Reviewerly/exHarmony huggingface dataset:
The Role of Open Mathematical Problems in the Formation of the Competence of Plausible Reasoning

Today, modern Internet technologies allow you to access the necessary information at any time from anywhere. In such a situation, the ability to find what is needed from different sources and critically revise it becomes of particular importance, which, in turn, leads to the formation of basic knowledge. Consequently, when preparing young people for real life, the need to develop their critical attitude and thinking is urgent. As a rule, in real life, the initial data is not always clear, the goal is not set clearly, and there may be cases when the way out of this situation is also not the only one. Therefore, a person often faces open-type problems. Such cases can be taken as an interpretation of mathematical open problems. Indeed, open tasks are understood as tasks in which the initial data or the final goal are not clearly formulated. At the same time, students are given the freedom to set tasks to a certain extent, choose a way of thinking and enter additional parameters necessary for its solution. The article discusses plausible reasoning in the process of solving open problems and its role in the formation of students' competencies on plausible reasoning. In addition, various examples of how plausible reasoning arises when solving open problems are given, and an algorithm of actions for composing and solving open problems is given. Here the algorithm is only as an orienting basis, since there are no algorithms for solving open problems. It can be seen from the algorithm that when forming the competence of plausible reasoning, students should be able to solve closed and open problems and combine them in a certain effective sequence. Thus, it is concluded that the analysis of the compilation and solution of open mathematical problems plays an important role in the formation of the competence of plausible reasoning of future mathematics teachers and has a great influence on the preparation of young people for changing real life.
Development of Critical Thinking of Students in the Process of Organizing Chemical Experiments

In the work the importance and methodological features of the organization chemical experiment for the formation of natural science knowledge about chemical processes by school students and the development of their critical thinking was shown. The influence of the methodology of conducting a chemical experiment on the success of mastering chemistry in experimental classes and the level of formation critical thinking by school students was established. For identifying the subject erudition of school students in inorganic chemistry, after studying the theme, a control work was carried out, some questions of which required demonstrating the skills of analysis, generalization and formulation of arguments. It was shown that the problem-research chemical experiment provides school students with high motivation to study the discipline, the formation of such important universal educational actions as analysis, synthesis, generalization. Mastering such research skills as setting goals, identifying problems, planning actions to solve it, summing up, contributes to the development of school students' personality through the development of critical thinking. The use of a specially elaborated chemical experiment for the organization of individual and group work of school students in the classroom contributes not only to the development of critical thinking and the formation of skills and abilities, but also to the formation of subject knowledge, confirmed by the results of the formative pedagogical experiment.
Development of a Digital Twin for Gas Mixing in a Generator

The subject of this research is the development of a digital twin for the process of mixing the components of a gas mixture in the mixer of a mixture generator. The problem is motivated by the concept of digitalizing modern production and is considered in relation to the technology in question for generating a gas mixture of a given composition and homogeneity. A gas-dynamic model of an unsteady flow has been constructed and a numerical study carried out using the Ansys Fluent software. The Reduced Order Model was developed and used in the Ansys Twin Builder platform to build the digital twin.
Educational Data Mining using ML

Abstract: The ability to forecast students' performance is one of the most useful and important academic issues in the world today because of the development of technology. In the subject of education, data mining is incredibly useful, particularly for analysing student performance. The imbalanced datasets in this subject have made it extremely difficult to estimate students' performance, and there is no comparison of the various resampling techniques. This study compares multiple resampling procedures to manage the unbalanced information problem when projecting student performance of two distinctive datasets, including Borderline SMOTE, SMOTE-ENN, SMOTE, Random Over Sampler, SVM-SMOTE, and SMOTE-Tomek. Additionally, the dissimilarity between binary classification and multiclass, as well as the features' structures, are looked at. must be able to evaluate the effectiveness.
Analisis Perbandingan Certainty Factor dan Dempster Shafer Dalam Diagnosis Penyakit Porfiria Menggunakan Metode Perbandingan Eksponensial

