Reviewerly/exHarmony huggingface dataset:
KFREAIN: Design of A Kernel-Level Forensic Layer for Improving Real-Time Evidence Analysis Performance in IoT Networks

An exponential increase in number of attacks in IoT Networks makes it essential to formulate attack-level mitigation strategies. This paper proposes design of a scalable Kernel-level Forensic layer that assists in improving real-time evidence analysis performance to assist in efficient pattern analysis of the collected data samples. It has an inbuilt Temporal Blockchain Cache (TBC), which is refreshed after analysis of every set of evidences. The model uses a multidomain feature extraction engine that combines lightweight Fourier, Wavelet, Convolutional, Gabor, and Cosine feature sets that are selected by a stochastic Bacterial Foraging Optimizer (BFO) for identification of high variance features. The selected features are processed by an ensemble learning (EL) classifier that use low complexity classifiers reducing the energy consumption during analysis by 8.3% when compared with application-level forensic models. The model also showcased 3.5% higher accuracy, 4.9% higher precision, and 4.3% higher recall of attack-event identification when compared with standard forensic techniques. Due to kernel-level integration, the model is also able to reduce the delay needed for forensic analysis on different network types by 9.5%, thus making it useful for real-time &amp; heterogenous network scenarios.
Measuring Quality of E-learning Websites Using WebQual 4.0 Method in Higher Education (Case Study : Institute Technology and Science Mandala)

The new normal era due to the Covid-19 pandemic has an impact on various sectors, one of which is the education sector. The Covid-19 pandemic has forced tertiary institutions to innovate by utilizing information technology in implementing higher education tridharma. The Mandala Institute of Technology and Science utilizes the LMS e-learning platform as an online learning medium. This research was conducted to measure the quality of e-learning using Webqual 4.0 approach to improve and maintain service quality based on user assumptions. The Webqual 4.0 method is an instrument used to assess website quality based on the end user's perspective of 3 (three) dimensions, namely usability quality, information quality, and service interaction quality. The results of this study indicate that usability quality, information quality and service interaction quality have a significant and positive effect on user satisfaction
Expert System For Diagnosing Alzheimer's Using Certainty Factor Method

This expert system for diagnosing Alzheimer's disease is a computer-based stem system used as a tool to diagnose Alzheimer's disease based on a dynamic knowledge base. This knowledge base contains knowledge obtained from various sources including from the experience of experts who are proficient in their fields and also books related to diagnosis of Alzheimer's disease and then collected into a database system needed for making conclusions. In this system, the certainty factor method will be used using a forward chaining inference engine. The purpose of making this root stem p can be useful for many people and can know clearly about Alzheimer's disease from its symptoms and solutions, which will be displayed in the form of a website using PHP programming with MySQL database.&#x0D;
Optimizing Forecasting of Dow Jones Stock Index in New York amid Uncertain Global Conditions in 2023: A Combined Approach of ARIMA and Machine Learning Models

This research aims to optimize the forecasting of the Dow Jones stock index in New York amid the uncertain global conditions of 2023 using a combined approach of ARIMA and Machine Learning models. This research aims to analyze the movement of the Dow Jones stock index during the uncertainty of the global economic conditions in 2023. The study used a quantitative approach with secondary daily data sourced from yahoo.finance website from january 2020 to may 2023. The current global uncertainty poses challenges to accurate forecasting, and this combined approach offers an effective solution. In this approach, the ARIMA model is employed to capture trends and seasonal patterns in historical data that exhibit stationarity, while the Machine Learning model is used to address more complex patterns and interactions among variables that cannot be handled by ARIMA. The uncertain data of the Dow Jones stock index in New York undergoes preprocessing stages using Machine Learning techniques such as data cleaning, data transformation, feature extraction, and data labeling. The results of the research demonstrate that the combined approach of ARIMA and Machine Learning provides more accurate and reliable forecasts. The integration of the ARIMA and Machine Learning models enables the capture of complex patterns and relationships in the data, resulting in improved forecasting accuracy and valuable insights for investors and market participants in navigating uncertain global conditions. In conclusion, the combined approach of ARIMA and Machine Learning is an effective strategy for optimizing the forecasting of the Dow Jones stock index in New York during uncertain global conditions in 2023. This research contributes to the field of financial forecasting by expanding the understanding of the use of combined approaches to enhance forecasting accuracy and support better decision-making amidst global uncertainty.
Modelling and analysis of rooftop PV as an energy optimization of flat roof and gable roof mounting system

