Reviewerly/exHarmony huggingface dataset:
DESAIN INTERIOR DAN MINAT KUNJUNG MASYARAKAT DI PERPUSTAKAAN DAERAH KABUPATEN TRENGGALEK

Interest in visiting the public at the Trenggalek regional library is still relatively low. One of the important factors that can increase the interest in visiting and the comfort of the community is interior design. This study aims to determine the role of interior library design in increasing user interest in visiting and knowing the condition of the library based on the elements of interior library design. This study uses a qualitative method with purposive sampling technique as a way of searching for informants. The informants in this study consisted of 3 informants, namely 2 users who had visited the Trenggalek regional library before and before, and 1 librarian. Researchers used data collection techniques in the form of observation, interviews, and documentation. The presentation of the research is done in the form of a narrative text. The results of this study indicate that the interior design of the Trenggalek regional library has a good influence on efforts to increase public interest in visiting. There are several elements that have been implemented well, including layout, color, and lighting. However, there are still unsatisfactory elements, namely air circulation and sound system. This is due to the small number of fans, the absence of air conditioning, and a whispering sound is still heard. The interior design of the Trenggalek regional library is not optimal due to the limited cost of building a library. Meanwhile, several factors in the interest of visiting are service, infrastructure, attractiveness of the place, and security.
Perancangan Filament Extruder pada Mesin Pengolah Sampah Plastik Terintegrasi “Creatics” Menggunakan Metode TRIZ dan AHP

&lt;p&gt;&lt;strong&gt;3D printer technology is being widely used in various manufacturing industries. 3D printers can produce three-dimensional products made of plastic sheets with a certain diameter called filaments. 3D printer filaments that are widely used are made of &lt;em&gt;Acrylonitrile Butadiene Styrene&lt;/em&gt; (ABS) plastic. The purpose of this research is to develop a Creatics plastic waste processing machine to produce products in the form of filaments that can be used as materials in 3D printers, so that they have more economic value and are environmentally friendly. Creatics machine is an integrated plastic waste processing machine that converts plastic waste into recycled products. In this study, the &lt;em&gt;Teorija Rezhenija Izobretatelskih Zadach&lt;/em&gt; (TRIZ) method is used as a product development method to determine product specifications that are able to generate new ideas by eliminating contradictions and using innovative principles that can produce creative solutions. In the process of selecting alternative concepts, the &lt;em&gt;Analytical Hierarchy&lt;/em&gt; &lt;em&gt;Process&lt;/em&gt; (AHP) decision-making method is used. The results obtained by the TRIZ method are important parameters and need to be prioritized in designing a filament extruder, namely product reliability, energy use from moving objects, and product strength. The product design chosen based on the AHP method is a filament extruder made of stainless steel to be resistant to rust and utilizes the fan in the filament cooling process.&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt; - &lt;em&gt;AHP method, Creatics machine, Filament extruder, Plastics waste, TRIZ method &lt;/em&gt;&lt;/p&gt;
Symmetry as a Representation of Intuitive Geometry?

Recognition of geometrical patterns seems to be an important aspect of human intelligence. Geometric pattern recognition is used in many intelligence tests, including Dehaene's odd-one-out test of Core Geometry (CG)) based on intuitive geometrical concepts (Dehaene et al., 2006). Earlier work has developed a symmetry-based cognitive model of Dehaene's test and demonstrated performance comparable to that of humans. In this work, we further investigate the role of symmetry in geometrical intuition and build a cognitive model for the 2-Alternative Forced Choice (2-AFC) variation of the CG test (Marupudi & Varma 2021). In contrast to Dehaene's test, 2-AFC leaves almost no space for cognitive models based on generalization over multiple examples. Our symmetry-based model achieves an accuracy comparable to the human average on the 2-AFC test and appears to capture an essential part of intuitive geometry.
Morphosyntax Errors in Undergraduate Research Articles from English Education Department

Since the graduates of English education department are expected to be educators, errors that are still prevalent in their research articles need to be acknowledgedas teaching what is essentially flawed language use may lead to damaging results.Therefore, the aim of this research is to inspectprevalent morphological and syntactical errors in undergraduate research articles from English education department and determine the factors causing the errors. The results of the study show that errors are found at both morphological and syntactical levels. The morphological level includes inflection, derivation, preposition, article, possessive determiner, quantifier determiner, copula be, and pronoun. Meanwhile, the syntactical level includes passive voice, tense, infinitive, noun phrase, adverbial clause, adjectival clause, auxiliary, and subject-verb agreement. As for the source of errors, both interlingual and intralingual factors are attributed to causing such errors.This study highlights the process of error classification andthe trend of frequently-made errors, including their commonality within the EFL context. Several suggestions are also offered in order that English learners can be more attentive to their writings.&#x0D; Keywords:error analysis, morpheme, syntax, research article, undergraduate
Analisis Web Performance Load Test Setelah Menggunakan Azure WAF Studi Kasus Pada Aplikasi ERP

