Reviewerly/exHarmony huggingface dataset:
DEVELOPMENT OF CREATIVE POTENTIAL - AS A PSYCHOLOGICAL MEANS OF SOCIALIZING THE TEENAGER

. The article is devoted to the problem of developing and socializing the teenagers’ creative potential. A description of main features and problem of creative potential has been developed. A system of psychological support work is proposed aimed at the correct socialization of teenagers by identifying effective ways to develop their creative potential. The ability of a person to do something is distinguished by the fact that it is characteristic of his personality that plays a leading role in performing the particular activity, manifests itself in the speed, depth and stability in solving a particular approach. The indicated factors of teeanegars’ ability group the qualities that correspond to this sphere. They are: intelligence, creativity, motivation, the individual’s social adaptation. Psychological quality, which includes the teenager’s creative abilities and is determined by the emergence of creative potential, is a high indicator of the mind at the same time with the psychological and social sphere, which is determined by personality - motivational high cognitive need, contact with the environment, general cultural and interpersonal relationships. These composite parts reflect the child’s creative potential which means that he does not need a high indicator for all four factors, but a high indicator for some ability is sufficient. And the rest of the factors are carried out in the course of training and development. Development of creative potential- arises as a result of motivational guidance of the child’s cognitive abilities, social adaptation.
THE ESSENCE OF THE FORMATION OF RESEARCH COMPETENCE IN THE TRAINING OF FUTURE TEACHERS

In the given article the theoretical basis of forming future teachers’ scientific-research competence is observed. The following notions as «Research», «competence», «research competence» are defined. The structure and types of competence in teachers’ scientific works are defined from the scientific theoretical point of view. The research questionnaire according to the future teachers’ scientific competence are held and it has been analyzed. The students’ skills in mastering the scientific competence are identified (set goals, search, plan, conduct research, analyze, summarize, conclude, draw up results). The opportunities are opened for students to master the scientific competence, combine theory and practice in their future professional pedagogical activities. The research object was to research the requirements for the specialists who master the scientific competence and modern education system. In forming the pedagogical professional basis the students’ scientific, creative, inquisitive, research competence are scientifically substantiated.
Analisis Static Malware Menggunakan Algoritma Random Forest Machine Learning

Malware is a malicious software program that aims to damage or steal data from a victim's system. Malware analysis is needed to determine the performance of the malware. Static analysis was used for feature extraction from a total of 10 PEfiles, 5 malware files and 5 benign files. The random forest machine learning algorithm obtained an accuracy of 99.99%.
Analysis of River Flow Velocity Using Current Meter with Six-Tenths Method and Two-Point Method (Case Study of Ampal River, Balikpapan City)

Rivers have cross-sectional sizes in the form of longitudinal profiles, valley slopes, and cross sections. The size can change according to the base material, cliffs, and water discharge so each river has different characteristics. The flow velocity will affect the flow rate. This study aims to determine the flow velocity of the Ampal River and determine the differences between the methods used. Measurement of flow velocity in this study using a current meter with the six-tenths method and the two-point method. The fastest flow velocity obtained on average is at the point z/b = 0.5 or in the middle of the river, with the maximum speed being at Cross Section 4, with a depth of 1.29 m and a speed of 0.474 m/s.
AN ANALYSIS ON STUDENT'S DIFFICULTIES IN READING COMPREHENSION AT SMKN 1 BANGKINANG

This research is related to student's difficulties in reading comprehension. The purpose of this study is to determine the student's difficulties in reading. This research is descriptive. The population of this research is the second-semester students of class XI of SMKN 1 Bangkinang. The sample consist of 24 students. This research was conducted using a questionnaire. The finding of the study showed that the student had difficulty long sentence and text, vocabulary, grammar, knowing the background, and concentration are the main problem faced by students class XI of SMKN 1 Bangkinang
Traffic Image Analysis Based on Stacked Denoising Autoencoder Neural Network

This study aims to explore major neural network models - Stacked Denoising Autoencoder (SDAE), Deep Belief Network (DBN), Backpropagation - that have recently garnered attention and propose the most suitable and reliable artificial neural network model for real-time road traffic information collection. In this study, to enhance the reliability of experimental results, numerous experiments were conducted under identical conditions (such as parameter values and network configuration) by setting different initial values for the weight vector. The results of the experiments were statistically validated to draw conclusions. The research results showed that the SDAE model exhibited the most superior performance, while the accuracy of the DBN was somewhat lower compared to the SDAE model. On the other hand, the Backpropagation model demonstrated a relatively low predictive accuracy compared to both models, particularly showing a significant influence of the initial values
Autocomplete recommendation plugin and Summarizing Text using Natural Language Processing