Photovoltaic (PV) systems are designed for both communal and self-installation. PV systems are intended for both communal and standalone installations. Installation is required not only in industry and commerce, but also in the growth of energy potential at Universitas Jenderal Achmad Yani. The focus of this research is rooftop PV modelling and analysis at Universitas Jenderal Achmad Yani. Because the ground mounting system could not be done due to limited land, a rooftop solar power-producing system was created. Data gathering is done as part of unique research that takes into account numerous technological criteria for efficiency. System analysis conducted by modelling and simulation, which will make use of a variety of tools linked to this PV system. Data was gathered from similar studies while accounting for numerous technological variables such as modelling and efficiency. K2Base system was used to model flat roofs with concrete roof types and gable roofs with tile roof types. The mounting type, wind load, truss load, and ballast were all taken into account in the design. This article also calculates PV panel configurations and component capacities. There are many different panels that can be constructed from each model. With a maximum roof area of 837.52 m2, 33 to 350 PV panels may be used. The number of inverters is changed to provide outputs of 10 kW, 25 kW, and 50 kW based on the calculations' findings. With differences in autonomous days, the number of batteries obtained has an average of more than 200 batteries.
Implementation and Testing System Information Academic (SIAKAD) In New University XYZ

Technological developments that are increasing each year rapidly in various fields have contributed to encouraging tertiary institutions to remain superior and carry out all fields quickly and efficiently by utilizing digital technology. Indicators of technological development in tertiary institutions have adequate information technology infrastructure. One of the tertiary information technology infrastructures has an academic information system governance (SIAKAD) in managing the educational management process at the tertiary institution. Universities that have just been established generally do not have SIAKAD in their academic management process, one of which is XYZ University. XYZ University in carrying out the process of academic activities is still done manually resulting in less effective and efficient activity processes. Then the condition of the COVID-19 pandemic requires students to do remote or online learning. Therefore the author makes SIAKAD which will be tested on users so that the system built can suit their needs. Of the 15 respondents, a questionnaire test was carried out which resulted in a user satisfaction value of 76.83% which showed reasonable satisfaction by the user. Based on the results of the test, it was found that the use of SIAKAD in tertiary institutions is very helpful in the academic process
Digital Currencies and The Monetary System: Review and Issues

This paper is a review article on digitalization, generating issues from the discourse. The place of digital currencies in the contemporary world of banking and commerce was discussed, and so were their attractiveness and variants in the emergent trend. The evolution and the conditions for the effectiveness of digitalization, differentiated policy goals of the various central bank digital currency projects as well as the regulatory and supervisory authorities were articulated and highlighted. Three competing models of central bank digital currency concerning the allocation of the functions of issuance, the validity of transactions, ledger update, user interface, user data and customer service were identified and distinguished by the different involvement of the central bank, commercial banks and the private sector in the functions identified. The choice of optimal technology underpinning the central bank digital currency was justified. The characteristics and functions of the various central bank digital currency designs were identified and discussed. Actual and potential challenges of the various central bank digital currencies gave insights into the present and possibly the future operating procedure of the central bank digital currencies. Perceived potential risks of central bank digital currency on commercial banks, financial stability and monetary policy as well as the likely combating measures would shape the future of the monetary system. However, the drivers of the reserve currency status would most likely remain unchanged. Central bank digital currency could offer the opportunity to address the challenges of cross-border payments.
DETERMINANTS OF MANAGEMENT EFFECTIVENESS OF SCHOOL OPERATIONAL ASSISTANCE FUNDS (BANTUAN OPERASIONAL SEKOLAH/BOS) AT SDN KALIGLAGAH 04

This study aims to analyze the effect of applying the principles of accountability, transparency, and stakeholder’s participation on the effectiveness of the management of School Operational Assistance Funds (BOS/Bantuan Operasional Sekolah) at SDN Kaliglagah 04 Sumberbaru District. The method used in this research is by distributing questionnaires. We used 80 sample in this study, they were school committee, teachers and parents. The sampling technique was carried out by simple random sampling technique. The data analysis method used is Multiple Linear Regression. The results showed that transparency had a partial effect on the effectiveness management of the School Operational Assistance Funds (BOS). While the application of the principle of accountability and stakeholder participation does not partially affect the effectiveness of the management of School Operational Assistance Funds (BOS). Simultaneously the application of the principles of accountability, transparency and stakeholder participation affect the effectiveness of the management of School Operational Assistance Funds (BOS).
Pembuatan dan Pemanfaatan Dashboard Data Rekam Medis Sebagai Alat Bantu Sistem Pendukung Keputusan