Porphyria refers to a group of genetic disorders that affect the metabolism of porphyrins in the body. Porphyrin itself is a molecule that plays a role in the synthesis of hemoglobin, which functions as a carrier of oxygen in the blood. Disturbances in porphyrin metabolism can lead to the accumulation of porphyrins or their precursors, which in turn can produce a variety of symptoms. Porphyria comes in many forms, including acute porphyria and skin porphyria, each with its own unique symptoms. Nervous system and skin problems are common in porphyria patients, and if not treated properly, their health condition can deteriorate. A unique approach is needed to provide answers to this problem because it is still challenging to develop practical ways to address the problems experienced by patients. Certainty Factor and Dempster Shafer methods are two techniques that are widely used in the field of disease diagnosis today, where expert systems are often applied. But building expert systems in multiple disciplines is difficult due to uncertainty. Therefore, it is important to research and distinguish the many ways that these systems can be built. The exponential comparison approach is one of the most straightforward comparison techniques and helps minimize bias in the analysis process. To identify candidiasis in humans, this study attempted to apply, evaluate, and compare the two methodologies, as well as compare the results with the exponential comparison method. Comparative findings suggest that the Dempster Shafer technique provides a more precise diagnosis of porphyria
Sentiment Analysis on Movie Review from Rotten Tomatoes Using Modified Balanced Random Forest Method and Word2Vec

The film industry is one of the impacts of the rapid development of technology. This causes the film industry to increase every year. In addition, technological developments also affect the public to make it easier to access various movies from various websites. With many choices of movies, people need to know the quality of various movies by knowing the reviews of these movies from other people. However, the large number of audience reviews of a movie makes it difficult for people to categorize good movies and bad movies. The solution to the problem is to perform sentiment analysis on movie reviews. In this research, the classification method used is Modified Balanced Random Forest. This method was chosen because it can overcome imbalanced data and can increase accuracy and reduce time complexity. In this research, Word2Vec is also used as feature extraction. This feature extraction was chosen because previous research explained that Word2Vec has the advantage of being able to show the contextual similarity of two words in the resulting vector. The best model produced from this research is a model built without using stemming in the preprocessing stage, using 300 dimensions in Word2Vec, and using the Modified Balanced Random Forest classification method which produces an f1-score of 84.15%.
Education to Reduce Food Waste through Bye Waste Social Business

The issue of food waste is very important as it affects various aspects of human life and the surrounding environment. Business ideas on food waste management are important to help people maintain cleanliness and environmental sustainability. Therefore, an e-booklet business idea with the title "Bye Waste" can be an effective solution for providing such business ideas. The "Bye Waste" e-booklet will contain information on how to manage food waste generated every day. In the e-booklet, it will explain the types of food waste, how to sort and process food waste, and how to use it as organic fertilizer. The "Bye Waste" e-booklet will be sold at an affordable price so that people can easily access it. In order to expand its reach, this e-booklet will be marketed through online platforms such as websites or social media.
Klasifikasi Sentimen Masyarakat di Twitter terhadap Ganjar Pranowo dengan Metode Naïve Bayes Classifier

Indonesia is a country with a Democratic political system. The public is given freedom of speech, collaboration and public criticism. In the modern era, the use of social media is growing rapidly at the community level. One of the social media trends in Indonesia is Twitter which is used to convey aspirations to the government and as a means to convey daily activities, opinions, culture and get the latest information or news from Indonesia and abroad. Public opinion taken from Twitter can be positive, negative and neutral. The number of tweets on Twitter one of the trend topics in Indonesia is Ganjar Pranowo, can be used as a source of data in the assessment of sentiment classification which is processed to produce accuracy values. This study aims to classify public opinion on social media Twitter about Ganjar Pranowo using Naïve Bayes Classifier method. In the classification processing using a dataset of 4000 tweet data with two labeling classes, positive and negative to determine the efficiency of NBC performance combined with TF-IDF weighting, feature selection using supervised learning approach techniques. The results of the test on the classification of public sentiment research on Twitter about Ganjar Pranowo using NBC method using 10% of the test data from the dataset used to produce an accuracy value of 83.0%.
Pemodelan Prediksi Harga Ethereum (Atribut: Open, High dan Low) dengan Algoritma Extreme Learning Machine