Expert-caliber documents, reports, letters, and resumes can be easily developed using Microsoft Office. Microsoft Office offers capabilities such as grammar check, text and font checking &amp; formatting, HTML compatibility, advanced page layout, image support, and more in contrast to a plain text editor, however, it does not have the autocomplete abbreviations feature. The paper proposes an Autocomplete abbreviation Recommendation System that will integrate the benefits of getting automatic suggestions of either full forms, abbreviations, or both by clicking on the option that is being suggested. This will provide more flexibility to the user using existing Microsoft Office platforms. To create this feature, we have examined the JavaScript JQuery functions to implement a basic autocomplete feature. Information overloading is also one of the most important problems brought on by the Internet's explosive expansion. Massive quantities of text are difficult for people to manually summarise. Thus, there is now a greater need for summarizers that are more sophisticated and potent. Hence, Python's packages, methods, and NLP are used in this work to implement Text Summarization. By using this technique, the phrase's overall meaning is enhanced and the reader's comprehension is enhanced.
THE EFFECTIVENESS OF ROUNDTABLE TECHNIQUE ON STUDENT’S WRITING SKILLS IN DESCRIPTIVE TEXT

This research aimed to assess the effectiveness of implementing the roundtable technique in enhancing descriptive writing skills among eighth-grade students at SMP Simanjaya Lamongan. The research utilized a pre-experimental one-group pretest-posttest design. Data analysis involved the application of a paired sample t-test to ascertain the presence of a significant effect before and after the intervention. This research included a sample of 30 students from the eighth grade at SMP Simanjaya Lamongan. The findings of the research indicated a notable improvement in students' writing skills when employing the roundtable technique. This was evident in the average scores obtained by students on both the pretest and posttest. The mean score increased from 73.60 during the pretest to 83.03 in the posttest. The researcher then conducted a paired sample t-test to address the research question. The results of the t-test analysis revealed that the p-value (probability value) was below the significance level α (0.00 &lt; 0.05). Consequently, the null hypothesis (Ho), asserting no significant effect of the roundtable technique on students' descriptive writing skills, was rejected. The acceptance of the alternative hypothesis led to the conclusion that the roundtable technique had a significant positive effect on the students' writing skills in producing descriptive texts.
ERROR ANALYSIS ON SUBJECT-VERB AGREEMENT IN NARRATIVE WRITING TEXT MADE BY SENIOR HIGH SCHOOL STUDENTS

This study aims to find out and analyze students' mistakes in writing narrative text and what causes these mistakes. The method used in this research is a qualitative research design with a case study method by applying descriptive analysis. In this study, the object being analyzed was the subject-verb agreement error in writing narrative text in class XI IPA 2 of the tenth grade of MA Miftahul Qulub Polagan Galis Pamekasan. The problem of this research is to find the types of errors that commonly, the causes of errors, and the frequency of errors that students made in using subject-verb agreement in writing narrative text. The errors are classified into four primary groups based on the surface strategy taxonomy of superficial strategies cited by (Irwansyah,2017): omission, addition, misformation, and misordering errors. The researcher found those errors in the students' work in writing narrative text. It can be seen that each student made one to three errors, which are omission, addition, and misformation errors. From the results of the frequency of omission errors 53%, 39% addition errors, 7% misformation errors, and 0% misordering errors. errors that are often made by students, namely the 53% omission error has a higher percentage than the errors that occur in other types. Based on the results of this research, the researcher hopes that it will become important data for the language community, especially those who are interested in analyzing errors in English lessons. This research is expected to increase the reader's knowledge about good sentence patterns in the structure of the English language. Keywords: Analysis error, subject-verb agreement, writing narrative text
Igor Mel'čuk. 2021. Ten studies in Dependency Syntax. Berlin: De Gruyter Mouton. Pp. 444. US $160.99 (hardcover).