The implementation of a hospital management information system at the 'Aisyiyah Padang public hospital opens opportunities for academics to conduct research and experiments. The amount of data stored in the information system database can be used as an alternative for decision making by hospital management, including medical record data for patients who go to the hospital. Existing medical record data can be summarized and presented visually in the form of a dashboard according to the needs of the hospital. Dashboard can provide an overview to management to determine future policies or as a decision support system. This study aims to create a dashboard that can be used as a decision support system. This type of research is descriptive with the subject of medical record data in the database. From the research that has been done, it is found that the number of outpatient patients in 2021 is 23,635 patients. Of this number, the 3 insurers for the most patients were the Badan Penyelenggara Jaminan Sosial (BPJS) with 19,834 patients, Umum with 3,551 patients and Smile Train with 69 patients. For the 3 doctors who treat the most patients, Dr. Lisa Oktamuva, Sp.PD as many as 3284 patients, dr. Yanasta Moendanoe, Sp.OG with 3112 patients, and drg. Harfindo Nismal, Sp.BM as many as 2351 patients. From the research that has been done, it can be concluded that the designed dashboard is still simple and incomplete. From the dashboard it was also found that the person who is responsible for the most patients is BPJS and the doctor who serves the most patients is Dr. Lisa Oktamuva, Sp.PD.)
Predicting Academic Staff Intention to Stay in Tanzanian Universities Using Job Embeddedness Model: Smart PLS Approach

Turnover is one of the reasons for the inadequacy of academic staff in Tanzanian universities as in many other African countries. This study examined the relationship between job embeddedness and academic staff Intention to Stay in Tanzanian Universities, as a key step towards combating the problem of turnover. A survey of 314 academic staff from selected public and private universities in Tanzania was conducted and Smart PLS Structural Equation Modeling was used in examining the relationship. Further, PLS-MGA was conducted to examine whether a significant difference exists in the influence of job embeddedness on the intention to stay among academic staff in Public and Private Universities. The findings indicated that Job Embeddedness sufficiently predicted academic staff Intention to Stay in Tanzania's universities, with organization fit and organization sacrifice exerting main influences. The relationships varied between public and private universities with stronger relationships in private than in public universities. It was concluded that job embeddedness is an important predictor of intention to stay, and its inclusion in retention models may improve retention of academic staff in Tanzania's universities. Private Universities in Tanzania may especially find more affirmative results in terms of retention, by improving the fit between their academic members of staff and their universities.Keywords: Job embeddedness, Academic staff, Intention to stay, Tanzaniaâ€™s universities.Â
Metadata Scraping Using Programmable Customized Search Engine

The World Wide Web (WWW) is a vast repository of knowledge, including intellectual, social, financial, and security-related data. Online information is typically accessed for instructional purposes. On the internet, information is accessible in a variety of formats and access interfaces. Because of this, indexing or semantic processing of the data via websites may be difficult. The method that seeks to resolve this issue is web data scraping. Unstructured web data can be converted into structured data using web data scraping so that it can be stored and examined in a central local database or spreadsheet. This paper offers a metadata scraping using a programmable Customized Search Engine (CSE) system, which can extract metadata from web pages (HTML pages) in the Google database and save it in an XML format for later analysis and retrieval. Documents that contain metadata are a relatively recent phenomenon on the web and increase the likelihood that users will find the information they need. Index Terms— Programmable (CSE), JSON API, API key, metadata scraping.
Challenges of Engineering Education in Digital Intelligence Era

The rise of the digital intelligence era signifies a new paradigm of digital technology and intelligent applications, bringing fresh opportunities and challenges to engineering practice. This paper focuses on the analysis of nine key challenges, encompassing the enhancement of complex engineering problem-solving abilities, the shortening of knowledge half-life, coping with the competition from intelligent machines, the role of engineers in industrial digitalization, the dual transformation of digitization and sustainability, effective engineering practice training, attracting outstanding young talent, digital transformation of engineering education, and the refinement of quality assessment standards for engineering education. These challenges reflect the complexity and diversity of engineering education in the digital intelligence era, requiring engineering education institutions to continuously adjust their curricula and teaching methods to cultivate engineers with comprehensive competencies and interdisciplinary skills. At the same time, the digital intelligence era also brings new opportunities for engineering education, including the application of digital technologies, emphasis on interdisciplinary learning, and the importance of sustainability. Effectively addressing these challenges will contribute to improving the quality of engineering education and provide critical support for the sustainable development of society and the environment. The future of engineering education in the digital intelligence era is promising, but it requires us to confront challenges to actively promote progress and innovation in engineering.
Bert Based Named Entity Recognition for the Albanian Language

