Reviewerly/exHarmony huggingface dataset:
Analisis peran orang tua dalam pendampingan belajar peserta didik sekolah dasar

&lt;p&gt;&lt;em&gt;This study aims to describe the results of the Analysis of the Role of Parents in Student Learning Assistance. This study discusses the role of parents in student learning assistance which takes place at the subject's home, namely in Karang Tengah Hamlet, Jatipuro Village, Karanganyar Regency, Central Java. &lt;/em&gt;&lt;em&gt;This study uses a type of qualitative research. This research uses a case study approach with qualitative methods. Techniques in collecting data are observation, interviews, and documentation. The subject of this study was one student at SD Negeri 02 Jatipuro. The data analysis technique used is technical triangulation. &lt;/em&gt;&lt;em&gt;The results of the research show that the role of parents in assisting students' learning varies and plays a role in supporting children's learning processes. Parents have given the best role to help students in learning by providing assistance, motivation, role models, and facilities. The results of this study indicate that parents play a very important role in the child's learning process. Based on this research, it can be concluded that the role of parents (Mr. Mardi and Mrs. Sri Wahyuni) in assisting students in learning has shown the role of parents, namely first, carrying out the process of accompanying learning by providing several examples in solving problems and providing suggestions for trying various solution method. Second, giving encouragement to children in learning to help children produce their own ideas in the form of giving awards in the form of goods or praise. Third, set a good example by inviting children and asking them to try to implement the ideas that children convey by adjusting the child's abilities and linking them to everyday life. Fourth, provide good facilities in the form of a good room or environment.&lt;/em&gt;&lt;/p&gt;
Strategi pembelajaran anak lamban belajar (slow learner) pada pembelajaran jarak jauh siswa sekolah dasar

&lt;p&gt;This study aims to describe the teachers strategy in dealing with Slow Learners for fifth grade students at SD Negeri 2 Ngringo. The method used in this research is qualitatitve method. This research was conducted at SD Negeri 2 Ngringo. The data in sthis study are the result of interviews with the fifth grade homeroom teacher of SD Negeri 2 Ngringo and 6 students, the results of observations of the learning process, and study documentation. Data collection techniques using interviews, observation, and documentation. The data analysis technique in research is interactive analysis with the stages of data collection, data, reduction, data presentation, and drawing conclusions. The triangulation technique uses data sources. The results of this study reveal a special strategy applied by classroom teachers, namely using an individual of student-centered learning approach and a remedial approach. This individual approach is carried out with special meetings given by the teacher to those who are indicated to have learning delays (Slow Learners). So, by using this approach it is hoped that the teachers will be able to ensure that students are able to understand and process material optimally in the distant learning process. In addition, studentlearning development can also be monitored specicically for teachers to carry out the process of assessing learning development in order to achieve optimal learning goals for Slow Learners.&lt;br /&gt;Kata kunci: distance learning,strategy,slow learners&lt;/p&gt;
E-Commerce Applications In Helping Selling Handphone Products In Ficho Mobile Store

Driven by technological advances and computerization to improve work efficiency through sales on the internet An e-commerce is familiar to consumers, many online stores are frequently visited by consumers. ficho cellular. Adding consumers who will transact at the ficho cellular store. The data collection method used in conducting this research is through primary data (interviews, observations) and secondary data (documents). This research was carried out on July 2 to August 19, 2021. From the results of research and testing that has been done, the design of an E-Commerce application in Helping Sales of Mobile Products at the Ficho Cellular Store can be done by applying php mysql and can be well integrated
Proper names of research instruments: An exploratory study

This exploratory study describes 55 proper names of research instruments in the fields of Medicine, Physical Education, Clinical Studies, and Education. These names were collected from the titles and abstracts of scientific articles published on the DOAJ platform between 2011 and 2022. They were qualitatively analysed according to their morphology, syntax, semantic and pragmatic features, which led to a tentative description of their essential characteristics. The article evidences that there is a basic pattern consisting of a complex noun phrase that describes the type of instrument created. The extent of the names ranges from one to twelve words. Whereas most names are followed by an acronym, others may also include a number, an eponym, an ethnonym, or a toponym. Thus, the pragmatic function of this type of proper name is to make the instrument visible and memorable and encourage its use and citation in future research articles.
Expert System in Helping Students Diagnose Car Engine Damage Using the Expert System Development Life Cycle (ESDLC) Method

