection Using Fundus Images and ResNet-50
Authors: Khan Irshad , Akbar Wajahat , Soomro Abdullah , Hussain Tariq , Khalil Irshad , Khan Muhammad Nawaz , Salam Abdu
Published: November 2024

Cataracts are a leading cause of blindness in Pakistan, contributing to more than 54% of cases due to poor living condition, nutritional deficiencies, and limited healthcare access. Early detection is critical to avoid invasive treatments,but current diagnostic approaches often identify cataracts at advanced stages. This paper presents an advanced,automated cataract detection system using deep learning specifically the ResNet-50 architecture, to address this gap. The model processes fundus retinal images curated from diverse datasets, classified by ophthalmologic experts through a rigorous three-stage process. By leveraging the ResNet-50 model, cataracts are categorized into normal,moderate,and severe, achieving an accuracy of 97.56% on full images. Notably, the system performs well even on partial images with 70% visibility, maintaining an accuracy of 95.23%, thus minimizing the need for extensive images restoration. The dataset was augmented to include 17,500 images,ensuring robust training. The model's ability to detect cataracts with high precision in images with varying visibility(70% ,80%,85% and beyond) demonstrate its flexibility and reliability, consistently achieving accuracy above 95.50%. This research offers a non-invasive, efficient solution particularly suited for remote areas, addressing the limitations of the late-stage diagnoses. It represent a significant advancement in cataract detection and has the potential to revolutionize global cataracts identification through early, accurate intervention.
Penerapan Metode Waspas dalam Pengambilan Keputusan Rekrutmen Anggota KPPS Pemilu
Authors: Agung Aulia Tama  , Marto Sihombing  , Anton Sihombing
Published: November 2024

Members of the KPPS (Voting Organizing Group) are responsible for organizing voting in a polling station (TPS) during general elections in Indonesia. They are the spearhead in carrying out the democratization process by supervising and ensuring the continuity of elections honestly, fairly, and transparently. The duties of KPPS members include preparing TPS before voting begins, receiving and examining voters, supervising the election process to ensure compliance with applicable regulations, counting votes after voting is complete, reporting election results, and maintaining security and order around TPS. Decision support system is a Decision support system or Decision Support System (DSS) is an interactive system that supports decisions in the decision-making process through alternatives obtained from data processing results. The purpose of this study is to facilitate the recruitment of members of the Voting Organizing Group (KPPS). The research method is Weighted Aggregated Sum Product Assessment (WASPAS). WASPAS is to find the most appropriate priority location choices using weighting. The results of this study are that the development of this support system can help the KPU in selecting or selecting KPPS members and this decision support system as a tool in developing KPPS members by viewing or using criteria according to the criteria needed using the WASPAS method.
Pengelompokan Penyakit pada Pasien Berdasarkan Usia dengan Metode K-Means Clustering
Authors: Maida Andriani  , Akim Manaor Hara Pardede  , Magdalena Simanjuntak
Published: November 2024

This research aims to cluster disease data based on patient age using the K-Means method at RSUD Dr. RM. Djoelham. In this case study, the clustering method with the K-Means algorithm is used to group patients based on patient age, address and type of disease. With this method, information can be obtained regarding patient grouping patterns based on age at Dr. RM. Djoelham, who helps identify the closest relationships between patient groups and provides insight into the distribution of disease across age groups, regions and types of disease suffered.This research was conducted at RSUD Dr. RM. Djoelham by loading data from patients treated at the hospital. The data used is 1,100 patient data from 2022-2024 which has been recorded by the hospital. This patient data will be analyzed using 3 variables in the research, namely Patient Age (C1), Address (C2), and Type of Disease (C3). With the results, cluster 1 contains 320 data, cluster 2 contains 326 data, and cluster 3 contains 454 data.
Enhancing Edge Computing Performance for IoT Applications Using Federated Learning Techniques
Authors: Lucas Henry Young  , Grace Olivia Hall
Published: November 2024