The increasing use of web applications is certainly proportional to the increase in cybersecurity attacks that occur. Many companies or agencies are less concerned about the security of the web applications that are used so that these web applications can be easily hacked. On the other hand, there are many ways to protect websites from hacker attacks, one of which is implementing waf. WAF is an application or device that has the ability to filter, monitor, and block traffic that goes to a website. The waf used in this study is a cloud-based waf, namely azure application gateway. Based on this, this study aims to discuss web performance analysis and load testing of a website after implementing waf. The tools used to test Web Performance and Load Test are GTMetrix and Pingdom Tools. With this research, it is hoped that this research can be a reference for individuals or agencies that will implement waf
Using CAD Virtual Reality Technology to Optimize the Communication and Presentation of TV Media

With the development of economy and the continuous progress of society, computer has become an indispensable part of People's Daily work and life, making People's Daily life more convenient and improving the efficiency of industrial production.Computers are important in all kinds of industries and industrial product design as well.The addition of computers not only saves labor costs and improves customer satisfaction, but also improves product quality and performance to a certain extent and improves work efficiency.It can be seen that in the process of work not only to make detailed product plans, but also to understand the current development and trend of computer-aided industrial product design.The computer is an important device in the industrial design industry.Virtual reality technology effectively integrates information technology, sensing technology and intelligent platform to build a virtual operation scene, and describes the running information of things in the current virtual environment through the docking and mapping of data information.Based on this, this paper takes the classification of virtual reality technology as the breakthrough point, explains the advantages of applying virtual reality technology in industrial design, and studies the application of virtual reality technology in industrial design.This paper discusses the application mode of cad in various stages of industrial design, analyzes the shortcomings existing in the current application process, and puts forward some suggestions for better popularization and application of CAD in industrial design.
Upaya Meningkatkan Prestasi Belajar IPS dengan Menggunakan Metode Kerja Kelompok pada Siswa Kelas IV SD N Gading Asri, Playen, Gunungkidul Tahun Pelajaran 2021/2022

The background of this research is that the lack of social studies learning achievement is caused by the selection of learning methods that do not increase students' motivation and activeness in participating in learning. Given that the learning process is very large in determining the success of students, it is necessary to conduct research on learning improvements. The purpose of this study is to prove that the application of the group work method can improve student learning achievement regarding the material for maintaining personal documents and valuables for fourth grade students at SDN Gading Asri, Playen, Gunungkisul, Academic Year 2021/2022. The research was carried out in 2 cycles consisting of cycle 1 on 20 and 22 August 2021. then cycle 2 will be held on 27 and 29 August 2021. Each cycle consists of several stages, namely: planning, implementation, observation and reflection. The data collected is analyzed at each stage of the cycle with quantitative descriptive analysis. Based on the research results, it can be concluded that the improvement of learning through the group work method in social studies subjects for fourth grade students at SDN Gading Asri in the 2021/2022 academic year can be increased. This can be seen from the increase in the average score of students starting from pre-cycle activities, namely 66, after the action in the first cycle increased to 73 then after the second cycle of action the average value increased again to 84.
QGNN: Value Function Factorisation with Graph Neural Networks

In multi-agent reinforcement learning, the use of a global objective is a powerful tool for incentivising cooperation. Unfortunately, it is not sample-efficient to train individual agents with a global reward, because it does not necessarily correlate with an agent's individual actions. This problem can be solved by factorising the global value function into local value functions. Early work in this domain performed factorisation by conditioning local value functions purely on local information. Recently, it has been shown that providing both local information and an encoding of the global state can promote cooperative behaviour. In this paper we propose QGNN, the first value factorisation method to use a graph neural network (GNN) based model. The multi-layer message passing architecture of QGNN provides more representational complexity than models in prior work, allowing it to produce a more effective factorisation. QGNN also introduces a permutation invariant mixer which is able to match the performance of other methods, even with significantly fewer parameters. We evaluate our method against several baselines, including QMIX-Att, GraphMIX, QMIX, VDN, and hybrid architectures. Our experiments include Starcraft, the standard benchmark for credit assignment; Estimate Game, a custom environment that explicitly models inter-agent dependencies; and Coalition Structure Generation, a foundational problem with real-world applications. The results show that QGNN outperforms state-of-the-art value factorisation baselines consistently.
Student Learning Arrangement Based On The ‘Flipped Classroom’ Model’