At school, especially in Automotive Vocational High Schools, a learning process is carried out by helping students to recognize and overcome problems that occur in motorbike/car damage. One of the SMKs that has an Automotive expertise program is SMK Negeri 2 Bengkulu City. So far, the automotive learning system has used books and pictures to support the learning process at school. However, this sometimes has problems, where students do not fully understand the material given, and on the other hand students have difficulty learning independently either in the school environment or at home. Expert systems in helping students diagnose car engine damage using the Expert System Development Life Cycle (ESDLC) method can be accessed online with internet access via the web link http://riska.vad.my.id. This expert system application is made using the PHP programming language and MySQL database. This expert system application has been embedded with the ESDLC method with the Forward Chaining inference engine which is used to trace damage to car engines based on the symptoms experienced by the car engine. This expert system application can help facilitate the understanding of students at SMK Negeri 2 Bengkulu City in diagnosing car engine damage, by providing consultation directions starting from entering symptoms to getting consultation results. Based on the system testing that has been done, it can be concluded that the functionality of the application has been running well and this expert system can provide consultation results based on the symptoms selected by the user through the stages of the Expert System Development Life Cycle (ESDLC) method.
Comparison of the DES Cryptographic Algorithm and the AES Algorithm in Securing Document Files

The document file security application at the Bengkulu City Education Office was made using the Visual Basic .Net programming language. In this application, 2 cryptographic algorithms have been implemented that can be used to secure document files, especially the employee payroll list file, namely the DES algorithm and the AES algorithm. In addition, this application has also embedded a process to analyze the comparison of the DES and AES algorithms, so that it can be known which algorithm is better to use. The comparison aspect consists of 2 aspects, namely processing time and file size after processing. Based on the tests that have been carried out, it can be concluded that the document file security application at the Bengkulu City Education Office is capable of carrying out the process of encrypting and decrypting document files and the functionality of the application has run as expected. From the test data that has been carried out by the encryption and decryption process, the results obtained based on the encryption processing time show that the AES algorithm is faster than the DES algorithm, based on the decryption processing time it is found that the AES algorithm is faster than the DES algorithm, based on the file size after the encryption process it is found that the DES algorithm and the AES algorithm have the same file size, based on the file size after the decryption process it is found that the DES algorithm and the AES algorithm have the same file size
Application of Recommendations for Selection of Outstanding Students at Seluma 06 State Senior High School Through the Fuzzy Tsukamoto Approach

SMA Negeri 6 Seluma is one of the state senior high schools in Seluma Regency. At the school, students are assessed every academic year through several criteria to select outstanding students who have the ability to master subjects and have good personal ethics. So far, the process of selecting outstanding students is only seen from the results of the report cards obtained by students, then ranking is carried out. This is of course less effective in determining outstanding students, because it must be supported by other aspects such as student ethics during the teaching and learning process. The recommendation application for selecting outstanding students at SMA Negeri 06 Seluma was made using the Visual Basic .Net programming language and SQL Server 2008r2 Database. This application has implemented one of the fuzzy logic methods, namely Fuzzy Tsukamoto which is used to help provide recommendations for selecting outstanding students at SMA Negeri 06 Seluma. The process of selecting outstanding students is carried out every academic year based on aspects based on aspects of average knowledge value, average skills score, absenteeism score, academic achievement, non-academic achievement, and guidance and counseling records. Based on the blackbox testing that has been done, the results show that the functionality of the recommendation application for selecting outstanding students at SMA Negeri 06 Seluma runs well as expected and is able to analyze student assessment data through the Fuzzy Tsukamoto Method to get recommendations for outstanding students
An Expert System To Diagnose Bronchitis Disease Using Certainty Factor Method

This study aims to create an expert system at Rafflesia Hospital of Bengkulu City, based on a website and using the PHP programming language, in diagnosing bronchitis using the certainty factor method, therefore the results of the diagnosis can be first aid when a user or patient suffers from bronchitis. The research method used is the certainty factor method, namely the certainty factor, thus the user or patient can choose. conditions according to the symptoms experienced from bronchitis. The program created is an expert system for diagnosing bronchitis using a website-based certainty factor method so that it can be accessed on laptops, computers, or mobile phones with the condition that it must be connected to the internet. This program can generate a percentage level of the possibility of how many percent of patients suffer from bronchitis, and this program also produces solutions to bronchitis therefore, it can be first aid when the user or patient suffers from bronchitis. Suggestions from the author are for agencies to be able to maintain and always update this expert system program, so then this system can run and be maintained properly.
"COGNITIVELY HIERARCHICAL" MODELING APPROACH RELATIONSHIP BETWEEN THE CONSUMER AND THE SERVICE PROVIDER

