Reviewerly/exHarmony huggingface dataset:
Implementation of Artificial Neural Network Method for Estimating Connected Power and Electric Energy Consumption

Abstract—Electricity is vital for modern society’s welfare. Daily electricity usage depended on the customers’ type. Hence, there was a difference between the connected power with consumption. Therefore, there needed an estimation method for long-term connected power and energy consumption to improve the safety of energy management and operation plan for the generator. This research used the Artificial Neural Network method with a backpropagation algorithm model to estimate the connected power and electricity consumption. This method has the advantage of following past patterns after the training process. This research used data such as total population, Gross Regional Domestic Product, total customers, produced energy, remaining energy, distribution loss, total transformer, peak load, and load factor as the independent data. The energy consumption and connected power served as the dependent data. The data was taken from Srengat Network Service Unit, East Java, for ten years, which started in 2008. This research used literature study, information and data collection, information and data process, data estimation and analysis, and conclusion as the procedures. Based on the results, the best network structure was 9-9-2 with the 10-6 goal, 0.9 momentum value, and 0.15 learning rate to produce the smallest Mean Squared Error of 0.00442 in 2015, Mean Absolute Percentage Error of 7.88% for the connected power, and 11.27% on electricity consumption target.
Manajemen Sistem Informasi Pembelajaran

The purpose of this study was to determine the management of learning information systems. The method used is the literature study method, namely by collecting material, data and information from books, journals and articles relating to the issues discussed. The results of the study, with a good SIM, developers with the implementation of computer-based SIM learning activities can be completed quickly and precisely in order to achieve organizational goals. This is due to the fact that computer-based management information systems have advantages in managing information, namely speed, quantity, repetitive, complexity, high accuracy, and other advantages so that it can support the development of an organization, Conclusions, management information systems can support the development of learning.&#x0D; Keywords: Learning, Management of Information Systems
PENERAPAN BIMBINGAN KELOMPOK DENGAN MENGGUNAKAN TEKNIK MODELING UNTUK MENINGKATKAN MOTIVASI BELAJAR SISWA UNDERACHIEVER

The purpose of this study was to determine the effect of group guidance services with modeling techniques on increasing learning motivation of underachiever students. The research method used is a quasi experiment. The population of this study were students of class XI MIPA who had an IQ of ≥ 130, totaling 30 students. The sampling technique used was purposive sampling and a sample of 13 students was obtained. The data collection method used was a psychological scale in the form of a learning motivation scale. The results showed that the students' motivation before being given the modeling technique group guidance service was in the low category with an average percentage of learning motivation of 45%. After being given guidance service the modeling technique group was in the high category with a percentage of 84% so that there was an increase of 39%. In addition, the data obtained through the Wilcoxon pairs match test with n = 13, 5% significance level obtained Tcount&gt; Ttable (90&gt; 21) or Ha was accepted and Ho was rejected. This means that group guidance with application modeling techniques has an effect on increasing learning motivation of underachiever students in class XI MIPA students of SMAN 1 Cisarua, West Bandung Regency, 2019/2020 academic year.Keywords: Motivation to learn, underachiever; group guidance, modeling techniques.
The level of formation of professional and ethical competence of social teachers at the constituating stage of experiment

The article discusses the results of the ascertaining stage of an experimental study on the implementation of a model for the formation of professional and ethical competence of future social teachers in terms of training in a magistracy through a set of pedagogical conditions and a number of interconnected blocks (conceptual, organizational, technological and effective), as well as stages (preparatory, informational, technological, effective). In the context of this study, a substantial description of the ascertaining stage of an experimental study is described, diagnostic tools are provided that were used at this stage to determine the initial level of formation of special competencies (moral and axiological, moral and regulatory, moral and reflexive) that we identified as an effective part of professional development. ethical competence of social educators. The results of a diagnostic study of the levels of development of special competencies (moral and axiological, moral and regulatory, moral and reflexive) are presented.In the pedagogical experiment, 192 graduate students took part, which were divided into two groups: the control group (96 people) and the experimental group (96 people). The educational process in the control group was built in the traditional form, and in the experimental one it was aimed at introducing and testing the model of the formation of the professional and ethical competence of the social teacher.According to the results of an experimental study, both the experimental and control groups of the threshold and base level of professional ethical competence were established to dominate, which was the basis for the further implementation of the formative stage of the experiment to introduce pedagogical conditions aimed at the targeted development of undergraduates in the direction of training 44.03.02 "Psychological and pedagogical education" professional and ethical competence.
Atypical Character Recognition Based on Mask R-CNN for Hangul Signboard

