Reviewerly/exHarmony huggingface dataset:
Electronic document management system for local area network-based organizations

The paper discusses the design and development of an electronic document management system (EDMS) that prepares documents for sharing and information dissemination. EDMS has to do with capturing, storing, indexing, retrieval, and disposal of documents. The electronic document management system process starts by converting paper document into digital record to efficiently store and organize document in standardized file structure and format, promoting a paper waste reduction in reproducing the document. The EDMS provided an easier way of sharing information with different stakeholders and securing documents according to standardized compliance rules. The developed system has also improved the accessing of vital documents by users since there is real-time information distribution of information and easy searching and retrieving of needed documents.
Cybersecurity in health sector: a systematic review of the literature

Currently, health centers are being affected by various cyberattacks putting at risk the confidential information of their patients and the organization because they do not have a plan or tools to help them mitigate these cyberattacks, which is important to know what measures to take to protect the privacy of personal data. The present work was carried out under a systematic literature review, which aims to show the importance of cybersecurity in the health sector knowing which tools are the most used and efficient to prevent a cyberattack. A systematic review of 301 articles was carried out, 79 of which are aligned with the objective set, fulfilling the inclusion and exclusion criteria. The search for information was carried out in the Scopus and Dimensions databases. The analysis carried out has resulted in good information that was compiled for the development of this topic, being favorable thanks to the different research of different authors.
Comparative evaluation of data mining algorithms in breast cancer

&lt;span lang="EN-US"&gt;Unchecked breast cell growth is one of the leading causes of death in women globally and is the cause of breast cancer. The only method to avoid breast cancer-related deaths is through early detection and treatment. The proper classification of malignancies is one of the most significant challenges in the medical industry. Due to their high precision and accuracy, machine learning techniques are extensively employed for identifying and classifying various forms of cancer. The authors of this review studied numerous data mining algorithms and implemented them such that clinicians might use them to accurately detect cancer cells early on. This article introduces several techniques, including support vector machine (SVM), K star (K*) classifier, additive regression (AR), back propagation (BP) neural network, and Bagging. These algorithms are trained using a set of data that contains tumor parameters from breast cancer patients. Comparing the results, the authors found that SVM and Bagging had the highest precision and accuracy, respectively. Also assess the number of studies that provide machine learning techniques for breast cancer detection.&lt;/span&gt;
Multi-layer perceptron neural network mobile robot navigator in unknown environment

&lt;span lang="EN-US"&gt;Recently, navigation in an unknown environment without hitting obstacles was considered a big challenge faced by researchers. The difficulty in finding a good mathematical model for the different systems is deciding to use artificial intelligent controllers to control the mobile robot movement. In this paper, designing two multi-layer-perceptron neural networks (MLP-NN) was done to control the movement of mobile robots in an unknown environment. The first MLP-NN is to control the linear velocity on the x-axis and angular velocity of the robot’s movement while the other MLP-NN is designed to avoid the static and dynamic obstacles faced by the robot while navigating in an unknown environment. The results show each controller's advantages in performing navigation tasks and avoiding obstacles in different environments.&lt;/span&gt;
Machine learning based approach for detection of fake banknotes using support vector machine

Currency counterfeiting is a significant offense that has an impact on a nation's finances. Due to the enormous progress in printing technology, it is now quite simple to create fake currency that resembles real currency in both appearance and texture, making it nearly difficult to manually tell them apart. The suggested approach will be helpful in identifying fake currency in financial systems. Because of the rise of fake currency in the market, numerous false note detecting techniques are available globally to address this issue, however the most of them rely on expensive technology. In this paper, we'll introduce a revolutionary way for separating fake banknotes from real ones using the support vector machine (SVM) approach. To categorize bank notes as authentic or counterfeit utilizing the data retrieved from the photos of the bank notes, SVM performs better overall and is more effective, particularly when it comes to pattern categorization. Finally, the results of our experiment will demonstrate that the suggested algorithm does really yield extremely good performance.
FunAR-furniture augmented reality application to support practical laboratory experiments in interior design education

Practical learning in the laboratory has been limited due to the COVID-19 pandemic. Conventional education must adapt to increasingly digital technological developments. The design of interactive learning media with augmented reality technology can be a solution and support the previous conventional learning. FunAR is a Furniture Augmented Reality Application developed using the analysis, design, development, implementation, and evaluation (ADDIE) method consisting of ADDIE. In its implementation, the FunAR application will provide basic information about existing equipment in Lab Furniture, accompanied by 2D images, and augmented reality technology that creates 3D objects from each piece of equipment in Lab Furniture. From 15 student respondents, the results reveal that distance, angle, and device specifications significantly impact camera marker reading. &lt;br /&gt; A distance of 20 cm to 80 cm and an angle of 25° to 100° can display 3D objects. Likewise, the camera’s ability to process reading markers is better on smartphones with better hardware specifications. The results of the respondents showed that 80% of respondents were satisfied with the FunAR application.
PENGGUNAAN MEDIA FLASHCARD UNTUK MENINGKATKAN KEMAMPUAN MEMBACA DAN MENULIS MATA PELAJARAN BAHASA INDONESIA DI KELAS II SDN KEPUH 1 KABUPATEN KEDIRI

