Reviewerly/exHarmony huggingface dataset:
Sistem Informasi Geografis (SIG) Titik CCTV Di Kota Jambi Berbasis Web

Requests for information regarding Closed Circuit Television (CCTV) in public areas by the people of Jambi City through the complaint channel, are increasingly being received by the Jambi City Communications and Information Office. The installation of Closed Circuit Television (CCTV) in public areas in Jambi City is one of the service innovations for the community in order to strengthen law enforcement, public order and public convenience and at the same time realize the Jambi City Government's Smart City program. CCTV installations in Jambi City have been carried out in various areas of Jambi City such as in various parking areas in government offices, at crossroads, and red lights. Even private business actors also support the installation of CCTV in their respective business areas. Advances in GIS technology can be applied to mapping the distribution of CCTV points in the city of Jambi to help collect information on the distribution of CCTV points in various public areas of Jambi City electronically so that they can improve excellent service for the community in the field of security and public comfort both for business actors and for visitors who came to the city of Jambi. So the final result of this research is the proposed design of a Web-Based Geographic Information System (GIS) application for CCTV Point in Jambi City. The system development method used is Prototype using Use Case Diagram modeling tools, Activity Diagrams, and Class Diagrams. This research is expected to provide complete information about the distribution of CCTV points in the Jambi City area, and become the initial foundation for integrating all CCTV management in Jambi City.
Designing a Chatbot Based on Full-Text Search and 3D Modelling as a Promotional Media

A chatbot is an application that can respond and reply to questions from the questioner, without any human being involved. In general, chatbots are used to simplify and improve public services, so that users can get information quickly and directly, without time constraints. This research objective is to create promotional media in the form of chatbots in the 3D Virtual Tour to answer questions and provide general information about an object while providing more attractive visuals for users. The method used to run the chatbot is Full-Text Search. Full-Text Search is an efficient and powerful search method that is built into MySQL by default, which works by matching words between keywords and patterns in the database. This study succeeded in applying the Full-Text Search method as a search technique for chatbot patterns in the 3D Virtual Tour application at Buddhi Dharma University as a promotional medium. Evaluation using the User Acceptance Test (UAT) method yielded a value of 83.45% in a very satisfying category for users.
Sistem Informasi Akademik SMKN 6 Muaro Jambi

The development of information technology, especially the use of the system allows the data processing become more efficient, faster and accurate than the system that is still done manually. One is the Academic Information System is used to provide ease of data processing. With a design that takes into account the facility and understanding of the human resources that will use this information system is expected to run well if it will be implemented. This study proposes an analysis and design of a prototype of a system of academic information in SMKN 6 Muaro which provides convenience in data processing and obtain information.
Quality Evaluation of Innovation and Entrepreneurship Education Based on Modelling of Students’ Behavior Sequences

In the Innovation and Entrepreneurship (I&amp;E) education of some higher vocational colleges, there’s a common problem: serious disconnection between professional education and practical education, which may result in poor quality of I&amp;E education. With the help of I&amp;E education quality evaluation, we can figure out the distribution and utilization of education resources, discover and solve problems during the teaching process in time, and optimize and adjust teaching content and methods in a targeted manner. Student behavior analysis can reveal the actual needs and questions encountered by students during I&amp;E education, thereby attaining more pertinent and pragmatic evaluation results. For this reason, this paper aims to study the I&amp;E education quality evaluation by means of modelling students’ behavior sequences. At first, a student I&amp;E behavior sequence feature extraction module was created based on attention mechanism, and the student I&amp;E ability level feature extraction layer and student I&amp;E ability level feature evolution layer contained in the module structure were introduced in detail. Then, the data sources of I&amp;E education quality evaluation based on students’ I&amp;E behavior analysis were given, the I&amp;E behavior sequences of students were modeled based on the single-sequence first-order linear differential equation model GM(1,1), and the established model was applied to I&amp;E education quality evaluation. At last, experimental results verified the validity and accuracy of the proposed method.
Brain data and driver's attention during simulated drive

The attention of drivers is a serious issue and one of the critical factors of road safety. The question is whether the electrical activity of the human brain can be correctly measured/collected and utilized to monitor and interpret the driver's attention during simulated driving. This article summarizes four experiments that have been designed, performed, and evaluated in the neuroinformatics laboratory at the University of West Bohemia. Simulated driving under various conditions in a car simulator was organized, and electrophysiology, mainly electroencephalography, data were collected from participants/drivers. The results include experience with the design of such experiments and the suitability of methods based on the collection and interpretation of electroencephalography data for driver attention detection.
Effect of Giving Oxygen Therapy Using Non-Breathing Mask on Changes in Intraparsial Pressure Value in Head Injury Patients at Home Grandmed Hurt of Lubuk Pakam

