Reviewerly/exHarmony huggingface dataset:
SHORT-TERM FORECASTING DAILY ELECTRICITY LOADS USING SEASONAL ARIMA PATTERNS OF GENERATION UNITS AT PT. PLN (PERSERO) TARAKAN CITY

Electrical power requirements at load centers tend to change over time, so the State Electricity Company (PLN) as a provider of electrical energy must be able to predict electrical load requirements every day. The city of Tarakan as a reference center in the northern region of Indonesia is developing rapidly. Along with this growth, the need for electric power is of course also increasing, so we must be able to provide an economical and reliable electric power supply system. This research aims to predict the electricity load at PT. PLN (Persero) Tarakan City. The author will carry out short-term forecasting using time series data in the form of daily electrical power usage data using the Autoregressive Integrated Moving Average (ARIMA) method. The ARIMA method or often called the Box-Jenkins technique shows that this method is suitable for predicting a number of variables quickly, simply and cheaply because it only requires variable data to be predicted. Analysis based on the Box-Jenkins time series taking into account the influence of seasonal patterns. The prediction results show that the data contains seasonal elements with the best model being SARIMA with a MAPE of 3 percent.
Modelling interpersonal behaviour-motive-satisfaction for employee commitment: Gender as moderator

This study investigated the association between interpersonal communication constructs and employee commitment. Employers and employees must have effective interpersonal communication skills to comprehend one another, understand requirements and expectations, and manage the workforce efficiently. Effective interpersonal communication also aids in enhancing the organisation’s engagement and enabling stronger bonds with stakeholders and colleagues. This research uses the quantitative method, a questionnaire-based survey of employees from various businesses to examine the factors that influence interpersonal communication competence. The data were analysed with partial least squares structural equation modelling with SmartPLS software. The findings reveal employers should prioritise interpersonal communication to enhance employee commitment. Organisations could undertake more engagement sessions and training to increase interpersonal communication. This study added to the body of knowledge by examining the relationship between three interpersonal communication factors and employee commitment. Other interpersonal communication factors influencing employee commitment and a mixed-method approach should be considered for future studies.
Approaching Relative Chronology of Unified Silla Pottery in Gyeongju: Emphasizing Overlapping Features and Stratigraphy

Given the challenging nature of obtaining a complete collection of artifacts from Unified Silla pottery, the issue of verifying typological chronology has been consistently raised. To overcome these limitations, this paper undertakes an experimental effort to establish a relative chronological framework for small vessels (bowls with heels, lids, and soft-type bowls) that can be comparatively sequenced and positioned through overlapping features and stratigraphy. By scrutinizing the distribution of continuous and nominal attributes for each type, the paper identifies morphological changes in relation to relative order and uses this as a basis for chronological differentiation.&#x0D; When compared with existing chronological frameworks, the results indicate a degree of validation for the overall trend of morphological changes, allowing for the reconsideration of certain aspects of the existing chronological sequence. Issues within the current chronological framework, such as the relationship between bowls with upright rims and everted rims and the temporal positioning of dot-punctuated designs, were also examined. However, given the focus on precision in this chronology, finer chronological details were not fully derived in this attempt.&#x0D; Nevertheless, considering the meaningful outcomes of this initial chronology in terms of validation, with further expansion to include relative order data, historical absolute dates, and radiocarbon dating, along with closed finds like pottery from well excavations, a comprehensive chronological framework for Unified Silla pottery could be constructed.
LARGE-SPAN BRIDGE STRAIN RECONSTRUCTION BASED ON BIDIRECTIONAL LSTM AND ESN

Partly missing and anomalous of the data collected from structural health monitoring (SHM) systems are inevitable due to the failure of sensor and data acquisition equipment, which lead to misjudgment of the target structure state. The data integrity demands for guaranty using reconstruction algorithms before signal processing. Recurrent neural networks (RNN) has been proved effective of reconstruction issue by learning from the historical and future signal segments. The gated RNN represented by long short-term memory (LSTM) networks and reservoir computing represented by echo state networks (ESNs) show superiority on accuracy or training efficiency than standard RNN method. In addition, bidirectional concept can be introduced into these two methods to further improve their reconstruction precision. In this paper, models built by bidirectional LSTM and ESN are used to reconstruct strain data measured by the SHM system of Tsing Kau bridge, during which performances in both time and frequency domains are compared and evaluated. Furthermore, hyperparameters including number of layers, number of hidden units, scale of reservoir, and leaky rate have been optimized to improve the structures of the proposed models.
APPLICATION OF AUGMENTED REALITY IN HERBAL PLANT LEARNING MEDIA