Housing is one of the most controversial and debated areas in any country. It is faced to a greater or lesser extent by all citizens, and the effectiveness of its work determines not only its payback, but also the general attitude of the inhabitants of the city, region and country. Today, in general, housing and communal services in Ukraine are one of the most problematic areas. Dispatching, monitoring of resource consumption is one of such issues. One of the tasks facing housing and communal services is to supply energy resources to consumers. This takes into account the consumption of these resources. It is conducted using different meters located on different parts of the network. A model of the relationship that currently exists in the housing market of Kyiv was built. With the help of this study, several scenarios of consumer behavior were built. Namely, "honest", "dishonest", "partial". The effectiveness of the scenarios is compared with each other, both on the part of the consumer and the supplier. Conclusions on the possible behavior of consumers are presented, the problem is reduced to game theory and the "cognitive-hierarchical" approach to solving the problem is considered, given the asymmetry of information. New equilibrium variants are proposed, taking into account possible levels of reasoning.
Domain-specific schema discovery from general-purpose knowledge base

General-purpose Knowledge Bases (KBs) have been used for various applications. An essential step for leveraging the content of KBs on domain-specific tasks is to discover their schema. In this paper, we propose ANCHOR, an end-to-end pipeline for schema discovery from general-purpose KB in an automated way. ANCHOR identifies a domain of interest based on category mapping from KB. Next, it learns representations of entities in this domain based on the entity-category mappings and uses these representations to identify the entities' topics within this domain. Finally, ANCHOR generates a profile for each topic using a strategy based on attributes co-occurrence. We have evaluated ANCHOR on four domains. The results show that: (1) the learned entity representation effectively produces better entity clusters than some traditional and embedding-based baselines; (2) our solution produces a high-quality profile for the discovered topics.
Assessing the effectiveness of image recognition tools in metadata identification through semantic and label-based analysis

This study evaluates the performance of four image recognition tools (Amazon Rekognition, Clarifai, Imagga and Google Cloud Vision API) for automatic image metadata. The experiment was conducted on various image categories, including human, animal, plant and flower, view and landscape, vegetable and fruit, food, vehicle, tourist landmark, art and culture and old book cover and posters. Semantic and label-based analysis was used to evaluate the performance of each tool. Results indicate that each tool performed differently across categories, demonstrating the importance of selecting the appropriate tool for specific tasks. Clarifai was found to perform best for human, animal and food image tagging, while Amazon Rekognition was best for vegetable-fruit and vehicle images. Imagga performed best for plant and flower, art and culture and old book cover and posters image recognition, while Google Cloud Vision API performed best for view and landscape and tourist landmark recognition.
IoT-Driven Healthcare Monitoring with Explainable Machine Learning Models

The need for this work arises from the critical importance of IoT-driven healthcare monitoring. In an era marked by technological advancements, the healthcare sector has not been left untouched. The ability to monitor patients' health remotely through IoT devices has emerged as a promising solution, offering real-time data for healthcare providers. However, amidst this promise, there remain significant challenges. Existing approaches in this domain have limitations. They often lack transparency and interpretability, making it challenging to trust the decisions made by machine learning models. Moreover, their performance metrics often fall short of achieving optimal precision, accuracy, recall, AUC, and speed, which are crucial in healthcare applications where timely and accurate decisions. In response to these challenges, this paper presents a novel approach. The proposed model leverages Convolutional Neural Networks (CNN) and integrates Deep Shap and GridCAM++ techniques to offer a more explainable and interpretable solution for IoT-driven healthcare monitoring. This fusion of methods enhances the model's transparency, allowing healthcare professionals to understand the rationale behind its decisions. The advantages of this approach are multifold. First and foremost, it enhances the precision, accuracy, recall, and AUC by 5.5%, 5.9%, 6.5%, and 8.3%, respectively, when compared to existing methods. These improvements translate to more reliable diagnoses and decisions in healthcare. Additionally, the model achieves a 4.9% boost in speed, ensuring that critical decisions can be made swiftly, reducing the time between data collection and actions. The impact of this work is substantial, it paves the way for more trustworthy and efficient IoT-driven healthcare monitoring systems, addressing the limitations of existing approaches. With improved performance metrics and enhanced explainability, healthcare professionals can make more informed decisions, leading to better patient outcomes. Ultimately, this paper contributes to the advancement of healthcare technology, bringing us closer to a future where IoT-enabled monitoring plays a pivotal role in improving patient care sets.
Secure Data Sharing in IoT Networks using Blockchain and Machine Learning