Objective: Head injury is a traumatic disturbance of brain function accompanied or without brain bleeding with a sudden blow or impact to the head without loss of consciousness. Oxygen is a gas component and a vital element in metabolic processes to maintain the viability of all body cells normally by inhale the room air with each breath. Knowing the value of intrapartial pressure by administering non-breathing mask oxygen with differences in intrapartial pressure values ​​in head injured patients at Grandmed Lubuk Pakam Hospital. The research method used a purposive sampling technique with a total sample of 21 respondents, while the research instrument used an observation sheet with an oximetry measuring instrument. Data analysis used bivariate analysis, namely the Paired Sample T-Test. Results; The results of the Bivariate test with the Paired Sample T-Test proved that there was an effect of giving non-breathing mask oxygen therapy on intrapartial pressure values ​​in head injured patients as evidenced by the p value: 0.00 &lt;0.05. Conclusion; There is an effect of giving threapy oxygen using a non-breathing mask on changes in intrapartial pressure values ​​in head injured patients at Grandmed Lubuk Pakam Hospital.
A Proposed Model for Persian Stance Detection on Social Media

Stance detection is a recent research topic that has become an emerging paradigm of the importance of opinion-mining. It is intended to determine the author’s views toward a specific topic or claim. Stance detection has become an important module in numerous applications such as fake news detection, argument search, claim validation, and author profiling. Despite considerable progress made in this regard in languages like English, unfortunately, we have not made good progress in some languages such as Persian, where we are confronted with a lack of datasets in this area. In this paper, two solutions are used to address this issue: 1) the use of data augmentation and 2) the application of different learning approaches (machine learning, deep learning, and transfer learning) and a meaningful combination of their outcomes. The results show that each of these solutions can not only enhance stance detection performance, but when both are combined, a very significant improvement in the results is achieved.
ACCURATE CELL SEGMENTATION IN BLOOD SMEAR IMAGES BASED ON COLOR ANALYSIS AND CNN MODELS

Abstract. Nowadays, automated blood cell evaluation play a major role in the classification and diagnosis of diseases. Despite the many possible ways to segment blood cells, the recognition efficiency remains insufficient, especially when different cell types overlap. Also, one should not forget about the cells structure complexity. Image segmentation and image classification are the main stages of this problem. At the same time, segmentation of blood smear images is considered the most important stage in automated disease detection systems. Often cell segmentation in blood smear images is performed as a separate mapping for white blood cells and red blood cells. We propose another problem statement that uses the capabilities of supervised and unsupervised CNNs for the semantic segmentation of objects of different sizes and shapes. CNN has encoder-decoder architecture and builds a pseudo-color map. We tested several CNN models using different color spaces converting initial images from RGB to Lab, HSV and CMYK color spaces and obtained promising experimental results for several microscopic datasets such as CellaVision DM96, All-IDB and Blood Cell Detection.
Guessing Game Effectiveness for Improving Student Speaking Skill in Elementary School

English speaking skills are very important because Game is Communicative Language Teaching (CLT) which will create an atmosphere that will increase students' desire to learn languages. However, there is an assumption that learning with games makes students undisciplined and difficult to do because it requires a long time and many teachers. This study aims to determine the effect of learning English using a guessing game method on the speaking skills of elementary school students. This research is a one-group pre-test post-test design that was implemented at the Islamic Elementary School in Yogyakarta. The research sample consisted of 68 elementary school students in grade 6 in 2019. The sampling technique used was total sampling. The research was conducted by classroom action with intervention in the form of learning English with guessing games for 3 months in two cycles. The measured learning outcomes are speaking skills in the form of pronunciation, vocabulary, grammar, fluency, and understanding. the assessment was carried out before and after the intervention. The data were processed using the Wilcoxon test. The results showed that the students' speaking skills improved after going through the learning process with guessing games. The speaking skills that have improved significantly are pronunciation, vocabulary and fluency. Grammar and comprehension improved but not significantly. The conclusion is that the guessing game can improve the students' speaking skills even though it has not covered all its aspects
Netflix Stock Price Trend Prediction Using Recurrent Neural Network

