Reviewerly/exHarmony huggingface dataset:
Dive-In: Interactive Learning Tool ‘Arthurian Legends: The Knights’ Quest’ Efficacy in Learning Literature Components among Form 1 Students

The literature component is one of the elements in the Malaysian English language syllabus or Form One to Form Five students in secondary schools.Literary work such as poems, drama, short stories and novels are the main opuses of the curriculum.Therefore, there is a significance in teaching literature to the students regardless of its status in examination at school and national levels.Teaching and learning literature has been one of the arduous components for both teachers and students due to a few hindrances especially during the Covid-19 pandemic.Teachers are lacking exposure to student-centered literature teaching while the students perceive literature as dull.The ability to comprehend the text also influences students' learning.Moreover, less proficient students are prone to cease making an effort during literature learning due to its foreign content.Hence, the aim of this paper is to improve pupils' mastery in a literature novel 'King Arthur' using the learning tool 'Arthurian Legends: The Knight's Quest' and acquire their perceptions towards the tool.This interactive multimedia learning tool, Arthurian Legends: The Knight's Quest incorporates digitalisation of the novel, 'King Arthur' with an inclusive set of exercises.It is designed as an interactive version of the novel with entrancing narration.Furthermore, it also focuses on other language skills such as reading and vocabulary learning.Lastly, this tool may increase students' interests by providing a fun learning environment for the students.This paper provides further explanation whether the tool created the opportunity for the pupils to master the novel 'King Arthur' and elevated their interest in learning the piece successfully.
Recruitment of Teachers for Cooperative Education in Educational Institutions

The study of cooperative education is important not only for researchers but also for those interested in studying educational methods, such as university professors, teachers in schools, and all educational institutions. This is because of its effectiveness in teaching students, developing their skills, developing their ideas and employing them in the study and finding appropriate solutions to the questions posed by the teacher. It also helps in instilling a spirit of cooperation among the students by dividing them into groups to achieve the desired goals. The aim of the study is to clarify how important it is for teachers to use cooperative education in addressing the educational, social and psychological aspects when teaching students in educational institutions. The study is divided into three sections. The first section presents the general framework of the study dealing with the problem, importance and objectives. The second section deals with the concept of cooperative education, its importance and the date of its inception. This section also discusses the most important theories that I mentioned about its importance, results, foundations and objectives of cooperative education, including its benefits, characteristics, stages and strategies. It clarifies the role of the teacher and student in e-learning. The third topic dealt with the methodology of the research and presentation of the results, their interpretation and discussion. The research reached several conclusions, the most important of which are: the teaching staff in educational institutions enjoy a high level in employing cooperative education in their teaching to students and to achieve the educational, social and economic goals, all of which were significant and used.
Application of Smart Surveillance System in National Security

&#x0D; Surveillance has been considered essential in maintaining order and discipline since the dawn of time. This paper explores various domains revolving around the Smart surveillance system ranging from the primitive definition, and how it deviates from traditional surveillance to how we can implement the system on a fundamental level which can be scaled up to work on national-level systems. With the rising criminal activity in today’s world, there is a need for a proposed solution in surveillance applications that can examine human behavior and recognize people with criminal pasts and detect abnormal activities. This article focuses on proposing advancements in Surveillance Systems in Nepal such that Artificial Intelligence (AI) systems will be able to recognize people with criminal pasts and also keep track of a person's behaviour to predict if any acts of violence are about to take place or not. The research aims to explore the potential for such a system in Nepal and other places around the world, including questions such as: what specific types of AI Surveillance are the governments deploying and “The feasibility and challenges of adopting a Smart Surveillance System in Nepal”. The research methodology consists of secondary sources of data to collect the information. A comparative document study, a quick survey with ICT experts, journal articles, and research on current technologies, found that Nepal is not far behind in technological advancements though it lacks policy-level intervention on AI which shows Nepal can enhance its national security by adopting an AI-powered Surveillance System.
The Financial Data Services Domain: From Taxonomies to Ontologies