As Internet of Things (IoT) devices proliferate, edge computing has become essential for reducing latency and improving data privacy. This paper explores federated learning as a method to enhance the efficiency and security of edge computing systems. We implement and evaluate federated models in various IoT environments, demonstrating how federated learning can reduce data transfer and computation load while maintaining accuracy in data analysis.
Image Processing Techniques for Enhancing Satellite Imagery in Disaster Management
Authors: Amanda Putri  , Budi Hartono  , Nike Ayu
Published: November 2024

This study examines advanced image processing techniques to improve satellite imagery for use in disaster management and recovery efforts. Through methods like deep learning-based image segmentation and noise reduction, we enhance image clarity and detail, allowing for better decision-making in emergency response. The results indicate a significant improvement in identifying affected areas, aiding faster and more accurate response.
Optimization Of Big Data Processing Using Distributed Computing In Cloud Environments
Authors: Rahul Dev Singh  , Vikram Kumar Gupta  , Priya Anjali Patel
Published: November 2024

The growth of big data has driven the need for efficient data processing methods, especially in cloud computing environments. This study evaluates distributed computing frameworks like Apache Hadoop and Apache Spark for optimizing big data processing. By analyzing different configurations, we demonstrate how distributed systems can significantly reduce processing time and improve resource utilization, making them ideal for handling complex datasets in cloud environments.
Enhancing Cybersecurity In Smart Cities Through IoT Device Management
Authors: Siti Aminah Binti Ismail  , Ahmad Faizal Bin Mohd Ali
Published: November 2024

The rise of smart cities brings increased interconnectivity, but also new security vulnerabilities, especially among IoT devices. This study investigates methods for improving cybersecurity in smart cities by implementing IoT device management protocols. We examine approaches such as network segmentation and secure authentication to mitigate common threats, thus providing a safer environment for urban digital infrastructure.
Enhancing Security in Industrial IoT: Authentication Solutions Leveraging Blockchain Technology
Authors: Rebecca Ling Ze Siew  , Brendan Chan Kah Le  , Lee Kai Yue  , Nuri Nazirah Binti Ismail  , Xavier Liong Zhi Hao  , Muhammad Faisal
Published: November 2024

The rapid advancement of Industrial Internet of Things (IIoT) technology necessitates robust authentication solutions to ensure security, scalability, and efficiency. This project, titled "Enhancing Security in Industrial IoT: Authentication Solutions Leveraging Blockchain," examines various blockchain-based authentication methods for IIoT and identifies their strengths and weaknesses. Despite the enhanced security and decentralized nature of blockchain, issues such as scalability, high latency, and computational load persist. To address these challenges, we propose the integration of Multi-Factor Authentication (MFA) as a supplementary solution. MFA can distribute the authentication load, enhance flexibility and security, and reduce latency by utilizing quick-to-verify factors. Moreover, MFA ensures high availability and scalable storage and processing through cloud services, seamlessly integrating with existing systems to provide a superior user experience. This comprehensive approach not only mitigates the inherent limitations of blockchain technology in IIoT but also reinforces the overall security framework, ensuring resilient and efficient authentication mechanisms. The results demonstrate significant improvements in system performance and user satisfaction, establishing MFA as a viable enhancement to blockchain-based IIoT security solutions.
Evaluation of Information Technology Service Governance Using the ITIL Method : A Strategy for Improving Business Intelligence Efficiency at Bank Rakyat Indonesia
Authors: Andysah Putera Utama Siahaan  , Wiko Pratama  , Juliyandri Saragih  , Muhammad Indra  , Muhammad Wahyudi
Published: November 2024

Information Technology (IT) service management plays a critical role in supporting the efficiency and effectiveness of business intelligence processes within modern organizations. This study aims to evaluate IT service governance in Bank Rakyat Indonesia using the Information Technology Infrastructure Library (ITIL) framework. This approach focuses on improving operational efficiency, service management, and aligning IT services with business needs. The research method involves a detailed analysis of service processes and activities based on ITIL stages, ranging from service strategy to continuous improvement. The findings indicate that ITIL implementation significantly enhances IT service management and promotes business intelligence effectiveness within the organization. Recommendations for further development are also provided to improve the quality and speed of IT services in the future.
IoT, Anomaly Detection, Machine Learning, K-Nearest Neighbors, Random Forest, Real-Time Detection
Authors: James Anderson  , Emily Johnson  , Michael Brown
Published: November 2024