Knowledge about herbal plants is widely known by the public. In addition, now is the transition period from the Covid-19 pandemic which has claimed many victims. In a lot of information, it is often mentioned that diseases are caused by drugs that contain very dangerous chemicals. This research introduces that you can study herbal plants along with information and recipes on how to process them in one application by utilizing augmented reality technology, a technology that combines three-dimensional graphics with the real world in real time with the help of a smartphone camera device. With augmented reality, the information displayed will be more interactive for users. Using the MDLC method makes the design of this application more mature, using this application displays 3D plants and brief plant information that matches the identified image. Augmented reality can provide a new method for information media. The result of developing this application is a learning medium that is very easy to use and has many benefits for the general public to avoid dangerous drugs and get to know more about herbal plants. The results of testing this application also obtained satisfactory results using the black box testing method to find out respondents using a questionnaire and in the nose using a Likert scale which got a score of 85%. This application can also run optimally on several different Android operating systems.
Pendampingan Strategi Peningkatan Kemampuan Memahami Materi Ekonomi Akuntansi Siswa Program Studi IPS MAMA 7 Banjarwati Paciran Lamongan Jawa Timur

This mentoring research aims to maximize strategies for increasing the ability to understand economic material and to increase the interest of students at Madrasah Aliah Ma'arif 7 Banjarwati, Sunan Drajat Banjarwati Paciran Lamongan Islamic Boarding School foundation. The method used in this assistance is Participatory Action Research (PAR). This assistance will be carried out in the even semester of the 2022/2023 academic year. The results of this research show; MA.MA 7 Banjarwati Sunan Drajat Islamic Boarding School maximizes the increase in the ability to understand economic material by maximizing learning strategies, learning methods and teaching aids in learning by adapting appropriate material in the teaching and learning process. Meanwhile, to increase students' interest in studying MA.MA 7 Banjarwati Sunan Drajat Islamic Boarding School Banjarwati Paciran Lamongan by formulating the problems faced by students and providing motivation to students about the importance of serious study so that it can encourage students' interest in learning with the stimulus of prizes, grades for outstanding students
THE BEST NURSE RECOMMENDATION SUPPORT SYSTEM AT THE SRI MURTI HUSADA CLINIC IN SURAKARTA WITH THE WEIGHTED PRODUCT METHOD

The Health Agency is a health institution that is needed in a place for treatment of a disease. The current outbreak of the corona virus demands optimal public health services. The role of medical personnel is an important concern in the world of health. Every Health Agency strives to be able to provide good and competent medical personnel in their fields to be able to help the community. Sri Murti Husada Clinic is a maternity clinic to serve patients of mothers who are about to give birth, check their wombs, place family planning, treat premature babies and others. The clinic is supported by specialist doctors, midwives and nurses who have various levels of performance. The problem in this study is the large number of patient requests for quality nurse performance services, for this reason the clinic must be able to provide the best nurses with criteria such as: Performance, Education, Years of Service, Discipline, Attitude and Productivity. In the old system that has been running in determining the best nurse only based on years of service and ignoring other criteria. This old system model can lead to inaccurate and unfair decision results. The aim of this research is to make a decision support system (SPK) application for determining the best nurse performance at the Sri Murti Husada Clinic using the Weighted Product Algorithm Method. This method was chosen because it has the ability in ranking to determine the best alternative by applying all the criteria. The result of this study is the formation of a decision support system application that can provide the best nurse recommendations by applying all the criteria. The results of the functionality test were successful for all test scenarios and the validity results obtained matched valid results.
Image Classification Using Deep Learning

- Image classification is an important topic of study in the field of image processing nowadays and is a popular area of research. By providing the computer with data to learn from, image categorization was created to close the gap between computer vision and human vision. In this paper, the methods for categorising images using traditional machine learning and deep learning are compared and investigated. This study employs a tensor flow framework and convolutional neural networks to classify images. This paper implements CNN in binary classification and multi-class classification for object identification and analyses the performance of well-known convolutional neural networks (CNNs). We built five unique image datasets on our own for multiclass classification, using the dog vs. cat dataset for binary classification. For our investigation, we classified the photos using a separate machine learning model and then classified them again using CNN because evaluating CNN's performance on a single data set hides its actual potential and limits. Additionally, trained CNNs perform very differently across various categories of objects, and we will thus talk about some potential causes. Key Words: Image classification, python, Deep Learning, Tensor flow, Convolutional Neural Network, Open CV, NLP
Penggunaan Strategi Story Impressions untuk Mengembangkan Kemampuan Analisis Teks Cerita Fantasi Pada Siswa SMP