There are many different types of instruments and hundreds of different markets for investment, leading to an extremely large and hard-to-define universe of financial data. The related commercial offer is extremely heterogeneous and complex. In this scenario, it is difficult to source the most appropriate financial services providers. In the past, eProcurement mainly focused on using ERP management tools to record and examine previous buying decisions and expenditure data. In recent years, machine learning and artificial intelligence have been applied to procurement workflows, introducing computation of external or third￾party unstructured data to achieve a higher level of market knowledge and decision automation. To exploit the possibilities provided by these new technologies to the full extent possible, theoretical models for understanding large amounts of unstructured data are essential. In this research-in-progress paper, we propose a taxonomy of financial data services and depict the related prototype ontological model, providing a possible conceptualization and specification of the domain of interest potentially useful for the development of applications based on semantic technologies.
Analysis of Consumer Motivation for Using Cryptocurrency in Indonesia

Currently, the use of cryptocurrency has been increasingly popular around the globe. In fact, cryptocurrency became the special topic in the 2018 G20 Summit in Buenos Aires. Moreover, in 2021 El Salvador has become the first country in the world to declare Bitcoin as its legal medium of exchange other than US Dollar. In Indonesia the use of cryptocurrency is also growing rapidly. According to Indonesia Crypto Outlook Report 2020, there was a 2,263% increase of cryptocurrencies users from 2015 to 2020, with the total number of users in Indonesia reaching 1,547,329 persons. Based on this development, it is necessary to conduct research to observe what factors influence the use of cryptocurrency in Indonesia. Previous study about behavioral intention in the use of cryptocurrency found four influencing factors, which are performance expectancy, social influence, effort expectancy and facilitating conditions. This research aims to determine the influence of those four factors to behavioral intention to use cryptocurrency in Indonesia. It uses a quantitative approach with survey as its method. Furthermore, the data is analyzed using multiple linear regression techniques. Tests carried out included validity &amp; reliability tests, normality tests, multicollinearity tests, heteroscedasticity tests, autocorrelation tests, F tests and t tests. The results of the study show that performance expectancy, social influence, effort expectancy and facilitating conditions have a significant effect on behavioral intention to use cryptocurrency.
Auto Encoder Fixed-Target Training Features Extraction Approach for Binary Classification Problems

The main issues with machine learning-based feature extraction techniques are the requirement of extensive domain-level knowledge, experience, and the need to be supported by large amounts of data that are sometimes not available. Moreover, it is often difficult to apply domain-level knowledge to extract the necessary features for building a machine-learning classifier. Therefore, it is significantly important to find and develop feature extraction techniques that depend mainly on the training data and don’t require or depend on domain-level knowledge and experience. To address these issues for binary classification problems, a novel feature extraction approach, AE-FT(Fixed Target) for extracting common features using a Deep Belief Network (DBN)-based Autoencoder (AE) is proposed in this paper. In this approach, common features are extracted by a DBN trained on a dataset sample’s binary using the Fixed Target training approach.&#x0D; The proposed common features extraction approach is tested and evaluated on two different data sets. For each dataset, the extracted features are used to train seven of the common machine learning binary classification algorithms and compared their performances. Moreover, the number of extracted features is very small compared to other existing feature extraction methods. Therefore, the proposed common features extraction method improves the performance of the binary classification algorithms by reducing the number of features reducing laborious processes, and increasing the recognition accuracy effectively.&#x0D; The results show that the proposed common features extraction approach, without any domain-level knowledge or human expertise, provides a very good performance compared to other feature extraction techniques.
Design Rancangan User Interface Aplikasi My Pets Dengan Menggunakan Metode Design Thinking

The research was made to produce an application design using the design thinking’s method. The system made on the basis of user interface and user experience. The user interface is used to meet user needs, while the user experience is used as an assessment of the system designed. The target of My Pets application is for pet parents. It has several stages; empathize, define, ideate, prototype, and testing. At the empathize stage it produces the main problems which are used as material for researchers to find a solution, problems obtained from the results of interviews and observations of 25 respondents. In the define stage, it begins to determine the problem as main focus to be solved. The ideate stage, it generates a solution to an existing problem. The prototype stage develops designs based on the previous stages. At the testing stage using the system usability scale to 25 respondents and getting a result of 87.7 or excellent. Based on the test results, My Pets application has been completed and assessed as effective based on the design thinking’s method. It is expected the design made can be used and the system developed better in the future
Pemanfaatan Model ISO 9126 Dalam Pengukuran Kualitas Perangkat Lunak Sistem Pengolahan E-Surat