The background of this research was that the ability to read and write was the difficult thing for the second grade students at SDN Kepuh 1, Kediri Regency. It turned out that 75% of students scored less than 70 out of a total of 19 students. This was caused by many students like to talk to themselves, sleepy and lack of enthusiasm. This study aims: 1) To find out the steps for using flashcard media in Indonesian Language Subjects. 2) To find out whether there is an increase in reading and writing skills using flashcard media. 3) To find out whether flashcard media can foster student learning activeness in learning Indonesian Subject for the second grade students. The results showed an increase in each cycle. In the pre-cycle there were 8 students or 42%, that showed improvement in cycle I became 12 students or 63% and at the end of cycle II there were 17 students or 89% that also showed an improvement. Likewise, students' writing abilities increased in each cycle where in the pre-cycle the completeness reached 9 students or 47%, it increased in cycle I there were 13 students or 69%, and in cycle II increased by 17 students or 90%. Thus it can be concluded that there was an increase in the reading and writing skills of second grade students at SDN Kepuh 1, Kediri Regency by using flashcard media that it can be seen by the students' reading abilities which have increased in each cycle.
A Localized Neural Network with Dependent Data: Estimation and Inference

In this paper, we propose a localized neural network (LNN) model and then develop the LNN based estimation and inferential procedures for dependent data in both cases with quantitative/qualitative outcomes. We explore the use of identification restrictions from a nonparametric regression perspective, and establish an estimation theory for the LNN setting under a set of mild conditions. The asymptotic distributions are derived accordingly, and we show that LNN automatically eliminates the dependence of data when calculating the asymptotic variances. The finding is important, as one can easily use different types of wild bootstrap methods to obtain valid inference practically. In particular, for quantitative outcomes, the proposed LNN approach yields closed-form expressions for the estimates of some key estimators of interest. Last but not least, we examine our theoretical findings through extensive numerical studies.
Pengembangan Media Pembelajaran Berbasis Animaker dalam Pembelajaran Daring Sebagai Sumber Belajar pada Teks Iklan, Slogan, Atau Poster pada Siswa SMP Kelas VIII

This study aims to describe the development of Animaker-based learning media and describe the results of the feasibility of Animaker-based media products in learning advertising texts, slogans, and posters for VIII grade junior high school students. This research used Research and Development (R &amp; D) method which referred to Borg &amp; Gall’s design. Data collection techniques in this study use interviews and observation. The results obtained from Animaker-based learning media produce a product in the form of a learning video which is divided into two parts. The results of this study indicated that the feasibility based on learning and content aspects obtained an average percentage of 85,7% and 93,75% with very decent criteria. The feasibility of the product that has been validated by media experts in the aspect of appearance and the role of the media has the same average percentage of 87.5% and both are very decent criteria.
PENGEMBANGAN INSTRUMEN TES PILIHAN GANDA BERBASIS HOTS TEKS PUISI KELAS VIII

The problem in this research is how to develop multiple choice test instruments based on higher order thinking skills in learning poetry texts for class VIII. The purpose of this study was to make a multiple choice test instrument product based on higher order thinking skills in learning poetry texts for class VIII. This research uses research and development (rnd). The results showed the creation of a multiple-choice test instrument product based on higher order thinking skills that had been validated. The validation was carried out by lecturers and experts/practitioners to test the feasibility of the product. The results of the validation of the practitioner or peer test and the expert or expert test that has been carried out using an instrument in the form of a questionnaire. The value obtained from the practitioner or colleague is 3.72 (good) and the value obtained from the expert or expert is 3.6 (good)
Interactive Games, E-books, and Methods to Support Arabic Language Learning Upper Secondary School State Islamic Institute

Arabic lessons taught by teachers in class use various teaching media that are designed to be as attractive as possible. One of these media is an interactive game and e-book and then the teaching method that will be used by researchers in learning using this media is the direct learning method. The purpose of this study was to find out how important interactive game media, e-books and methods that support learning Arabic for MTsM students in Solok City. The research method used in this study is the quantitative method, the researcher will examine how important the media and teaching methods are. The results of the study prove that interactive game media, e-books and the methods used can affect students' enthusiasm and understanding of the material being taught. In this study it can be seen that the use of interactive games, e-books with direct learning methods can influence students' enthusiasm and understanding of the material being taught and can be applied to other lessons.
Increase Elementary School Students' Interest in Learning During Covid-19 with Teaching Materials Using E-Books