Abstract— Stocks are investments that have dynamic movements. Stock price changes move every day even hourly. With very fast changes, stock prices require predictions to be able to determine stock market projections. Predictions are used to reduce risk when making transactions. In this study, predictions of stock price trends were made using the Recurrent Neural Network (RNN). The approach taken is to perform a time series analysis using the RNN variance, namely Long Short Term Memory (LSTM). Hyperparameter construction in the LSTM model testing simulation can estimate stock prices with maximum percentage accuracy. The results showed that the prediction model produced a loss function of 0.0012 and a training time of 73 m/step. The evaluation was carried out with the RMSE which resulted in a score of 17.13325. Predictions are obtained after doing machine learning using 1239 data. The RMSE and LSTM models are calculated by changing the number of epochs, the variation between the predicted stock price and the current stock price. Computations are carried out using a stock market dataset that includes open, high, low, close, adj prices, closes, and volumes. The main objective of this study is to determine the extent to which the LSTM algorithm anticipates stock market prices with better accuracy. Code can be seen at iranihoeronis/RNN-LSTM (github.com) Keywords— Stock Prediction, Time Series, Recurrent Neural Network (RNN), Long Short Term Memory (LSTM).
PRESUPPOSITION ANALYSIS OF CHARACTER’S UTTERANCES IN CAMP ROCK MOVIE

This descriptive qualitative research aimed to discover different types of presupposition occurred in the Camp Rock movie. To sort the data into categories according to the types of presupposition, the theory of Yule (1996) was applied. Existential presupposition, factive presupposition, lexical presupposition, structural presupposition, non-factive presupposition, and counterfactual presupposition are the six types of presupposition. Observational and non-participatory techniques were used to obtain the data. Additionally, the data was analyzed using the pragmatic identity technique and pragmatic competence-in-equalizing data. To get data from the source, a number of procedures are taken. The researchers started by downloading the movie’s script. The researchers next watched the movie on the internet while highlighting the utterances that had the occurrence of presupposition. The result of this research revealed that there were 15 utterances of presupposition in Camp Rock movie. There were existential presupposition with 4 data, factive presupposition with 1 data, lexical presupposition with 5 data, structural presupposition with 4 data, and counterfactual presupposition with 1 data. The most dominant presupposition type appeared in the movie was lexical presupposition, because most of the characters declared meanings which were customarily interpreted with presumptive statement and had another meaning was recognized.
THE DEVELOPMENT OF PROFESSIONAL MOTIVATIONS OF THE FUTURE PSYCHOLOGISTS IN THE CONTEXT OF SITUATIONAL MODELING

Abstract: key concepts about professional motivation are considered. An overview of theoretical and empirical methods of diagnosis and interventions to develop professional motivation has been made. The structural model of the process of formation and/or development of professional motivation in students of psychologists with the help of situational modeling is displayed.
Implementation of the Storytelling Method to Improve Early Children’s Language Skills

Language for early childhood is important as a means of thinking, listening, speaking, and reading and writing. The purpose of this study was to describe the application of an appropriate and effective storytelling method so that it can improve early childhood language skills in group B at Baitul A'la Lubuklinggau Kindergarten. This study used the Classroom Action Research (CAR) method or action classroom research using 3 cycles. Each cycle includes the stages of planning, implementing, observing, and reflecting. The subjects in this study were early childhood in group B of Baitul A'la Lubuklinggau Kindergarten, totaling 20 children. The results of the study showed that there was an increase in language skills from cycle I and cycle III seen from the class averages of (2.30), (3.00), (3.60) and an increase in mastery of learning outcomes in language skills from cycles I and cycle II by 30% increased in cycle II to 75% and cycle III to 100%. The application of an effective storytelling method to improve language skills for early childhood in group B of Baitul A'la Lubuklinggau Kindergarten, this is reflected in an increase in communication skills and social action.
USING CRYPTOCURRENCIES IN FINANCING SUSTAINABLE DEVELOPMENT GOAL PROJECTS: SWOT ANALYSIS

The interest and adoption of cryptocurrencies, such as Bitcoin and Ethereum, have significantly increased as a medium of payment and investment. At the same time, the international community has set a list of Sustainable Development Goals (SDGs) to be achieved by 2030, which includes eradicating poverty, protecting the planet, and ensuring peace and prosperity for everyone. One of the most significant challenges in achieving these SDGs is financing the necessary projects to implement them. Traditional financing sources, such as government budgets and private investments, may not be sufficient to cover the enormous costs associated with achieving the SDGs. Therefore, there is a need to explore alternative financing mechanisms to support the implementation of the SDGs. Cryptocurrencies represent a potential alternative source of funding for SDG projects. However, the lack of regulation and the high volatility of cryptocurrency prices may create uncertainty and risk for investors and project stakeholders. Examples of the use of cryptocurrencies in various SDG projects to enable fast and low-cost cross-border transactions are presented. The feasibility of using cryptocurrencies as a financing mechanism for SDG projects, a comprehensive SWOT analysis of the use of cryptocurrencies in financing SDG projects, potential problems and opportunities related to the use of cryptocurrencies for financing SDG projects, practical recommendations for policy makers, project developers and investors who are interested in using cryptocurrencies for financing SDG projects are discussed in the article. To address this issue, this article aims to conduct a SWOT analysis to evaluate the strengths, weaknesses, opportunities, and threats of using cryptocurrencies as a financing mechanism for SDG projects. The analysis will provide valuable insights into the potential benefits and drawbacks of utilizing cryptocurrencies for SDG project financing and identify strategies to mitigate risks and maximize opportunities. Ultimately, this research aims to contribute to the broader conversation around alternative financing mechanisms for sustainable development projects.
The Effect of Grammar Mastery and Self-Esteem towards Students’ Speaking Skill