The article is devoted to the topical issues of remote student-teacher interaction in the Moodle environment.The article dwells on the opportunity of using the 'Flipped Class' model in higher education as one of the models of blended learning as it seems to be the most reasonable in today's epidemiological situation.During the study, the authors review psychological, educational and methodological literature on the problem of including the flipped classroom technology in teaching Teacher Training students, cover the use of modern information and communication technologies in education, report on the regulatory documentation related to the learning process in higher education; best practices of remote interaction between students and lecturers in a teacher-training university.As a result of the study, the authors describe the stages of planning a lesson typical of the 'Flipped Class' model, touch upon the trends of the course content transformation using modern information and communication technologies, give examples of digital tools that are supposed to be introduced into the interactive forms for teaching undergraduate students.The results obtained during the educational experiment and presented in the paper, point to the effectiveness of the 'Flipped Class' model in learning for Teacher Training undergraduate students.
OCR for Arabic character recognition with advanced principal component analysis based on feature extraction and fuzzy-KNN based classification

Offline character recognition has become a highly important study field for various pattern recognition applications in recent years. Several handwritten character recognition systems have been suggested, with the complexity of these systems varying depending on the recognizing units' writing styles. In reality, identifying letters or numerals is far simpler than recognizing cursive sentences or lines of text. As a result, early handwriting recognition algorithms could only distinguish a few characters with limited vocabularies. Nowadays Arabic handwritten character recognition is very important as it is very difficult to identify. The cursive writing and variety of styles make this recognition more complex. This paper presents an automated model for ACR. This ACR is constructed from four phases: Preprocessing, Segmentation, Feature Extraction, and Classification. In this research article, we compare the advanced EPSO EKNN Algorithm with the earlier DBN Algorithm and also suggest a new method having higher Accuracy. In this research article, the "Enhanced K-Nearest Neighbor" (EKNN) classification model was used to identify and classify or simply recognize the particular Arabic character, and the "Extended Particle Swarm Optimization" (EPSO) methodology was introduced to select the best feature from feature extraction to comply with Arabic-Character Classification.
Prediksi Penggunaan Obat Peserta Jaminan Kesehatan Nasional Menggunakan Algoritma Naïve Bayes Classifier

Currently, most of the patients seeking treatment at the hospital use the National Health Insurance (JKN) organized by the Healthcare and Social Security Agency (BPJS Kesehatan). In some hospitals, the figure is above 80%. Considering the very high number of BPJS Kesehatan participant seeking treatment at the hospital, a good data management method is needed, especially regarding the management of drug. Drug supply needs to be analyzed from time to time so that it can help predict future needs. An adequate supply of drugs and as needed is one of the things that affect service to patients. The availability of sufficient stock is expected to accelerate service to patients so that they do not have to wait long. Patients who are served quickly are expected to be satisfied. The impact of this patient satisfaction will increase the number of patient visits to the hospital. To support this, it is necessary to create a system that can estimate drug needs. The system can predict drug demand by using drug sales data to JKN participant patients for five years. Drug data used as research samples and then processed using an algorithm is the Naive Bayes Classifier. The Naive Bayes Classifier method is a method used to predict future opportunities using the basis of previous experience. A distinctive feature of this method is that it uses a very strong assumption of the independence of each event. While software testing uses the User Acceptance Test (UAT) model. Based on testing using this method, the system can be well received by users with a score of 78.64% (good).&#x0D;
Sistem Cerdas Berbasis Android Untuk Diagnosa Penyakit Betta Fish (Ikan Cupang) Menggunakan Metode Dempster Shafer

This study focuses on designing and making intelligent systems to help diagnose diseases found in betta fish or better known as betta fish using the dempster shafer method, the problem that has been happening is the lack of knowledge of novice cultivators related to the diseases suffered by betta fish resulting in their death. Siamese fighting fish. There are several diseases that often attack betta fish, some of which are Stress, White Spot and Pineapple Scales. In building an android-based intelligent system for diagnosing this betta fish disease, the Research &amp; Development research method is used. The use of the dempster shafer is very suitable to be implemented to diagnose diseases in betta fish (betta fish) which basically users of this application do not know for sure the disease that is being suffered by betta fish
My HD Media Pembelajaran pada Masa Pandemic Covid-19 Berbasis Mobile Learning