The purpose of this research is to increase students' interest in learning in elementary schools during Covid-19 with e-book teaching materials by utilizing technology in learning media, especially using digital books (e-books) through computer intermediaries, laptops or smartphones. Since the existence of Covid-19, the level of interest in learning from students has been very minimal, because educators are less creative in using technology when carrying out the learning process, so that students are less interested in doing learning, by utilizing technology published in digital form can be used by students to facilitate students in learning and increase student interest in learning during the Covid-19 pandemic by displaying information in the form of text, images, audio, video, animation, narration, music, and other multimedia. The method used in this study is a quantitative research method, in which this method researchers can collect data by means of in-depth interviews using the Google form. Because of that, with the e-book media, researchers hope that students' interest in learning can increase even though learning is still done online
Optimal quantum network decongestion strategies

Abstract This study clarifies the problem of decongestion in quantum networks, with a specific focus on the crucial task of entanglement distribution. Entangled particles are a valuable resource in quantum networks, as they are used for most quantum protocols. As such, ensuring that nodes in quantum networks are supplied with entanglement efficiently is mandatory. Many times, parts of a quantum network are contested by multiple entanglement resupply processes and the distribution of entanglement becomes a challenge. The most common network intersection topology, the star-shape and it’s various generalizations, are analyzed, and effective decongestion strategies, in order to achieve optimal entanglement distribution, are proposed. The analysis is comprehensive and relies on rigorous mathematical calculations which aids in selecting the most appropriate strategy for different scenarios optimally.
A Survey on Text Mining - Techniques, Application

Text mining, also known as text data mining or text analytics, is a field of study that focuses on extracting meaningful information and knowledge from textual data. The rapid advancement of digital data acquisition techniques has resulted in an unprecedented volume of data. In fact, over 80 percent of the data generated today comprises unstructured or semi-structured formats. Extracting meaningful patterns and trends from such massive amounts of text data poses a significant challenge. Text mining addresses this challenge by extracting valuable and nontrivial patterns from vast collections of text documents. Various techniques and tools are available for mining text documents and uncovering valuable information to inform decision-making and future processing. Selecting the appropriate text mining technique is crucial as it can significantly enhance the speed and efficiency of retrieving valuable information, reducing the time and effort required. This paper provides a concise analysis and discussion of text mining techniques and their applications. As technology continues to advance, the availability of digital data continues to increase. A substantial portion, approximately 85 percent, of this data exists in unstructured textual form. Consequently, it has become imperative to develop improved techniques and algorithms to effectively extract useful and interesting information from these vast amounts of textual data. This has resulted in the emergence of information extraction and text mining as popular research areas dedicated to uncovering valuable and necessary information from textual data.
PENGUNAAN MEDIA COLORED STICK UNTUK MENINGKATKAN KEMAMPUAN OPERASI HITUNG PENJUMLAHAN DAN PENGURANGAN PADA PELAJARAN MATEMATIKA PESERTA DIDIK KELAS I SDN GABUSBANARAN

This study aims to improve the ability of students in the learning process, namely the use of colored stick media to improve the ability to calculate addition and subtraction operations in mathematics lessons for first grade students at SDN Gabusbanaran. The results obtained in the use of this media are growing rapidly so that students can master the material so that the changes obtained are 100%. And this research uses classroom action research (PTK) techniques.
A comparative study of red cell histogram along with CBC parameters and peripheral blood smear in various anemias

: The red blood cell (RBC) parameters generated by cell counters can aid in morphological categorization of anemia, the significance of microscopic analysis of peripheral blood smears (PBSs) cannot be overlooked when it comes to interpreting the underlying cause of anemia. Therefore, both RBC parameters and microscopic examination of PBSs are essential for a comprehensive assessment of anemia. This study aimed to evaluate and compare the results obtained through two different methods: examination of peripheral blood smears (PBS) and automated cell counter generated parameters. The objective was to identify any differences or similarities in the diagnostic outcomes produced by each method. Over the course of one year, from December 2020 to November 2021, a hospital-based, prospective study was conducted. The study aimed to evaluate and compare the PBS findings and RBC parameters and histograms generated by a cell counter in 1000 anemic patients. In a sample of 1000 cases, we compared the typing of anemia using an automated analyzer and peripheral smear examination. Out of these cases, 690 showed consistent typing results between the two methods, while 310 showed discordant typing. The automated analyzer diagnosed majority of cases 70.1% as microcytic anemia and Normocytic, dimorphic, and macrocytic cases were found in 13.5%, 7.8%, and 4.3% of cases, respectively. Additionally, a normal histogram was observed in 17.6% of cases. We have concluded that while the automated analyzer is useful in reducing the overall workload through its graphical representation of anemia typing, it should always be confirmed through microscopy. The automated analyzer is a helpful tool, it should not be relied upon solely for accurate anemia typing. Microscopy remains an essential method for confirming the results of automated analysis.
Trends and Techniques used in Tourist Recommender System : A Review