This study proposes a method of learning and recognizing the characteristics that are the classification criteria of Hangul using Mask R-CNN, one of the deep learning techniques, to recognize and classify atypical Hangul characters. The atypical characters on the Hangul signboard have a lot of deformed and colorful shapes beyond the general characters. Therefore, in order to recognize the Hangul signboard character, it is necessary to learn a separate atypical Hangul character rather than the existing formulaic one. We selected the Hangul character ‘닭’ as sample data and constructed 5,383 Hangul image data sets and used them for learning and verifying the deep learning model. The accuracy of the results of analyzing the performance of the learning model using the test set constructed to verify the reliability of the learning model was about 92.65% (the area detection rate). Therefore we confirmed that the proposed method is very useful for Hangul signboard character recognition, and we plan to extend it to various Hangul data.
EFL Students’ English Listening Comprehension Problem: A study of English Teacher Education Program

Listening comprehensively is one of the way to build EFL students’ Listening skill, however, they still got problem in different phase of listening. The aimed of the study to identified the listening comprehension problem of EFL students during take English teacher program, the data was collected from Muhammadiyah university students in Kendari. This descriptive study used the listening comprehension problem questionnaire. The result of the study showed that the students still got difficulty in all three phases of listening problem, they are perception, parsing and utilization, moreover, the highest problems was in perception problem. So this problem is highly influence their quality of listening skill. This findings are expected to be a good implication for the lecturer in designing course and listening teaching strategy.
A Remote Sensing Image Registration Method Based on Multi-features

Remote sensing image registration technology has important significance in the field of image processing. The registration technology of SAR images has been a hot research in this field, and it is also a challenge. Aiming at this difficulty, this paper proposes a fusion feature algorithm, which combines gradient, grayscale, texture, geometry and other features in heterogeneous remote sensing images for comprehensive matching. Compared with the traditional single feature, the improved detector has good performance and registration accuracy in SAR image and visible light image registration.
PENERAPAN ALGORITMA NAIVE BAYES DAN PARTICLE SWARM OPTIMIZATION UNTUK KLASIFIKASI BERITA HOAX PADA MEDIA SOSIAL

Social media is the most effective way to facilitate fast information, unfortunately, there are some elements who use social media to add hoax or deception to give misleading opinions to the public. Therefore a method is needed to classify hoax news and non-hoax news on social media. Naive Bayes is a simple classification algorithm but has high qualifications, but Naive Bayes has a very sensitive shortcoming in the selection of features and therefore the Particle Swarm Optimization method is needed to improve the expected results. After conducting research with the Naive Bayes method and the Naive Bayes method based on Particle Swarm Optimization, the results obtained are Naive Bayes yielding 74.67% while the Naive Bayes based on Particle Swarm Optimization with an accuracy value of 85.19%. The purpose of this study is to see a large comparison. Swarm Optimization particles to improve accuracy in the classification of hoax news on social media using the Naive Bayes classifier. After using Particle Swarm Optimization the test results increased by 10.52%.
Proposed Algorithm For Using GLCM Properties To Distinguishing Geometric Shapes

In this research, an algorithm was used to look at the characteristics of a set of images for geometric shapes and then to classify them into totals based on four characteristics obtained from the co-occurrence matrix (energy, contrast, correlation and homogeneity).Studying the above four characteristics in detail and then presenting a complete presentation on the extent of their effect on the distinctive characteristics of the geometrical shapes.The adopted algorithm shows that the above four qualities can be new features of geometric shapes in digital images.The results of the practical application of the proposed algorithm show that the three features of homogeneity, energy, and contrast give a topical distinction to the shape, but the correlation property is weak in the distinction of shape.The algorithm was programmed using MATLAB R2010a for Windows 7 operating system on the computer that has the following specifications: (Processor Intel (R) Core (TM) i5, CPU 640 M & 2.53 GHZ, RAM 6GB).
A Requirements engineering process for a quality model in Cuba