The increase in connected IoT devices causes increased vulnerability to cyber attacks. This research develops a hybrid machine learning model to detect real-time anomalies in IoT networks. This model combines the K-Nearest Neighbors (KNN) and Random Forest (RF) algorithms to increase accuracy and efficiency. Evaluation was carried out using the UNSW-NB15 dataset to test model performance. The results show that this hybrid approach is able to detect anomalies with high accuracy and a low false positive rate.
Optimizing the Transmission of Church Information Through the Design Thinking-Based Church News Application
Authors: Gunawan Prayitno  , Jenny Tandi
Published: November 2024

The church plays a crucial role in spreading Christian values and nurturing the growth of faith within its community. However, in the context of GPSI EFATA, there are several challenges in effectively conveying church information. These challenges include the unappealing presentation of physical congregation news, the accumulation of paper, and limited distribution of information. In order to address these issues, this research project utilizes the Design Thinking method to develop a smartphone-based application for congregational news. The Design Thinking method consists of five stages: empathy, definition, ideation, prototype, and testing. During the empathy stage, the needs of the congregation are identified, particularly the need for more accessible and engaging information. The ideation stage then generates a solution in the form of a smartphone application. This application includes various features such as notifications, prayer schedules, financial reports, photo galleries, and management profiles. A prototype of the application was developed to meet these needs and was subsequently tested using a questionnaire. The results of the testing indicated that the application had an easy-to-understand interface, adequate features, and received suggestions for improvement. Overall, this smartphone application offers a modern and efficient solution to the challenges of delivering information within churches. It enhances accessibility and improves the quality of communication with the congregation.
Online Class UI/UX Design Using Design Thinking Method in Virtual Reality Environment
Authors: Bosya Perdana  , Tata Sutabri
Published: November 2024

The development of Virtual Reality (VR) technology opens up new opportunities to improve the quality of online learning through more interactive and immersive learning experiences. This study aims to design the user interface (UI) and user experience (UX) of VR-based online classes using the Design Thinking method to meet students' needs in a virtual learning environment. The Design Thinking method, which includes the stages of empathy, definition, ideation, prototype, and testing, is applied to produce a user-friendly interface design that supports student engagement and social interaction during the learning process. The results of the study show that the VR-based interface is able to increase student engagement through more active interactions, intuitive navigation, and collaboration features that approach interactions in a physical classroom. Testing of the prototype shows that this design can meet students' needs in increasing engagement and learning comfort. It is hoped that this study can be a reference in the development of an effective and efficient VR-based online learning platform.
The Role of Language Proficiency in Academic Success for International Students: A Case Study Approach
Authors: Mohamed Ali Hamade  , Noor Azizi Ismail  , Siti Nurul Asyiqin Mohamed
Published: November 2024

This research examines the role of language proficiency in determining academic success among international students. Using a case study approach, the study focuses on international students across several disciplines to assess the impact of language skills on academic performance, participation, and peer integration. Results demonstrate that language proficiency significantly correlates with academic outcomes and engagement levels, emphasizing the need for universities to provide targeted language support services.
The Impact of International Mobility on Intercultural Competency among University Students
Authors: Rafli Arya Priananto  , Inez Galuh Destyara
Published: November 2024

This study examines the influence of international mobility programs on the development of intercultural competency in university students. Through a mixed-methods approach, data was collected from participants across several mobility programs to understand changes in attitudes, awareness, and skills relevant to intercultural communication. Findings indicate that students with international exposure show higher adaptability, cultural sensitivity, and openness compared to their peers. The research suggests that well-structured mobility experiences can significantly enhance students' readiness to work in global settings.
Development of Dribbling Learning Model in Football Games Through Playing Approach for Students of SMP PGRI 2 Cilongok Banyumas Regency in the 2023 Academic Year
Authors: Didi Muhtarom  , Dian Anggi Permadi  , Boby Agustan  , Oman Hadiana  , Ramdhani Rahman
Published: November 2024