The study’s goal is to discover and to investigate how students’ grammatical knowledge and sense of self-worth influence their capacity for effective oral expression empirically. The researchers adopted a quantitative strategy and used a survey to gather information. Seventy-three students were selected at random from the population of students at selected Private Vocational High Schools in East Jakarta. In order to verify the hypotheses, a multiple regression analysis was performed. The study yielded the following findings. Self-Esteem and grammatical competence go hand in hand when it comes to a student’s ability to communicate clearly. The fact shows that Sig. = 0.000 &amp;lt; 0.05 and Fo= 25.662. Students' fluency with grammar has a major bearing on how well they can express themselves verbally since Sig. = 0.000 &amp;lt; 0.05 and to= 3.788 demonstrate this to be the case. Students' confidence in their own abilities has a major bearing on how well they can express themselves. This is evidenced by the congruence between the values Sig. = 0.000 &amp;lt; 0.05 and to= 4.921.&lt;p&gt; &lt;/p&gt;
Decision Support System for SmartPhone Selection with AHP-VIKOR Method Recommendations

Produce products that have various features and diverse functions, which are able to provide convenience with the reliability of their features and functions. The advantages possessed by SmartPhone become more confident for users to assess the level of product intelligence, the more trustworthy. The purpose of this research is to provide additional knowledge on the selection of SmartPhone to the user in having a product with various benefits. The more criteria that become a barometer, the more difficult it is to choose a product in the form of a SmartPhone. Thus, the right method is needed to perform the selection of the SmartPhone. There are several methods offered to carry out the selection process for SmartPhones, namely the Analytic Hierarchy Process (AHP) method combined with the VIKOR elimination method. Both of these methods are very supportive in the selection process with many types of criteria and their meanings against these criteria. A number of criteria that serve as a barometer for selecting object-based applications are Operating System, Processor, Internal Memory, External Memory, Back Camera, Front Camera, Battery, Cassing Model, Screen Size, Wight and Price. Of the eleven criteria have two different characteristics of understanding. The results of this study can be seen explicitly on the selection of SmartPhones through the acquisition of the smallest Qi index with the three highest ratings, namely the first ranked Samsung Galaxy A3 (0.00) the second is the Xiaomi Mi 4C with an index of 0.19, the third is the Lenovo Vibe K5 Plus with index 0.31. Thus it can be said that the collaboration of the AHP and VIKOR Elimination methods is able to provide optimal decision-making support.
Effect of Pressure on Salt Water Spray as Alternative Methods of Desalination Using Droplet Evaporation-Air Entrainment

It is necessary to utilize desalination technology to clear the water available, including seawater, to meet the increasing need for clean water due to population growth.Several desalination methods, such as thermal methods, membranes, freezing g, and ion exchange, continue to be developed but have not overcome some deficiencies.Therefore, new alternative desalination methods with droplet atomization, which utilizes the air entrainment phenomena, are being developed.Research on non-dimensional fluid atomization is the basis for designing this method.The study used brine pumped through a nozzle with a small diameter to become mist or vapor.This study carried out variations of research parameters on the configuration of the experimental apparatus in the form of pressure, the diameter of the nozzle, and the number of nozzles.Quantitative data from experimental results obtained from measurement instruments and qualitative data in videos obtained using a camera are to be processed into quantitative data using image processing.The results showed that pressure affects the characteristics of a full cone-shaped water spray.It was found that the best spray system configuration with two nozzles with a diameter of 0.5 mm in a pressure of 9 bar.
Three-qubit Deutsch-Jozsa in measurement-based quantum computing

Measurement-based quantum computing (MBQC), an alternate paradigm for formulating quantum algorithms, can lead to potentially more flexible and efficient implementations as well as to theoretical insights on the role of entanglement in a quantum algorithm. Using the graph-theoretical ZX-calculus, we describe and apply a general scheme for reformulating quantum circuits as MBQC implementations. After illustrating the method using the two-qubit Deutsch-Jozsa algorithm, we derive a ZX graph-diagram that encodes a general MBQC implementation for the three-qubit Deutsch-Jozsa algorithm. This graph describes an 11-qubit cluster state on which single-qubit measurements are used to execute the algorithm. Particular sets of choices of the axes for the measurements can be used to implement any realization of the oracle. In addition, we derive an equivalent lattice cluster state for the algorithm.