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Expert System for Diagnosing Inflammatory Bowel Disease Using Certainty Factor and Forward Chaining Methods

Identification of inflammatory bowel disease quickly and accurately is motivated by the large number of patients who come with pain in the abdomen and receive minimal treatment because they are considered to be just ordinary abdominal pain. This study aims to identify inflammatory bowel disease which is still considered by some people as a common stomach ache quickly, and precisely and to recommend therapy that can be done as an initial treatment before getting medical action by medical personnel. The method used in this expert system research is a combination of forward chaining and certainty factors. The forward chaining method traces the disease forward starting from a set of facts adjusted to a hypothesis that leads to conclusions, while the certainty factor method is used to confirm a hypothesis by measuring the amount of trust in concluding the process of detecting inflammatory bowel disease. The results of this study are a conclusion from the process of identifying inflammatory bowel disease which begins with selecting the symptoms experienced by the patient so that the diagnosis results appear using forward chaining and certainty factor in the form of a percentage along with therapy that can be given to the patient to reduce pain in the abdomen. A comparison of the diagnosis results using the system and diagnosis by experts, in this case, specialist doctors, shows an accuracy rate of 82,18%, which means that the expert system diagnosis results can be accounted for and follow the expert diagnosis.
Machine Learning based on Probabilistic Models Applied to Medical Data: The Case of Prostate Cancer

The growth in the amount of data in companies puts analysts in difficulties when extracting hidden knowledge from data. Several models have emerged that focus on the notion of distances while ignoring the notion of conditional probability density. This research study focuses on segmentation using mixture models and Bayesian networks for medical data mining. As enterprise data becomes large, there is a way to apply data mining methods to make sense of it using classification methods. We designed different models with different architectures and then applied these models to the medical database. The algorithms were implemented for the real data. The objective is to classify individuals according to the conditional probability density of random variables, in addition to identifying causalities between traits from tests of conditional independence and a correlation measure, both based on χ2. After a quick illustration of several models (decision tree, SVM, K-means, Bayes), we applied our method to data from an epidemiological study (done at the University of Kinshasa University clinics) of case-control of prostate cancer. Thus, we found after interpretation of the results followed by discussion that our model allows us to classify a new individual with an accuracy of 96%.
Clustering Productive Palm Land using the K- Means Clustering Algorithm

Indonesia is a country with a tropical climate that has many oil palm plantations. CV. Alkema Deo is one of the companies that manage oil palm plantations in Sampit City, East Kotawaringin Regency, Central Kalimantan. CV. Alkema Deo was founded in 2016 and has two plantation locations located on Jl. General Sudirman Km. 18, East Kotawaringin and Seibabi Village, Telawang District, East Kotawaringin. In this study, a qualitative approach was applied using a descriptive research pattern. In qualitative research, data is obtained from sources using various data collection techniques. Research using qualitative methods emphasizes the analysis of thought processes related to the dynamics of the relationship between observed phenomena, and always uses scientific logic. Based on the results of research for authors on a CV. Alkema Deo, the use of Excel in companies is quite good at processing data, but on a CV. Alkema Deo does not yet have land groupings based on productivity levels, so it is difficult to see the level achieved in 6 months based on the set target, and daily production control in terms of area and block area. Data obtained from CV. Alkema Deo is grouped based on area, block, and productivity. Application of data mining for grouping productive oil palm land on a CV. Alkema Deo with 4 variables, namely: land area, length, average production yield, percentage of achievement using the K-Means Algorithm to produce three clusters, namely 8 blocks or 50% including the high productive group (C2), 1 block or 6% blocks including the medium productive plantation group (C1), and 7 blocks or 44% including the small productive plantation group (C0).
A Survey of Applications of Blockchain in Collective Decision-Making Scenarios in Swarm Robotics

Blockchain is a distributed ledger that was introduced to decentralize monetary systems. However, with time, the applications of blockchain in different realms have been identified. Swarm robotics is a field that combines swarm intelligence and robotics to solve real-world problems that cannot be solved by monolithic robots. Collective decision-making is one of the major behaviors implemented by swarm robotics. This study analyzes existing literature on the applications of blockchain in the collective decision-making scenarios in swarm robotics. Consequently, this study introduces a novel taxonomy to study the different applications effectively. The taxonomy categorizes existing literature into (i) application of blockchain in other areas of swarm robotics, (ii) application of blockchain in continuous collective decision-making scenarios, (iii) application of blockchain in discrete collective decision-making scenarios, (iv) application of blockchain in other discrete collective decision-making scenarios, and (v) application of blockchain in the collective perception scenario. Finally, the limitations of existing work such as excessive resource consumption and violation of swarm robotics principles are discussed.
ROLES OF MOTIVATION (SELF-EFFICACY AND TASK-VALUE), WRITING KNOWLEDGE, SKILLS, AND STRATEGIC APPROACH TO STUDENTS' PERFORMANCE IN WRITING