Learning football is one of the lessons that seventh grade junior high school students must learn. However, the reality in the field is that there are still many obstacles faced by both teachers and students. One of them is the development of dribbling in playing violin and the lack of game practice in carrying out soccer lessons. In other words, students are only given theory and are not helped with playing practice. For this reason, the problem formulation can be drawn: How is the development of soccer dribbling learning after learning using a playing approach for class VII students at SMP PGRI 2 Cilongok? The aim of this research is to determine the development of dribbling learning in the game of soccer through a playing approach for class VII students at SMP PGRI 2 Cilongok. This research method is to use an experimental method with pretest and posttest. The total population was 25 people with data collection techniques through pre-test and post-test. Data analysis will be carried out using the morality test, homogeneity test and t test. The results of research on playing approaches can have a significant influence on improving dribbling abilities in students at PGRI 2 Cilongok Middle School, Banyumas Regency.
Studi Komparatif Performa Framework Javascript Modern dalam Pengembangan Aplikasi Web
Authors: Octa Selsa Is Anggraeni  , Lilik Sugiarto  , Tinuk Agustin
Published: November 2024

This research conducts a comparative study on the performance of modern JavaScript frameworks - React, Angular, and Vue.js - in the context of web application development. Using an experimental approach, this study measures various performance aspects including rendering time, bundle size, page load time, and memory usage. The research method involves developing web applications using all three frameworks in different scenarios, as well as interviews with experienced developers. Results show that Vue.js excels in rendering speed and memory efficiency, React demonstrates superiority in handling large-scale dynamic updates, while Angular offers a robust structured architecture. This study also reveals the importance of non-technical factors such as learning curve and community support in framework selection. In conclusion, the selection of an optimal framework should consider project-specific needs, team expertise, and long-term organizational goals. This research provides valuable insights for developers and organizations in choosing the appropriate JavaScript framework for their projects.
Aplikasi Pengaduan Tumpukan Sampah dengan Algoritma Analytical Hierarchy Process (AHP) untuk Menentukan Prioritas Layanan
Authors: Ergie Suhendri  , Jaroji Jaroji
Published: November 2024

Waste is a waste product of human activities that continues to increase along with the increase in population, activities, and consumption levels. In Bengkalis Sub-district, Bengkalis Regency, there are many waste accumulation points that have not been handled properly, mainly due to the lack of information about the location of waste accumulation. This causes the Bengkalis Regency Environment and Hygiene Agency (DLHK) to have difficulties in managing waste transportation, even though it is carried out every day. There are still many complaints from people who are outside the waste collection point. To overcome this problem, this research aims to develop a mobile application-based garbage pile complaint application focused on the Bengkalis District area. This application is designed to assist DLHK in monitoring environmental cleanliness more effectively. The Analytical Hierarchy Process (AHP) method is used to determine the priority of handling waste complaints, which will be implemented in a web platform to ensure optimal handling. Application development uses a prototype approach to ensure that the resulting application is in accordance with user needs and expectations. With this application, it is hoped that waste management in Bengkalis Regency will become more efficient and responsive to community complaints.
Pengelompokan Menggunakan Metode Clustering Pada Pola Hidup Pengguna KB
Authors: Dio Fani Prakasa  , Novriyenni Novriyenni  , Lina Arlianan Nur Kadim
Published: November 2024