A high percentage of projects worldwide fail or are canceled due to incorrect requirements engineering. Incorporating good practices into this process provides the appropriate mechanism to understand and analyze what stakeholders want and need. It also allows to evaluate and negotiate a reasonable solution, specify, validate and manage the requirements as they are transformed into a functional system. The objective of this research is to elaborate a process of Requirements Engineering for the Quality Model for Software Development that contributes to raise the percentage of successful projects, in Cuban´s software development organizations, regarding the fulfillment of the agreed requirements. The solution proposal contains specific requirements and support elements (graphic and textual description of the process), divided by the three levels of maturity proposed by the Model. In order to reach the proposed goal, a bibliographic review was made on the requirements engineering discipline, as well as interviews and surveys to roles related to this activity in the software development organizations of Cuba. The solution was evaluated by experts in a focus group and put into practice, as a pilot, in three organizations, it was also measured the satisfaction of the users who used it using the Iadov technique.
Sentiment Analysis: An empirical comparison between various training algorithms for Artificial Neural Network

The proliferated increase in the commercial benefits of sentiment analysis accumulated a huge interest in the domain of sentiment classification. Sentiment analysis categorises a given text into positive or negative class. In this paper, we present an empirical comparison between different training algorithms gradient descent (GD), gradient descent with momentum backpropagation (GDM), gradient descent adaptive learning rate backpropagation (GDA), gradient descent with momentum and adaptive learning rate backpropagation (GDX), and Levenberg-Marquardt backpropagation (LM), used for training the neural network for the domain of sentiment classification. The performance of all the methods is compared and evaluated using three balanced binary datasets from various domains with different features using various performance metrics such as accuracy, precision, recall, f-score, mean squared error, and training time. The experiments are performed five times with different random seed values using 10-fold cross-validation. The results indicate that GDX and LM outperform other methods in terms of classification accuracy.
RESEARCH ON BEHAVIORAL MOTIVATION INFERENCE METHOD FOR GEOGRAPHICAL SPATIOTEMPORAL LARGE DATA

Abstract. Along with the rapid development of Internet technology, GNSS technology and mobile terminals, a large amount of information including geographical location and time attributes has been generated. Faced with large and complex Internet geospatial data, how to quickly and accurately extract valuable reference information becomes an urgent problem to be solved. And the user's demand for personalized information of recommendation information is getting stronger and stronger, and researching efficient and accurate personalized recommendation system has good application value. In this paper, based on the application requirements of personalized recommendation information, the GIS platform and related recommendation algorithms are used to fully exploit the user and location based on geographic space-time big dataIt is divided into user explicit interest and user implicit interest, and then establishes a scientific and efficient user behavior motivation prediction model based on geographic situation. User interest information can be obtained from explicit interest information, implicit interest information and geographic situation interest information. Geographical environment, geographic location and other related context information. By introducing time factors, it is used to update and improve the user real-time interest model to achieve accurate prediction of user behavior motives under geographic spatio-temporal big data. Use Apriori algorithm to calculate the support and determine the current Frequent itemsets of user interest in geographic context, using frequent itemsets to generate strong association rules, and realizing the analysis of user behavior motives based on geography context. For geographic spatio-temporal big data, this paper proposes a personalized hybrid recommendation algorithm, which is based on users. Effective combination of collaborative filtering algorithms and association rules for geographic context-user behavioral interest adaptation.
Penerapan Good School Governance (GSG) Dan Pengaruhnya Terhadap Efektifitas Pengelolaan Bantuan Operasional (BOS) Sekolah Dasar Kota Blitar

This study aims to determine the effect of the application of good school governance on the effectiveness of the management of elementary school operational assistance. The method used is descriptive analysis method with a quantitative approach. The sample used saturated samples by showing all treasurers of primary school operational assistance as many as 48 people, data collected by questionnaire techniques while data analysis used multiple linear regression techniques. The results showed that participation had a positive and significant effect on the effectiveness of the management of school operational assistance, transparency had a positive and significant effect on the effectiveness of the management of school operational assistance, while accountability separately did not have a positive and significant effect on the effectiveness of the management of school operational assistance but together participation, transparency and accountability have a positive and significant effect on the effectiveness of managing school operational assistance.
Automatic Panorama Generating of substations with Primary and Secondary Equipment