The development of information technology impacts the use of technology in all fields and the many applications created to support the performance of companies, schools and even MSMEs. Today's very high-end app creation is not accompanied by good-quality support. Good software quality is one of the factors determining a software's success. The software created must be tested for software quality to reduce the loss of software procurement costs, time, and resources. To obtain good software quality, developers must carry out extra activities and a long process by implementing the ISO 9126 model. Six factors are used to determine software quality: functionality, reliability, usability, efficiency, portability, and portability. Keluarahan Sambikerep, Kecamatan Sambikerep, Surabaya, East Java, has developed an E-Letter application to serve the public in administrative activities. Still, the E-Letter application has not been tested for software quality. Researchers conduct quality testing of E-Letter software to ensure that the application complies with International Standards for software quality. By knowing the quality of the E-Letter software, it will automatically have an impact on the services provided by Kelurahan. Researchers use three factors from ISO 9126: functionality, usability, and efficiency. Researchers used black box testing with the equivalence partitions technique to test the E-Letter software. Researchers conducted 30 black box tests on the E-Letter application feature, namely the Login feature, citizen data submission form, birth certificate submission form, death certificate application form, citizen data report form, birth certificate report form, and death report form. From the ISO 9126 Implementation Process for the E-Letter application, an average rating of 81,667% or rounded up to 82% is obtained, which means that the E-Letter application has outstanding quality
Analisis Pengaruh Kualitas Website Kejaksaan Negeri Penajam Paser Utara Menggunakan Metode Webqual

The information technology that used by the Penajam Paser Utara Regency of Prosecuting Attorney Office is a website to support information and public services is more easily, on the website there are several news` menus, profiles, vision and mission, and several of public services. The main function of the Penajam Paser Utara regency of Prosecuting Attorney website as an online public service facility. So far the Penajam Paser Utara Regency prosecuting Attorney has paid little attention to their website and there has no progress because the Penajam Paser Utara Regency of Prosecuting Attorney has no permanent staff in the Information Technology section .The purpose of this research is to know how the quality of the Penajam Paser Utara Regency Prosecuting Attorney Office website affects To The user satisfaction based on the WebQual 4.0 method. The results of the Research for usability quality (X1), it can be seen that the significance value of the usability quality (X1) is 0.035 &lt; 0.05 or T count 2.143) &gt; T table (1.995) so H1 is accepted, then there is an influence between the usability quality (X1) with the user satisfaction (Y). Meanwhile, for Information Quality (X2), it can be seen that the significant value of the information quality (X2) is 0.064 &gt; 0.05 or T count (-1.878) &lt; T table (1.995) so H2 is rejected, so there is no influence between the information quality (X2) with the satisfaction user (Y). As for the Quality of Interaction (X3), it can be seen that the significance value of the quality of the interaction (X3) is 0.002 &lt;0.05 or T count (3.184) &gt; T table (1.995) so H3 is accepted, then there is an influence between the quality of the interaction (X3) with The user satisfaction (Y). From The results obtained are expected to be the recommendation for the Penajam Paser Utara regency Prosecuting attorney Office to develop a much higher quality of the website, So as to increase the utilization of public services through the Penajam Paser Utara regency Prosecuting Attorney Office website, besides that it is also suggested for the future that the Penajam Paser Utara regency prosecuting Attorney Office is given the attention to the overall of quality of the Penajam Paser Utara Regency Prosecuting Attorney Office website in order to maintain or to increase of the user satisfaction in using their website
Prediksi Penjualan Sparepart Mobil Terlaris Menggunakan Metode K-Nearest Neighbor

PT. GAYA MAKMUR MULIA MEDAN is a company engaged in selling spare parts and spare parts in North Sumatra. Along with the development of technology, the increasing business competition, especially regarding the sale of spare parts. This also affects the competition between brands of goods with the quality they produce. Products offered by various brands, brands influence people to buy these products. Judging from the large number of consumer requests for spare parts products based on sales over the last 2 years, predictions are needed for sales of the best-selling spare parts products, in order to make it easier for companies to provide stock. To find out the sales of best-selling spare part product, data mining techniques and K-Nearest neighbor algorithm are used to produce predictions of the best-selling sales in the Mitsubishhi division with an accuracy of 80,00% and Isuzu accuracy of 66,67% so that acquisition targets are obtained to increase the accuracy value for the classification of best-selling product sales.PT. GAYA MAKMUR MULIA MEDAN is a company engaged in selling spare parts and spare parts in North Sumatra. Along with the development of technology, the increasing business competition, especially regarding the sale of spare parts. This also affects the competition between brands of goods with the quality they produce. Products offered by various brands, brands influence people to buy these products. Judging from the large number of consumer requests for spare parts products based on sales over the last 2 years, predictions are needed for sales of the best-selling spare parts products, in order to make it easier for companies to provide stock. To find out the sales of best-selling spare part product, data mining techniques and K-Nearest neighbor algorithm are used to produce predictions of the best-selling sales in the Mitsubishhi division with an accuracy of 80,00% and Isuzu accuracy of 66,67% so that acquisition targets are obtained to increase the accuracy value for the classification of best-selling product sales.
Sistem Pakar Skrining Gejala Gangguan Kepribadian Ambang Menggunakan Metode Certainty Factor