Healthy lifestyles are habits of doing something, be it food, healthy behavior so as to avoid the disturbance of all kinds of diseases, both physical and non-physical diseases, as well as birth control users must also strive for a healthy lifestyle, such as managing a healthy diet, rest, exercise, eating vegetables and fruits, doing optimal physical activity, not consuming alcohol, and maintaining a healthy body. In this problem, many family planning users do not pay attention to a healthy lifestyle because they think that the family planning tools used have no risk to health, but the use of family planning has side effects on health such as menstruation is not smooth, the body is obese, the body feels warm or feverish, there are blood clots, nausea, bloating, changes in vision, difficulty in getting back to normal, headaches, and others. To be able to attract the attention of the community in implementing a healthy lifestyle for family planning users, it is very necessary to have a system that can help people in changing their unhealthy lifestyle to a healthier one by grouping family planning user data based on variables that have been determined using the clustering method, to group data on healthy lifestyles for family planning users which later the results of this study can be used as input and guidance for a healthy lifestyle for family planning users, so that family planning users are more careful and have a healthy life. Of the 20 data, there are 3 groups, namely group 1 there are 4 data and group 2 there are 4 data and group 3 there are 12 data from the above results it can be seen that in cluster 3 is a group on family planning users based on a lot with a total of 12 data and is located in the contraceptive type group (X) is injectable birth control, and for the lifestyle group (Y), namely Frequent Night Baths and Risk (Z), namely Decreased Bone Strength.
Rancang Bangun Alat Deteksi Kebisingan Perpustakaan dengan Indikator Peringatan Berbasis Internet Of Things (IOT)
Authors: Yourman Doni Siddik  , Akim Manaor Hara Pardede  , Husnul Kahir
Published: November 2024

Noise in libraries can disrupt the concentration and comfort of visitors who are reading or studying. Therefore, a tool is needed to detect noise and automatically issue warnings to maintain silence in the library environment. This research aims to design and develop a noise detection tool in libraries using Internet of Things (IoT) technology. The device consists of a sound sensor that detects noise levels and sends data to a cloud-based server for analysis. When the noise level exceeds a specified threshold, the tool provides warnings through visual indicators and notifications to the library staff. The prototype was tested in a library environment and was able to detect noise accurately and issue real-time alerts. The results showed that the device effectively reduced noise levels and improved the comfort of library visitors. With the implementation of IoT technology, this system can be accessed and monitored remotely, facilitating library management in maintaining a conducive environment.
Analisis Tingkat Kepuasan Penggunaan Aplikasi E- Faktur Pajak dalam Proses Pelaporan Pajak di PT. Anugerah Texindotama
Authors: Shan Putra Elliotman Sarumaha  , Agus Budiyantara
Published: November 2024

This study aims to analyze the level of satisfaction with the use of the tax e-Faktur application in the tax reporting process at PT Anugerah Texindotama. The e-Faktur application is a technological innovation that facilitates electronic tax reporting, which is expected to increase compliance and efficiency in the tax administration process. This research method includes observation, interviews, and distributing questionnaires to 43 respondents who are directly related to the use of the application. Based on the results of the study, it was found that the use of the e- Faktur application has had a positive influence on user satisfaction, with an average satisfaction level of 80.83%, which is categorized as good. Several advantages of the application, such as minimizing the risk of errors and ease of access, also increase user acceptance. However, there are technical constraints that need to be improved to support system optimization. Recommendations for improvement focus on enhancing features and technical training for employees to strengthen the implementation of the e-Faktur application in corporate tax reporting.
Klasifikasi Proses Menentukan Kelayakan Karyawan Baru dengan Metode C4.5 pada Perusahaan Outsourcing PT.SAHABAT DUA PEMUDA
Authors: Theodorus Ikhtiar Hulu
Published: November 2024

Human resources are a company's most dominant asset, because they can play an important role in the company's business development. An outsourcing company is a legal entity and is obliged to comply with business licenses issued by the Central Government. The eligibility process for new employees is supported based on the level of ability and competency determined by the company. The existence of difficulties for companies in determining the eligibility of new employees which makes the reason for the ineffectiveness of the processes carried out by the company at this time, is used as a goal for the authors for the purposes of a study. By using the classification method in a data mining with the C4.5 algorithm (Decision Tree) and a RapidMiner application as a tool in the analysis process carried out to find a factor supporting the process of a new employee eligibility. With the data of 960 applicants used as a sample, this data was taken from 2021-2022. From the data divided into several attributes used, the highest Gain value obtained from these attributes through the results of Test 2 of 0.417152421 which will be used as the root in the process of determining employee eligibility and has the highest accuracy value of 98.44%.
Building the baseline: Assessment of ungulate densities in Amangarh Tiger Reserve, Uttar Pradesh, India
Authors: Reza Sajid , Singh Vijay Pratap , Anwar Meraj , Khan Afifullah
Published: November 2024