Writing is challenging with many variables to consider, including learners’ knowledge, motivation, strategic behaviors, and skills. This study investigates the relationship between writing knowledge, strategic approach, skills, and motivation (self-efficacy, task value) on students’ performance in writing. The samples were 100 students (40 males and 60 females) from the Department of English Education at the University of Riau, Indonesia. They were between 18 and 24 years old. Researchers used a correlation approach. The finding of this study indicates that motivation (self-efficacy and task value), strategic approach, skills, and writing knowledge have a close and significant relationship one another. It is also proven that motivation (self-efficacy and task value), strategic approach, writing skills, and writing knowledge strongly influence the students' performance in writing. Keywords: writing performance, motivation, writing knowledge, skills, strategic approach
DEVELOPMENT OF ANDROID-BASED LEARNING MEDIA APPLICATION FOR BASIC ANALYSIS OF PROSE COURSE

This study aims to elaborate the development of learning media based on android applications and analyze the feasibility of learning media. The design of this study applies Research and Development (R&amp;D) method which uses ADDIE model that was developed by Dick and Carey (1996). Data collection techniques were carried out through interview and questionnaire by validity test data and documentation. The validation of learning media was carried out by media experts and material experts. The media was tested on students in sixth semester of English Education Department at Universitas Billfath. Data analysis techniques uses mixed methods (qualitative and quantitative). The results of this study indicates that the media is suitable for use because it is approved by the media expert validator with a percentage of 85%, the material expert validator 92% and students responses 85%. In addition, this media is able to help students conduct the study more effective, interesting, and fun, and also it helps students get better understanding of Basic Analysis of Prose material.&#x0D; &#x0D; Keywords: Development, Android-based, Learning Media, Prose&#x0D;
Development of Edu-Fertiblox Digital Game Using Roblox as a Teaching Aid for the Fertigation System Topic in the Design and Technology Subject Form 1

A lack of practical facilities frequently causes problems for teachers and students. The Edu-Fertiblox digital game has been developed for the purpose of being a teaching aid (TA) for the topic of Fertigation Systems in Design Technology Subject Form 1. This study aimed to identify the needs of TAs for the topic of fertigation systems, develop the Edu-Fertiblox digital game as a TA, and assess the usability of the digital game. The development of this game is using the ADDIE model as a research design. The digital game was developed using Roblox Studio. After that, Edu-Fertiblox was evaluated for its usability by three informants, consisting of teaching staff who are experts in Design and Technology. The findings showed all the informants agreed that the Edu-Fertiblox digital game can be used as a teaching aid for the Fertigation System topic of Design and Technology Form 1.
Reasoning Disaster Chains with Bayesian Network Estimated Under Expert Prior Knowledge

Abstract With the acceleration of global climate change and urbanization, disaster chains are always connected to artificial systems like critical infrastructure. The complexity and uncertainty of the disaster chain development process and the severity of the consequences have brought great challenges to emergency decision makers. The Bayesian network (BN) was applied in this study to reason about disaster chain scenarios to support the choice of appropriate response strategies. To capture the interacting relationships among different factors, a scenario representation model of disaster chains was developed, followed by the determination of the BN structure. In deriving the conditional probability tables of the BN model, we found that, due to the lack of data and the significant uncertainty of disaster chains, parameter learning methodologies based on data or expert knowledge alone are insufficient. By integrating both sample data and expert knowledge with the maximum entropy principle, we proposed a parameter estimation algorithm under expert prior knowledge (PEUK). Taking the rainstorm disaster chain as an example, we demonstrated the superiority of the PEUK-built BN model over the traditional maximum a posterior (MAP) algorithm and the direct expert opinion elicitation method. The results also demonstrate the potential of our BN scenario reasoning paradigm to assist real-world disaster decisions.
Students' perceptions on the use of selected mobile apps in the process of acquiring L2 pronunciation – a preliminary study

The accessibility and multimodality of modern technologies make them particularly beneficial for pronunciation learning and teaching. Google Play Store offers more than 300 English pronunciation apps, many of which have received high ratings ranging from 4.5 to 4.9 out of 5 stars. Most of these apps are available for free. Due to their capacity for individualized, customized, self-paced “anytime – anywhere” learning and automated feedback on individual performance and progress, these apps are gaining increasing popularity among English learners worldwide. This paper reports on a small-scale study that examined five of the highest-rated free apps: Elsa Speak – Learning English Pronunciation by ELSA, English Pronunciation 2019 – Correct Pronunciation by Grounders, English Pronunciation by NVG Std, Pronounce It by Maclo Studios, and Quick Pronunciation Tool by Tiago English Tutor. Twenty first-year BA students of English Philology from the University of Łódź participated in the study by testing the five apps and answering questions related to their overall design, utility, potential for learning, teaching, and pronunciation assessment. The results of the study revealed the learners’ practical uses of the apps and their views on the value of using these apps for practising, teaching, and assessing English pronunciation skills.