This study aims to understand the use of Story Impression strategies in an effort to develop the ability to analyze fantasy story texts in students of SMP Negeri 1 Tebo Regency. In this study, Pre-experiment design with one group pretest-postest design was used. The participants in this study were 5 students from class VII at SMP Negeri 1 Tebo. The measurement was conducted by utilizing a written description test developed together with several Indonesian language teachers who also served at SMP Negeri 1 Tebo. From the results of data processing that has been done, it is known that there is a change in the average score of the pretest which previously had a value of 62.4 then increased to 93.2 in the posttest. The change value is then described through N-Gain of 0.81. The N-Gain value is classified as a high change value. Based on this, it can be understood that the use of the Story Impression strategy is known to have benefits for developing the ability to analyze fantasy story text in groups.
XSS Attack Detection using Machine Learning Algorithms

This project focuses on the development of an XSS attack detection system using machine learning algorithms. The research involves the careful curation of diverse datasets encompassing XSS attacks and benign data. Key features are extracted, emphasizing HTML structure and JavaScript patterns. The study evaluates the efficacy of k- Nearest Neighbors, Logistic Regression, Random Forest, and Support Vector Machines (SVM) in detecting XSS threats. The training phase optimizes model accuracy, and performance metrics such as Precision, Recall, and F1 Score assess the model's effectiveness. Results provide a comparative analysis of machine learning algorithms, offering insights for future implementations. The study contributes to strengthening web security, showcasing the potential of machine learning in XSS attack detection.
IMPLEMENTATION OF PROBLEM-BASED LEARNING MULTIMEDIA WITH FIND AND SORT QR CODE GAMES TO IMPROVE STUDENT'S COMPUTATIONAL THINKING SKILLS

This study aims to evaluate the effectiveness of using and developing problem-based learning multimedia with find and sort QR code games to improve students' computational thinking (CT) skills in learning object-oriented programming using a web-based digital platform. The Research and Development (R&amp;D) method and One-Group Pretest-Posttest design was used in this study. The subjects of this study were 35 students of SMK Negeri 1 Cimahi, Indonesia. There are three stages in conducting research 1) analysis of problems, 2) learning multimedia development, and 3) evaluation. The findings show there is an increase in students' CT skills after implementing the find and sort QR Code Game problem-based learning multimedia during the learning process. Student learning outcomes have increased from 45.71 (pretest) to 89.50 (posttest). The average increase in student learning outcomes occurred significantly based on the results of the t-test. In addition, the students' CT average score increased from 65.43 (pretest) to 85.29 (posttest). The order of increasing the CT component based on the n-gain value is 1) abstraction (0.66); 2) pattern recognition (0.63); 3) decomposition (0.48); and 4) algorithm design (0.39). Student responses to multimedia learning in this study were obtained very well with a score of 84.95%.
A plan of improvement for the security major curriculum within universities to cultivate security industry professionals

The purpose of this study is a plan to improve the curriculum for security majors in universities to train security industry professionals, and the research method to achieve the research purpose was set as a systematic literature review. The identified problems consisted of three issues: first, deepening of the centralization of educational subjects, second, the curriculum not reflecting social changes and trends, and third, the inconsistency between the goals of the curriculum and industrial demands. The improvement measures for this were first, it was proposed to increase the proportion of public security subjects, second, to establish 4th Industrial Revolution technology convergence subject, and third, to establish a new subject that reflects the demands of the security industry.&#x0D; The meaning of the improvement plan presented above is that the curriculum of majors and departments related to security and security ultimately has a mutual influence with science of security and the security industry. In other words, as the decline of the curriculum can be seen as a decline of the science of security and the security industry, it can be seen that this suggests that intensive changes and efforts must be made in the current security and security-related majors and departments.
Pengenalan Bahasa Inggris dengan Metode Story Telling pada Anak Usia Dini di RA Bakti Telang Bangkalan Madura

This activity aims to introduce young children to English by using storytelling in classroom learning. This activity was carried out at one of the kindergarten schools in Bangkalan, Madura, namely RA Bakti Telang. The target participants were students in group B. Theory and practical methods were combined in this activity to stimulate young children's curiosity in learning English. The results showed that the storytelling method could increase young children vocabularies. This is proven based on the results of the pre-test and post-test comparative evaluation. Storytelling could make young children understand new vocabularies in English easier.
Introduction to Fuzzy Cognitive Maps

This chapter gives a short introduction to Fuzzy Cognitive Maps (FCMs). It starts with the origin and first applications of Cognitive Maps, then describes the theoretical background of FCMs. Based on the cognitive model, simulations can be performed in order to predict the dynamic behavior of the system and support decision making tasks. The widely applied variations of implementation details are also covered, including their effect on model properties and behavior. A simple example is given to help understanding the theoretical parts, and a short outlook is provided to the possible ways of model creation, too.
Facial Recognition-Based Entry System for Student Residence Halls: Enhancing Security and Accessibility