We estimated density of ungulate species in the Amangarh Tiger Reserve using line transect distance sampling. Twelve transects were marked and monitored between February and April 2021 resulting in an effort of 108 km. A total of 210 sightings of five species of ungulates were recorded. Spotted deer (Axis axis) was the most frequently recorded species with 80 sightings followed by wild boar (Sus scrofa), sambar (Rusa unicolor), nilgai (Boselaphus tragocamelus) and barking deer (Muntiacus muntjak). The overall density estimate of all five ungulate species was 62.7 (±11 SE) km-2. Spotted deer was the most abundant ungulate (22.95 ±6.5 km-2) followed by sambar (14.26 ±4.2 km-2), wild boar (13.21 ±4.8 km-2) and nilgai (10.56 ±5.06 km-2). This study provides the first comprehensive assessment of ungulate densities in Amangarh Tiger Reserve. The findings establish baseline information for future monitoring and research studies in the area which is an important buffer to Corbett Tiger Reserve and has seen an increase in tiger numbers over the years.
Mind Mapping Solutions to Improve Learning Outcomes in Islamic Education and Natural Sciences
Authors: Sari Julita Permata , Sukandar Warlan , Yumna Yumna , Nurhasanah Nurhasanah , Dahliana Dina , Yolanda Sylvi Aulia , Cahyani Rahmi Indah
Published: November 2024

Mind mapping is a method that can be used in learning natural and social sciences. In fact, this research aims to explain the planning, implementation and improvement of learning outcomes in Islamic education and natural sciences using the mind map method. This research uses classroom action research methods. The research subjects were all 7 class V students consisting of four boys and three girls. Data sources were obtained from teachers and fifth grade students using observation and tests. Data were analyzed through four steps, namely the planning stage, action stage, observation and reflection stage. The results of the research showed that there was an increase in the average student score from cycle I of 66.42, then increased to 85.00 in cycle II and student success was seen to increase from cycle I, 42.85% of students completed, while in cycle II this occurred. enhancement. Complete learning outcomes were 85.71%. For this reason, it is recommended that teachers use the mind map method in science learning and create a comfortable learning atmosphere so that children are interested and do not get bored easily when studying.
Analysis the Concept of Social Justice from Perspective in Tafseer Al-Munir
Authors: Saudiah Paridatus , Yusrial Yusrial , Putri Mirna , Rahmanda Rega , Ardianda Viona , Samsurizal Samsurizal , Ediz M.Hidayat
Published: November 2024

Social justice is an ideal that everyone hopes for. The Quran has ordered to uphold justice in every aspect of life. Therefore, this article will discuss the concept of social justice and then relate it to the Quran so that it can be understood and applied in life. The existence of this research can minimize the occurrence of social conflicts in society, especially those related to justice. This research uses a qualitative method with a thematic analysis approach, the data source obtained from the tafseer Al-Munir, then collects secondary sources by reviewing the sources; from books, theses, journals, articles and papers related to the concept of human justice. Then analyzed thematically based on the explanations contained in the interpretive tafseer of the mufassir. Furthermore, to strengthen the analysis and discussion the author also refers to books, expert opinions and various findings from previous researchers related to this issue and topic. The analysis findings found that justice is not only focused on individual interactions with society, but also interactions between individuals and the Khaliq community and themselves. Damage to justice in one of these elements will create new problems in a person's life. That the concept of justice in the Quran is in accordance with the interpretation interpreted by Wahbah Az-Zuhaili. Apart from that, justice contained in Surah An-Nisa verse 135 regarding the concept of social justice contained in the Quran and the interpretation of Wahbah Az-Zuhaili is upholding justice and working together to help each other, prohibiting taking sides with one party in giving testimony.
METODOLOGIA DE ANÁLISE DO COMPORTAMENTO APLICADO (ABA): INTERVENÇÃO PRECOCE NO DESENVOLVIMENTO DE CRIANÇAS COM TRANSTORNO DO ESPECTRO AUTISTA: REVISÃO DE LITERATURA SISTEMÁTICA
Authors: Guimarães Cordes Maria Fernanda , Guimarães Cordes Maria Eduarda , Puzziello Abduny Jaruche Samira , De Oliveira Rossetto Maria Eduarda , Batista do Nascimento Guilherme , Franco Marinho Cesar Antônio
Published: November 2024