The price of cryptocurrencies such as Ethereum often experiences high fluctuations and is difficult to predict. This study aims to predict Ethereum prices using the Extreme Learning Machine (ELM) algorithm which is a fast and efficient machine learning method. Ethereum price data is collected from CoinMarketCap by scraping the data using CoinmarketCap Scraper from the cryptocmd library using Python. An ELM model is built by changing the number of hidden nodes to determine the optimal prediction model of Ethereum prices based on the smallest average MAPE. Model performance was evaluated using the mean absolute percentage error (MAPE) on the test data set. The results show that the ELM model built can predict Ethereum prices with an accuracy of 96.96%. The MAPE obtained is 3.035334%, with 9 hidden nodes in the ELM network architecture model that was built. This shows that the model can explain about 96.96% of the variation in Ethereum price data. Therefore, the ELM model can be used as an aid in making investment decisions
Sistem Pendukung Keputusan Pemilihan Sales Supervisor Menerapkan Metode EDAS berdasarkan Pembobotan ROC

Sales is a job that aims to sell a product in the form of goods, services and others and provide the best service to consumers or buyers. Sales will work optimally if managed properly. The person who works to manage sales work is a sales supervisor. Sales Supervisor is someone who is responsible for managing the work procedures of each sales person under his control. A supervisor is required to be able to control every task implementation of a salesperson. If the company hires someone who is not qualified to be a sales supervisor, it will cause losses. So to determine the sales supervisor, a system is needed that will help select good and quality sales supervisor candidates according to the criteria set by the company. The right system to assist companies in making elections is SPK. Decision support system (DSS) is a system that is deliberately created to assist certain parties in making decisions with quality and objective results. SPK requires a method. In this study the method used is the EDAS method. The EDAS method has a function, namely to produce a ranking value by implementing mathematical formulations correctly according to the rules. The mathematical formulation is systematically arranged by experts and produces a ranking value which will eventually be assembled into an accurate decision. From the results of this study, a value of 0.5348 was obtained by Mandala as an alternative to B7, which is the best sales supervisor candidate
Penerapan Algoritma FP-Growth untuk Menentukan Strategi Promosi Berdasarkan Waktu dan Pembelian Produk

Sales is the main activity in every business. In making business decisions, sales patterns can be used to provide useful information such as strategies for promotion. Wandri Mart is a business engaged in the sale of products or goods commonly referred to as minimarkets in the city of Payakumbuh. In conducting promotional strategies, the owner of Wandri Mart does not know when to do promotions and what promotions are needed in order to increase sales. The purpose of this study is to obtain purchasing patterns related to the time of purchase and the type of goods purchased, so that a more effective promotional strategy can be developed. The method used by researchers is data mining techniques with the FP-Growth algorithm. The data used was taken as much as 5471 sales transaction data for 1 year. The results of this study indicate that the FP-Growth algorithm can be used to determine association rules using a minimum support of 1%, 2%, 3% and a minimum confidence of 10%. Experiments using Minimum Support 1% and Minimum Confidence 10% have the highest lift ratio value and produce more rules compared to other experiments so that it is obtained if on Tuesdays in August, customers buy instant noodles and packaged drinks with 6% and 5% support respectively and 50% and 45% confidence respectively with a lift ratio of 1.75 and 1.59 respectively. The lift ratio means that the rules have high association accuracy, and this also has a positive impact on sales and can be used as useful information for Wandri Mart to increase sales
Analisis Perbandingan Sistem Pakar dalam Mendiagnosa Penyakit Limfoma Hodgkin Menggunakan Algoritma Teorema Bayes dan Certainty Factor

Disease is a major challenge in the medical world. Accurate and timely diagnosis is a crucial key in disease management, including in cases of cancer. One type of cancer that affects the lymphatic system in the body is Hodgkin's lymphoma, which is also considered a rare disease. Typically, this disease occurs in adolescents and adults. Hodgkin's lymphoma requires serious treatment, although there are also cases of successful recovery. The importance of accurate and timely diagnosis in diagnosing Hodgkin's lymphoma is a critical factor in planning effective treatment and providing a favorable prognosis for patients. This study aims to perform a comparative evaluation of the Bayesian Theorem and Certainty Factor methods in diagnosing Hodgkin's lymphoma by comparing both methods. Diagnosing this disease is challenging for an expert due to the similarity of symptoms with other lymphoma diseases, which adds complexity. Therefore, this research provides an alternative to facilitate diagnosis by utilizing a system that can determine the level of certainty of a disease based on available data, including symptoms, expert values, and user values. After conducting research by comparing the two algorithms, Bayesian Theorem and Certainty Factor, various processing stages were implemented according to the established algorithm. The Bayesian Theorem algorithm yielded a result of 77.7%, while the Certainty Factor algorithm produced a higher value of 94.1%. The comparison between the Bayesian Theorem and Certainty Factor methods shows that the Certainty Factor method is more accurate in diagnosing Hodgkin's lymphoma and can be used in further research
Bayesian belief network model for quantifying the delay risk of marine construction projects in developing countries