The burgeoning proliferation of IoT networks has underscored the pressing need for robust and secure data sharing mechanisms. The existing methods for data sharing in IoT networks exhibit certain limitations, notably in terms of energy efficiency, speed, throughput, packet delivery ratio, and overall consistency. These limitations have sparked the demand for innovative solutions that can mitigate these issues effectively. To address these limitations, the paper proposes an advanced model that harnesses the power of Analytic Hierarchy Process (AHP) based Smart Contracts, fortified with Genetic Algorithm optimized Sidechains, within the blockchain framework. This integration synergizes the strengths of blockchain technology and machine learning, offering a robust foundation for secure data sharing in IoT networks. The advantages of this approach are manifold. By leveraging AHP and Smart Contracts, the model ensures the precision and reliability of data transactions. The incorporation of Genetic Algorithm optimized Sidechains optimizes the scalability and efficiency of the system. Consequently, the proposed model exhibits a remarkable 4.9% improvement in energy efficiency, a 5.5% boost in speed, an 8.3% increase in throughput, an 8.5% enhancement in packet delivery ratio, and a 3.9% better consistency compared to existing methods. The impacts of this work are profound. It not only addresses the current limitations of IoT data sharing but also paves the way for more efficient, secure, and reliable data exchange in IoT networks. This innovation holds the potential to revolutionize the IoT landscape, offering a robust solution that can unlock new possibilities for a wide range of applications, from smart cities to industrial automation sets.
Analisis problematika guru dalam pelaksanaan pembelajaran daring pada siswa kelas rendah sekolah dasar

&lt;em&gt;The purpose of this study to describe the implementation of online learning, learning problems experienced by teachers, and the solutions used to overcome the problems that arise in the implementation of online learning in SD Negeri 1 Krasak Boyolali. This research is a descriptive qualitative research. The subjects in this study were second grade teachers at SD Negeri 1 Krasak Boyolali. Data collection techniques through observation, interviews, and documentation. The validity test of the data used in this research is triangulation of sources and triangulation techniques. The data analysis techniques used in this study using Miles and Huberman analysis model consisting of data collection, data reduction, data display, and conclusion drawing/verification. The result showed that there were problems experience by grade II teachers when conducting online learning activities. At the planning stage teachers experience problems when preparing online lesson plans, at the implementation stage teachers experience problems when supervising and delivering learning materials, while at the evaluation stage teachers experience problems in assessing knowledge, attitudes, and skills. The conclusion of this study is that the problems experienced by teachers during online learning activities can be found a solution by adjusting the state of students and the school environment.&lt;/em&gt;
Analisis motivasi belajar dalam menguraikan informasi paparan iklan pada pembelajaran bahasa indonesia kelas V sekolah dasar

&lt;p class="Abstract"&gt;&lt;em&gt;The purpose of this study was to describe the learning motivation of fifth grade elementary school students in describing advertising exposure information. This study used qualitative research methods. The subjects of this study were seven fifth grade students at SDN Mangkubumen Lor No. 15 Surakarta for the 2021/2022 academic year. This study uses data collection techniques in the form of interviews, observation, and documentation studies. The data analysis used is an interactive analysis model consisting of data collection, data reduction, data presentation, and conclusion/verification. The results showed that students with low learning motivation had a percentage of 28.57%. Students with sufficient learning motivation have a percentage of 28.57%. Students with high learning motivation have a percentage of 28.57%. While students with very high learning motivation have a percentage of 14.29%. There are seven indicators of learning motivation to determine the level of student learning motivation, including: being diligent in facing assignments and completing them, facing difficulties tenaciously and never giving up, showing interest in dealing with problems, independent learning, getting bored quickly. on assignment. - Routinely do assignments, defend and convince opinions with good and strong reasons, and like to find problems and solve problems.&lt;/em&gt;&lt;/p&gt;
Analisis keefektifan pembelajaran daring dalam muatan pelajaran PPKn kelas 5 sekolah dasar

&lt;p&gt;The purpose of this study was to determine the effectiveness of online learning on civic education subjects for Class V Elementary School 1 Semali. The subjects of this study were class teachers and students of class V Elementary School 1 Semali, totaling 25 children. There are 3 discussions to determine the effectiveness of online learning, namely the implementation of online learning, the activeness of students when participating in online learning, and student learning outcomes. Data collection techniques in this study included interviews, observation, and document analysis. The data of this study indicate that the implementation of online learning in class V of the State Elementary School 1 Semali is going well, but the students are not active during learning. This results in the teacher's assessment being less than optimal so that student scores tend to decrease during online learning. Based on the data, it can be concluded that the effectiveness of online learning in the subject of Citizenship Education Class V Elementary School 1 Semali for the academic year 2021/2022 is less effective because of the 3 indicators only 1 aspect is in the good category while the other 2 aspects in the poor category and tends to decrease.&lt;/p&gt;