O presente artigo tem como objetivo abordar, caracterizar e identificar a importância da terapia de Análise do Comportamento Aplicado (ABA) no diagnóstico e tratamento precoce em indivíduos com Transtorno do Espectro Autista (TEA). Trata-se de uma revisão de literatura sistemática, partindo de uma consulta bibliográfica eletrônica ocorrida entre os meses de abril e julho de 2024, que compreendeu artigos, monografias e teses, publicadas nas bases de dados, SciELO, BVS, Lilacs, Pubmed, Web of Science, Scopus e nos Periódicos Capes. Foram aceitos trabalhos publicados nas línguas portuguesa, espanhola e inglesa. Para tal, foi realizada uma busca simples, utilizando as palavras-chave: Transtorno do espectro autista; Análise do comportamento aplicada; Intervenção precoce. Ao todo 27 trabalhos foram selecionados para o presente trabalho. Após a identificação do perfil da criança, é elaborado um plano terapêutico singular, onde esquemas individuais são criados com a apresentação inicial de uma indicação ou instrução, oferecendo apoio transitório quando necessário. A metodologia ABA tem por objetivo trabalhar os déficits, através da identificação dos comportamentos desafiadores ou até inabilidades que prejudicam sua vida e suas aprendizagens; reduzir a frequência e intensidade de comportamentos indesejáveis, como por exemplo: agressividade e estereotipias que dificultam o convívio social destes indivíduos, promover o desenvolvimento de habilidades sociais, comunicativas, adaptativas, cognitivas e acadêmicas e promover comportamentos socialmente desejáveis. Embora seja fundamental reconhecer suas limitações e desafios, este trabalho comprovou a eficácia e os benefícios do tratamento através da intervenção ABA por meio da melhora nas habilidades comportamentais, sociais e comunicativas em indivíduos diagnosticados com TEA.
PROGRESSÃO DO DESEMPENHO FUNCIONAL NA DISTROFIA MUSCULAR DE DUCHENNE: REVISÃO INTEGRATIVA
Authors: Alves Vale Fernando , Perez Nogueira Aline Talita , Da Ponte Melo Adersiara , Da Cunha Lima Jackson Felipe , Callil Voos Mariana , Caromano Fátima Aparecida , Dos Santos Filho Carlos Alberto
Published: November 2024

A distrofia muscular de Duchenne (DMD) é um distúrbio genético que consiste na mais grave e a mais comum das distrofias. As disfunções motoras decorrentes da alteração do gene Xp21 surgem nos primeiros anos de vida, com evolução progressiva e rápida, que afeta gradualmente a força muscular e a capacidade funcional. O presente estudo visou revisar a literatura e descrever a progressão da função motora na DMD em tarefas funcionais e analisar os principais testes utilizados para mensurar a progressão da função motora utilizados nos estudos. Realizou-se uma revisão de literatura dos últimos 10 anos (2014 – 2024) nas bases de dados PubMed/MEDLINE, SCOPUS e SCIELO utilizando-se os termos "Duchenne muscular dystrophy" AND "motor function". Após filtragem por título, foram selecionados 31 estudos, que foram lidos na íntegra.É interessante observar que estudos mais antigos utilizaram a medida de função motora (MFM), enquanto estudos mais recentes utilizaram a North Star Ambulatory Assessment (NSAA). A maioria dos estudos avaliaram deambuladores do que cadeirantes e mais estudos avaliaram tarefas envolvendo membros inferiores do que membros superiores. O presente estudo descreveu muitas estratégias para avaliação da progressão da DMD. A corticoterapia e novas terapias genéticas estão mudando a história natural da doença e protocolos precisos de avaliação são essenciais para mensuração desses efeitos. Testes como NSAA, Teste de Caminhada dos 6 minutos, Teste de Caminhada dos 10 metros, Testes cronometrados de função e MFM têm sido muito utilizados e se mostram eficientes para avaliação e seguimento dos pacientes com DMD.