The majority of international trade in goods is carried by maritime transport with higher volume for developing countries.Therefore, considering the enormous contribution of marine construction projects to economic growth, they have become one of the most crucial construction types in many countries.For this reason, the completion of these projects on time has critical importance on the local economy.However, marine construction poses serious risks compared to other construction works, resulting in possible delays since they have significant differences in design and construction.As a result, delay factors identified for different construction projects cannot be transferred directly to marine projects.This study identifies significant delay factors encountered specific to marine construction projects, a crucial gap in the literature.Subsequently, their relationships are examined and approved by experts.We also proposed a Bayesian Belief Network predictive model for estimating schedule delays in the marine project, carried out by a case study.The results show that the delay duration can be predicted using the proposed model before the marine project starts.Also, the identification of dependencies between the delay factors has practical advantages.Practitioners could define the cause-effect relations and prevent delays by focusing on the origins of the delay factors unique to developing countries.
Data Mining Clustering Korban Kejahatan Pelecehan Seksual dengan Kekerasan Berdasarkan Provinsi Menggunakan Metode AHC

Sexual harassment is one of the most common crimes in Indonesia recently. Acts of sexual harassment can occur in everyday life regardless of time, whether at work, on the street, or at home. Women are often the victims of sexual harassment, although men can experience the same. Perpetrators of sexual harassment can come from people we don't know, people who have hatred, even people we care about. Lack of religious and moral education, and technological developments that allow easy access to pornographic content are contributing factors to sexual harassment. To overcome this problem, fast action is needed in places where sexual harassment often occurs through socialization so that people are more vigilant when they are in these places. Apart from that, it is necessary to improve security in the area and provide consultation places such as psychologists. To identify places that are prone to sexual harassment in Indonesia, a data mining method is applied by utilizing previous data. The clustering method used is AHC using the complete linkage mode (longest distance) between the initial clusters. The final results of this research involve a manual process and the appropriate RapidMiner application, so that new clusters can be formed using RapidMiner. There are 5 provinces included in cluster 0, then there are 17 provinces in cluster 1, and 12 provinces in cluster 2
Penerapan Metode Teorema Bayes Dalam Mendiagnosa Penyakit Autoimun

Autoimmune diseases are caused by the failure of the immune system to attack the body itself. According to data from the US Department of Health and Human Services, more than 23.5 million Americans have an autoimmune disease, which is difficult to diagnose because of the variety of symptoms it presents. Therefore, the development of mechanisms to identify autoimmune disorders is essential. One of the developing technologies in this field is the use of expert systems in diagnosing diseases. An expert system is a system developed by experts using science-based technology. In order to use it effectively, proper methods are needed, such as the Bayes Theorem approach, described by Thomas Bayes, a priest. The Bayes Theorem approach explains the relationship between the probability of event A and event B based on available information. This study attempts to facilitate the diagnosis of autoimmune diseases by using an expert system and Bayes' Theorem technique. With a confidence level of 0.57 or 57%, the examination results show that the patient suffers from an autoimmune disease of the type Hemolytic Anemia (HA) based on the patient's input
The effect of information and communication technology on economic growth high-income countries

This study analyzes the influence of information and communication technology (ICT) and financial developments on the economic growth in high-income countries. This research uses the panel data regression method with a random effects model (REM) approach. The data were sourced from the World Bank and the International Telecommunication Union publications from 2001–2020. The results show that ICT (fixed telephone subscriptions, mobile/cellular telephone subscriptions, internet users and fixed broadband subscriptions) had no significant effect on economic growth. On the other hand, financial development (domestic credit to the private sector and stock market capitalization) had a significant effect on economic growth. Thus, indicators of financial development are better at promoting economic growth in high-income countries. Domestic credit to the private sector has a greater influence on economic growth compared to stock market capitalization. The research implications show that it is necessary to increase the contribution of financial development, such as facilitating access to credit to the real sector and increasing access to the capital market for economic actors to increase economic growth.&#x0D;