Substations are described in detail in the Substation Configuration Description (SCD) file in Substation Configuration Language (SCL) for intelligent substations according to IEC61850 standard, including primary equipment and topology, secondary smart equipment, measurement and communication, etc. After the SCD file of the downstream substation is got, the corresponding grid logic view for the upstream main station system can be established theoretically. The SCD file is analyzed in this paper, the relationship of primary and secondary equipment model objects of substations are constructed, generating standard spatial point and line model and automatically identifying the wiring of primary equipment, supporting the substation model description according to IEC61970/CIM. With automatic layout and routing technology, the grid panorama is generated, and the relationship of secondary equipment automatically superimposed based on the primary equipment model view is drawn. This technology has important and broad application prospects for easy and convenient maintenance and management of intelligent substations, improving the integration of upstream and downstream information, and intelligent dispatching of grid.
Pengembangan Lembar Kerja Siswa (LKS) Menggunakan Contextual Teaching and Learning (CTL) Berbasis Kota Lubuklinggau

The purpose of this study was to develop student worksheets (LKS) using the Lubuklinggau city-based Contextual Teaching and Learning (CTL) on the set material in class VII according to the 2013 curriculum and find out the quality of worksheets developed from the validity, practicality and potential effects of using LKS. The research method used is Research and Development (R&amp;D) research. Development of worksheets using a 4-D model that was modified to a 3-D model. This model consists of 3 stages, namely: the stage of defining (Define), design (Development) and development (Develop) without including the spread (Disseminate) due to time constraints. The results of the study are based on the assessment analysis by the three experts namely: linguists, material experts, and media experts showing that the worksheet fulfills valid criteria with an average score of 3.12. While the results of the analysis of student response questionnaire assessments obtained that the student worksheets meet practical criteria with an average score of 3.55 and have a potential effect of 27 students (84.37%) whose grades reach mastery learning, while 5 students (15.63%) not reached mastery learning. In conclusion, the development of student worksheets using the contextual Teaching and Learning (CTL) based on the city of Lubuklinggau is declared valid, practical and has a potential effect on students' mastery learning.&#x0D; Keywords: Contextual Teaching and Learning, Student Worksheet
Publisher Correction: Study on the Visualization of Pigment in Haematococcus pluvialis by Raman Spectroscopy Technique

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Approach to cost-of-quality management in pharmaceutical manufacturing

Introduction: The costs related to pharmaceutical production, including quality costs are a substantial and persistent part of the costs of pharmaceutical companies. Moreover, there are a number of activities in pharmaceutical production, originating from regulatory requirements to ensure the quality of pharmaceuticals, which do not contribute to real value; however, they consume time, materials and human resources. One of them is the operation of an effective quality management system in accordance with the requirements of the Good Manufacturing Practice for pharmaceuticals. The adherence to all regulatory requirements related to pharmaceutical production is quite costly and constitutes a substantial part of the budget of pharmaceutical companies. There are, however, opportunities for cost reduction which can increase profit without extra investments, ensuring at the same time regulatory compliance. Materials and Methods: A scientific literature review was performed with regards to cost management in pharmaceutical production. On the grounds of the analysis, personal experience and observation, some factors were identified which could impact the costs of pharmaceutical manufacturers and an approach for their management was developed, aiming to reduce the costs and improve company performance. Results: The costs for materials, equipment, production process, personnel, control and facilities were identified as major sources of production costs in the pharmaceutical industry, which affect the quality costs. The costs were classified by type and specific approaches for cost reduction were proposed; the expected effects of this reduction on the company results were assessed, e.g. reduction of total costs, losses and product unit costs, reduction of the duration of production, reduction of downtime and the time required for preparation and effective use of facilities, as well as quality costs (for assessment, prevention, internal and external issues/failures). Conclusion : The proposed approaches for cost reduction can be used as a manual for cost assessment, as well as for the suitability and prioritization of the relevant approaches for their reduction. They have a major impact on the “good quality” costs, related to assessment and prevention; they also contribute to the reliability of quality assurance, thus reducing the costs for its application for handling of internal and external issues. The proposed approaches have a synergistic effect on quality costs reduction and on the improvement of company performance.