Borderline Personality Disorder is a type of personality disorder characterized by an overall unstable personality pattern, excessive impulsivity, which often confuses sufferers with their own identity. An expert system is a system developed to assist in making decisions on a particular problem. This expert system aims to help screen symptoms of borderline personality disorder and provide solutions to relieve these symptoms. The method used by the expert system is the certainty factor. The expert system development stage uses the waterfall method and uses the PHP programming language. The results of this study are in the form of an accuracy value of 80% with test data of 10 people, these results are obtained by comparing the results of experts with the results of the system that has been designed
Implementasi Algoritma Apriori Untuk Menentukan Pola Pembelian Produk

Flanker Distro or known as Flanker Flag Shop is one of the names of distros engaged in the sale of various types of racing-themed t-shirts, jackets and hats. The problem that occurs in Flanker distro is that sales patterns have not yet been formed, making the owner experience difficulties in determining what products must be provided at a certain time and the stored transaction data is only used as an archive, even though the transaction data can be processed and used as useful information to determine future business strategy. With the large number of existing sales transaction data, it will be difficult if the data is analyzed manually, so to overcome this problem a system is needed to process the data automatically so that it is easy to get sales patterns. The results of this processing will produce transaction information to help determine product sales patterns. The implementation will be made in the form of a web application that uses the UML (Unified Modeling Language) modeling method and the a priori algorithm by providing relationships between items in sales data. In this case, it is a product purchased by a consumer so that a consumer buying pattern will be obtained. The application of the Apriori Algorithm helps in forming possible item combination candidates, then testing whether the combination meets the minimum support and confidence parameters which are the threshold values given by the user. The test was carried out with monthly Flanker distro transaction data from January to July 2022 with a total of 316 sales transaction data. The results of the analysis are obtained after calculating the association rule using the minimum support rule of 5 and a minimum confidence of 30%. So that later it will produce information that can be the basis for Flanker distro owners to determine business strategies and carry out product production in the following months, semesters and years.
Implementasi Metode K-Modes Dalam Pengelompokan Penerima Bantuan Langsung Tunai

Direct Cash Assistance is a government assistance program that is given to underprivileged people. Assistance is distributed in the form of cash assistance sourced from village funds. In the process of distribution BLT funds, there were obstacles faced by the village, namely incomplete data on BLT recipients. Based on these constraints, a data survey of BLT recipients was carried out using predetermined variables. There are 20 variables used for BLT recipients. Based on the survey results, there was a lot of data that had something in common, making it difficult for the Sungai Dungun village to group BLT recipients. Therefore we need a system that can grouping BLT recipient data. The method used for grouping data on this system is the K-Modes method. The test uses the Davies Bouldin Index (DBI) to know out whether the cluster results are good or not. Based on the results of the DBI test, there is a minimum value generated in grouping using 4 groups with a value of 1.25858. Grouping with 4 groups resulted in a very worth it group of 101 heads of households, a feasible group totaling 40 heads of households, a moderately feasible group totaling 44 heads of households, and an unfeasible group totaling 15 heads of households.
Deteksi Serangan pada Jaringan Kompleks IoT menggunakan Recurrent Neural Network

The complex network in the Internet of Things is challenging to maintain network security. With network complexity including data, protocols, sizes, communications, standards, and more, it becomes difficult to implement an intrusion detection system (IDS). One way to improve IDS on complex IoT networks is by using deep learning to detect attacks that occur on complex IoT networks. Recurrent neural network (RNN) is a deep learning method that enhances the detection of complex IoT networks because it takes into account the current input as well as what has been learned from previously received inputs. When making decisions about RNNs, consider current information as well as what has been learned from previous input. Therefore, this study proposes the RNN method to improve the performance of attack detection systems on complex IoT networks. The results of this experiment show satisfactory results by increasing the performance of the accuracy detection system in complex IoT networks which reaches 87%.