Protecting an organization from numerous threats both inside and outside is the primary function of the security system. Automated embedded systems have come a long way in the contemporary era and have shown to be highly beneficial in applications related to security and surveillance. Face recognition is one of the study fields in computer vision, which is commonly used in security systems for video surveillance. Even though facial recognition technology has advanced significantly and is employed in several significant applications, numerous challenges need to be solved. These challenges include changes in posture, occlusions, expression, aging, lighting, and other elements. Deep learning can be useful in these situations. By using several processing layers to develop data representations with multiple feature extraction layers, deep learning may achieve higher accuracy. With the purpose of providing better security for student residence halls, in this work, we present a real-time deep learning-based facial recognition system that can be used to identify an individual's identity and give a warning when the individual's face is not recognized in front of the system. Here, faces from the face database are matched in order to identify students based on a video of their arrival into the residence halls. This process begins with face detection and ends with face recognition. We used a Convolutional Neural Network (CNN) based model Multi-Task Cascaded Convolutional Neural Networks (MTCNN) for face detection and recognizing faces using the Google FaceNet model. The model was trained on around 3000 photos, taken by 30 distinct people.
The Effectiveness of Using Plotagon Story Media to Improve Listening Skills for Non-Arabic Speakers

Digital learning has many benefits and importance in today's information technology era. With digital learning, students can set the time and place of study according to their needs and preferences. This research has a problem formulation: how to use the Plotagon story in listening skill learning in Islamic Yunior High School 2 Surabaya, and how effective the use of the Plotagon story is in improving students' listening competence. The population of this study was all grade 7 students, totaling 278 students, while the sample was 32 students studying in grade 7F. This quantitative research collects data through tests, namely prates and posters, and then ends with a t-test analysis. The results significantly increased after students followed digital learning with Plotagon stories. This problem is expected to be developed in other learning domains, such as speaking, reading, and writing competencies.
A Mathematical Approach on the Use of Integer Partitions for Smurfing in Cryptocurrencies

In this paper, we propose the modelling of patterns of financial transactions - with a focus on the domain of cryptocurrencies - as splittings and present a method for generating such splittings utilizing integer partitions. We further exemplify that, by having these partitions fulfill certain criteria derived from financial policies, the splittings generated from them can be used for modelling illicit transactional behavior as seen in smurfing.
The Social Science of the COVID-19 Pandemic

Abstract The book begins by overviewing the timeline of the pandemic and how it affected life, followed by a discussion of the ethics and legal aspects of the pandemic. It then discusses behaviors during the pandemic (e.g., social distancing, protesting) before discussing experiences during the pandemic (e.g., prejudice, well-being, stress, joblessness, family changes). Next, the book discusses outcomes after the pandemic (e.g., global outcomes, societal outcomes, and individual outcomes; these outcomes might be related to shifts in the economy, health, morality, politics). To compliment these theory-based sections, Section Five discusses best practices for conducting future studies during or about the pandemic.
Correction: Specialty detection in the context of telemedicine in a highly imbalanced multi-class distribution

[This corrects the article DOI: 10.1371/journal.pone.0290581.].
A Design Thinking Based Study to Assess the Effectiveness of Computer Assisted Teaching on Knowledge and Attitude Regarding Organ Donation Among Non-Health Professional Students at Selected College in Coimbatore

Design thinking is generally defined as an analytic and creative process that engages a person in opportunities to experiment, create and prototype models, gather feedback, and redesign. Design Thinking Approach is adopted to carry out the research to correlate the knowledge and attitude among non-health professional students. Objectives: (a) To assess the pre-test and post-test level of knowledge and attitude regarding organ donation among non-health professional students. (b) To assess the effectiveness of computer assisted teaching on knowledge and attitude regarding organ donation among non-health professional students. (c)To find out the association between post-test level of knowledge and attitude regarding organ donation and the selected demographic variables among non-health professional students. (d)To assess the correlation between knowledge and attitude regarding organ donation. Methodology: The research design used was a pre-experimental one group pretest and posttest design. The samples for the study were chosen by using convenient sampling technique, The sample size was 50. Results: Karl Pearson correlation test was used. It reveals that there is effectiveness present in the group. Conclusion: Organ donation is a huge public health concern worldwide. The biggest advantage to organ donation is, it saves lives that would otherwise be lost. A single organ donor has the chance to save the lives or improve the quality of life for several people. So, the organ donation should be encouraged and the people should be motivated to donate their organs by conducting periodical educational programmed regarding organ donation.