&lt;span lang="EN-US"&gt;The application of online and offline learning certainly requires more innovation to absorb more optimally, one of which is the application of technology as a learning medium. The role of technology today in learning has a considerable influence. Based on the results of interviews with students, it was revealed that students felt bored with the learning process and with reduced offline learning time while students did not have handbooks for studying at home, so that the implementation of learning was less than optimal. Based on these problems, the design of learning media was carried out on My Hope and Dream's English subject for class XI students based on mobile learning. This research aims to develop My HD learning media, find out its feasibility, and look for user responses to My HD products. The method used in this research is Research and Development (R&amp;amp;D). This method is used to produce products and test the feasibility and user response to the resulting product. The data collection instrument used a questionnaire. Based on the results of the expert evaluation of the application material, it is in the Very Appropriate category for use with an average percentage of 85%. Based on media experts, it is in the Very Appropriate category for use with an average percentage of 89%. User responses were obtained from the data collection results using a questionnaire with an average percentage value of 83% in the Very High category&lt;/span&gt;
The Opposition-Based Learning Parameter Adjusting Harmony Search Algorithm Research on Radars Optimal Deployment

In order to solve the problem of maximizing the utilization of resources through reasonable deployment under limited resources, this paper studies from two aspects: one is to establish the mathematical model of maximum coverage of space detection, and the other is to improve the harmony algorithm. The exploration performance and convergence performance of the harmony search algorithm are analyzed theoretically, and the more general formulas of exploration performance and convergence performance are proved. Based on theoretical analysis, the algorithm called opposition-based learning parameter adjusting harmony search is proposed. By using the algorithm to test the functions of different properties, the value range of key control parameters of the algorithm are given. The proposed algorithm is applied to optimize the problem of radar deployment. This paper takes a certain area of the Shandong Peninsula as the deployment scope. The simulation results show that the proposed algorithm is effective and practical. Although there is a large amount of calculation, it provides ideas and ways for other problems, such as the site selection of new observation and communication post, the deployment of maneuvering radar stations, and the track planning of fleet.
Implementasi Pembelajaran Artificial Intelligence Bagi Siswa Sekolah Dasar di Kota Batu, Malang, Jawa Timur

In today's learning, the development of artificial intelligence designs is a necessity to support the education system. The involvement of artificial intelligence will help students more easily understand lessons in class and facilitate interaction between students and teachers. Through the development of design concepts and learning pelatihans, it is expected to be able to encourage the participation of students and teachers to be able to support the learning system in order to obtain better educational outputs through the use of appropriate technology. There are three learning platforms that are used as learning media, including Duolingo, Khan Academy, and Kejarcita. During the implementation of the activity, it was found that students tend to learn faster and enjoy exploring new things. It is hoped that the artificial intelligence learning design through these three applications can help the learning process during the Covid-19 pandemic which requires school from home to continue and run smoothly.
Ketidakhadiran Guru Hubungannya Terhadap Kerusakan Fasilitas Kelas dalam Jangka Waktu Satu Semester (Penelitian di SMP Darul Falah Cihampelas Bandung Barat)

The purpose of this study was to determine how much influence the absence of teachers in teaching and learning activities (KBM) had on the damage to existing facilities in the classroom at SMP Darul Falah Cihampelas West Bandung. The number of teachers in this school is 110 people and the number of students is 27 groups with grade 7 nine grades, grade 8 nine classes, and grade 9 nine classes, teacher attendance was studied in the odd semester of the 2018-2019 school year, with a presentation of 100% attendance in January , February 96%, March 98%, April 70%, May 98% and June 50%. From these data, the level of influence of the teacher's presentation with the damage to class facilities will be presented.
ToKen: Task Decomposition and Knowledge Infusion for Few-Shot Hate Speech Detection

Hate speech detection is complex; it relies on commonsense reasoning, knowledge of stereotypes, and an understanding of social nuance that differs from one culture to the next. It is also difficult to collect a large-scale hate speech annotated dataset. In this work, we frame this problem as a few-shot learning task, and show significant gains with decomposing the task into its "constituent" parts. In addition, we see that infusing knowledge from reasoning datasets (e.g. Atomic2020) improves the performance even further. Moreover, we observe that the trained models generalize to out-of-distribution datasets, showing the superiority of task decomposition and knowledge infusion compared to previously used methods. Concretely, our method outperforms the baseline by 17.83% absolute gain in the 16-shot case.