In this paper, we explore the application of the Bidirectional Encoder Representations from Transformers (BERT) model for Named Entity Recognition (NER) in the Albanian language. Despite the success of BERT in various NLP tasks across numerous languages, Albanian remains under-represented. Our approach leverages a transfer learning strategy with multilingual BERT, fine-tuned on a newly created, comprehensive Albanian language corpus. The corpus includes texts from various domains, thereby facilitating the identification of a broad range of named entities. We report on the challenges faced during corpus creation, model fine-tuning, and testing phases, such as dealing with dialectal variations and lack of existing resources for the Albanian language. This research not only contributes to the advancement of NER systems for low-resource languages, but also provides a robust foundation for further advancements in Albanian language processing.&#x0D; &#x0D; Received: 21 September 2023 / Accepted: 29 October 2023 / Published: 23 November 2023
A Review of Face Detection Methods Based on Feature Approach

Face detection technology is the first and essential step for facial-based analysis algorithms such as face recognition, face feature extraction, face alignment, face enhancement, and face parsing. That is besides serving other applications related to human intention and act analysis such as facial expression recognition, gender recognition, and age classification. Face detection is used to detect faces in digital images. It is a special case of object detection and can be used in many areas such as biometrics, security, law enforcement, entertainment, and personal safety. There are various methods proposed in the field of face detection, and they all compete to make it more advanced and accurate. These methods belong to two main approaches; feature-based approach and image-based approach. This paper reviews the face detection methods that belong to the feature-based approach. Moreover, their work concepts, strengths, and limitations are mentioned. This paper concentrates on the feature-based approach due to its simplicity and high applicability in real-time detection compared to the image-based approach. Index Terms— Face Detection Methods, Feature-Based Approach, Viola-Jones Algorithm, Deformable Template Matching.
ANALISIS PENGARUH PENERAPAN METODE LISTENING DALAM UJIAN SEKOLAH TERHADAP PENINGKATAN KEMAMPUAN MENDENGARKAN DAN PEMAHAMAN MATERI SISWA SMA

The purpose of this study was to analyze the effect of applying the listening method in school exams to improving high school students' listening skills and material comprehension. The research method used is a literature study that involves searching and analyzing literature related to previous research. This study aims to collect information and findings from previous studies that have discussed the use of the listening method in school exams and its impact on high school students' listening skills and material comprehension. The results of this study indicate that the application of the listening method in school exams has a significant positive effect on increasing high school students' listening skills and material comprehension. Based on the analysis of the literature, the listening method can help students improve their listening skills better, improve understanding of subject matter, and develop critical thinking skills. In addition, the use of the listening method in school exams can also motivate students to be actively involved in the learning process and improve information retention. Keywords: listening method, school exams, listening skills, understanding of the material
Exploring Teachers’ Perspectives on Slow Learners in the Science Classroom

Background: Educators encounter a significant challenge when it comes to instructing students with slower learning abilities in the field of science classroom. Students with limited cognitive abilities are typically identified as slow learners. The objective of this study was to examine the attitudes of teachers towards students with slower learning abilities in science classrooms and analyze their perceptions of these students. Methods: The study has been conducted by selecting a sample of 51 science teachers who teach at basic and secondary school levels. A representative sample of 51 teachers, who teach at basic and secondary level, were selected from 6 public schools in Chandragiri Municipality, Kathmandu district and 10 public schools in Ratnanagar Municipality, Chitwan district. The required data were gathered using a survey that employed three-point Likert-type questionnaires. The data were analyzed using frequency and percentage analysis. Results: The findings indicate that the science teachers exhibited a positive attitude towards students who have a slower learning pace. Conclusions: It is recommended to prioritize the enhancement of their science learning experience.
Biobank as a legal category

The development of medical technologies increases the need for legal regulation of relations on the formation of biobanks. The comparative legal method and the formal legal method were used. Currently, the term biobank is used to denote both the totality of objects of rights and to denote the entity carrying out the storage. The conclusion is made about the need for additional regulation of the concept of biobank. To protect the rights and legitimate interests of the patient, it is necessary to take into account his consent or lack of consent both for the removal of cells and other biological materials, and for their storage, transportation, cryopreservation. The conditions of consent may provide for the destruction of biological material upon the occurrence of certain conditions, for example, in the event of the death of a patient. Consent to the processing of personal data should be obtained separately. For more complete regulation, it is necessary to determine the features of the legal personality of organizations engaged in professional activities for the storage of biological samples and related data. It should be recognized that it is expedient to preserve the rules on licensing the activities of such organizations.