Traveling to other locations for pleasure, business, or other reasons is called tourism. In every sort of recommender system, there are a certain amount of users and items. Creating a recommendation systems is made more difficult by the abundance of information available online and the high volume of website visits. A recommender system pulls the user's preferences or interests from relevant data sets to reduce information overload. This calls for the development of a new recommended system that will deliver higher-quality recommendations for massive data sets. To solve these kinds of problems, we have found several approaches for making recommendations, including three different types: content-based filtering, collaborative filtering, and hybrid filtering. With each type of recommender system, this research also analyses several algorithms. The main aim of this paper is to review several trends and techniques currently being used in tourist recommender systems.
Exploring the Generality of Norms in Multi-Agent Systems

Norms are useful tools to regulate autonomous agents, and their generality is the focus of this paper. The generality of norms refers to the extent of behaviors the norms are capable of regulating. While very specific norms tend to be inefficient to avoid undesirable behaviors (since they are rarely activated), very general norms tend to limit excessively the options of the agents (since they are activated too often) hindering them to achieve the system goal. Therefore, a norm that efficiently regulates the agents should have a balanced generality, being neither too specific nor too general. Therefore, we consider that exploring the generality of norms is a fundamental key to obtaining efficient norms. However, the evaluation of their generality usually considers every behavior they regulate. Since it is likely an unfeasible task, in this paper, we investigate alternatives to estimate the norms generality from their syntactic characteristics. Based on these characteristics, we obtain different sequences of norms that vary, approximately, from the most specific to the most general. We assume thus that norms with a balanced generality are more easily found considering these orderings. Therefore, it is relevant to understand the impact of the syntactical characteristics in ordering the norms. In this context, we found out how different alternatives organize the norms space. This result is particularly useful for the development of algorithms for searching efficient norms that, through different strategies, may exploit how norms space is arranged and may be pruned.
MENINGKATKAN HASIL BELAJAR PESERTA DIDIK DALAM MATA PELAJARAN IPAS (PENGETAHUAN ALAM) PADA TEMA PERUBAHAN BENTUK ENERGI DENGAN MENGGUNAKAN MEDIA PEMBELAJARAN GENERATOR SEDERHANA DI SDN PUNTEN 01 BATU

&#x0D; This study aims to be able to determine the level of achievement of students' understanding of the subject of Natural Sciences (IPAS) after applying the learning method using simple generator learning media and to find out the effect of learning methods using simple generator learning media on increasing student understanding. This research took place at SDN Punten 01 Batu which was carried out from October to November 2022/2023 odd semester with the research subjects being students of class IV (Four). The results of this study concluded that the learning method using simple generator learning media can increase students' understanding which can be seen from the learning completeness of students in each cycle. The stage in cycle I got a presentation result of 36.36% while the stage in cycle II got a result of 81,82% so that the application of the learning method using simple generator learning media affects students' understanding which can increase students' learning motivation. Learning using this method has a very positive value in improving student learning achievement.
Analisis Tingkat Kesehatan Bank Syariah di Indonesia Menggunakan Metode Fuzzy Inference System Takagi-Sugeno-Kang

This study aims to measure the level of accuracy of the health of Islamic banks in Indonesia using the RGEC (Risk Profile, Good Corporate Governance, Earning, and Capital) method and the Takagi-Sugeno-Kang (TSK) Fuzzy Inference System. Fuzzy Inference System is an Artificial Intelligence method that can measure the level of accuracy well. The application of the Takagi-Sugeno-Kang Fuzzy Inference System in assessing the health level of 12 Islamic banks in Indonesia begins by dividing the data into 40 data for training and 20 for testing. The inputs used are NPL, LDR, ROA, ROE, NIM and CAR. The level of accuracy obtained in the fuzzy system for training data for 2014, 2015, 2016, 2017 and 2018 is 95.4%, 97.7%, 98.2%, 96.8%, and 95.4%. In the testing data, the accuracy value for 2014, 2015, 2016, 2017 and 2018 is 100%.