Reviewerly/exHarmony huggingface dataset:
Penerapan Deep Learning Menggunakan Gated Recurrent Unit Untuk Memprediksi Harga Minyak Mentah Dunia

Crude oil is a much-needed energy for the whole world. Each country is inseparable from the use of crude oil for use in various sectors, such as transportation, so that the price of world crude oil is the most important variable for the world. Fluctuations in oil prices will cause various problems, such as inflation, changes in market prices, and others. Therefore, the prediction of world crude oil prices is very important as a consideration for decision making. This study implements deep learning using the Gated Recurrent unit model. The data used is the price of Brent crude oil with a total of 5834 data, starting from January 4, 2000 to December 19, 2022. The parameters used are the number of GRU units, batch size, and lookback. The best model produced in this study is the GRU model with hyperparameters consisting of 30 lookbacks, 50 GRU units, and 256 batch sizes with the lowest MAPE value among the other models, which is 2.25%. The MAPE value states that predictions using the GRU model are said to be very good at predicting world crude oil prices
The Effect of Feature Weighting on Sentiment Analysis TikTok Application Using The RNN Classification

Social media is a medium used by people to express their opinions. In its development, social media has become a necessity in social life. One of the most popular social media applications since 2020 is TikTok. Short videos with an average duration of 60 seconds can entertain the community so that they don't feel isolated. There are 17 million TikTok application reviews in the Google Play store in Indonesia from various user ages. The rapid development of information and technology has led to the pros and cons of this application. Freedom of expression without specific restrictions on content publication negatively impacts the user's mentality. Based on this, sentiment analysis is very important to reveal trends in opinions about applications that are useful for the community in increasing awareness of whether the application is good before use. Proper feature weighting is required to improve the sentiment analysis results' accuracy. More optimal results can be obtained by determining the appropriate weight for different feature weighting. This study compares the TF IDF, TF RF, and Word2Vec feature weighting methods with the RNN classifier on the TikTok app review. The experiment shows that TF RF is superior to TF IDF, with successive feature weighting accuracy with TF RF of 87,6%, TF IDF of 86%, and Word2Vec of 80%. The contribution of this research lies in its exploration of different feature weighting methods to enhance sentiment analysis accuracy and provide valuable insights for decision-making processes.
Agglomerative Hierarchical Clustering (AHC) Method for Data Mining Sales Product Clustering

Supermarkets are Indonesian terms that refer to large stores or supermarkets that offer a variety of daily needs such as food, drinks, cleaning products, household appliances, clothing, and so on. In contrast to stalls or small shops, supermarkets have a larger size and provide a variety of products. Because of this, many people prefer to shop for their daily needs at the supermarket rather than at the nearest shop because the existence of the supermarket makes it easier for consumers to buy various products in one place without having to move to another store. However, sales in supermarkets also pose a problem, namely how to sort or group products that are not selling well so they can be replaced with products that are selling better or reduce the number of suppliers. This is where data mining or data analysis techniques that use business intelligence are needed. The research was conducted to classify the best-selling products in supermarkets using the Agglomerative Hierarchical Clustering (AHC) method, in which alternatives with the same matrix or distance are grouped into certain clusters. In applying the AHC method, the number of clusters formed is 3. There are three different clusters, namely cluster 0, cluster 1, and cluster 2, each with a different alternative group. Each cluster has a different number of products and a different percentage. Cluster 0 is the cluster with the highest number of products and the largest percentage, namely 45% with a total of 9 products, followed by cluster 2, and cluster 1 has the smallest number of products and percentage, namely 0.30% with a total of 6 products and 0 .25% with a total of 5 products. In addition, sales data for several products each month are grouped based on certain price ranges
Public Speaking Anxiety in English Among ACCA Foundation in Accountancy Students in a Malaysian Private University: A Case Study

This research looked into the level of public speaking anxiety in English at three distinct speaking stages, including before, during, and after speaking, as well as the coping strategies employed to manage public speaking anxiety. The study utilized a quantitative method and an online survey design, with (n=36) participants comprising ACCA Foundation in Accountancy students from a private university in Malaysia. The participants completed an online questionnaire survey using Google Forms. The questionnaire survey consisted of three sections; Section A asked for personal information, while Likert scale survey questions were included in Sections B and C. The data collected were analyzed using the Statistical Package for the Social Sciences (SPSS), which enabled the computation of mean scores, standard deviations, and percentages to summarize the results. The study’s findings revealed that ACCA Foundation in Accountancy students experienced high levels of anxiety in public speaking before their presentation stage, followed by moderate levels during and after their delivery stages. Furthermore, the study demonstrated that the coping strategies utilized by the students during preparation and delivering strategies were at a high level. This study offers an opportunity for tertiary students and educators to recognize the level of anxiety experienced when it comes to public speaking in English and to learn effective coping mechanisms to manage that anxiety. Such coping strategies can improve academic performance and advance career growth. Keywords: Public speaking (PS), Accountancy students, Quantitative method, Questionnaire survey, Likert-scale questionnaire
Governance Perception Study of the Chinese Foreign Direct Investment Activities in Nigeria

This study explores the governance perceptions of stakeholders regarding Chinese Foreign Direct Investment (FDI) activities in Nigeria. The aim is to gain insights into stakeholders' perspectives on various governance dimensions, including transparency and accountability, efficiency and effectiveness, participation and inclusiveness, the rule of law and legal frameworks, social and environmental impact, and stakeholder engagement. Thematic qualitative analysis is applied to the collected data to identify emerging themes and patterns in stakeholders' perceptions of Chinese FDI activities. By analyzing stakeholders' perspectives, this research provides valuable insights into the governance challenges and opportunities related to Chinese FDI in Nigeria. The findings include valuable insights into stakeholders' viewpoints, allowing for a comprehensive understanding of governance dynamics and areas of improvement in Chinese FDI activities in Nigeria. The findings enhance governance frameworks and promote sustainable and mutually beneficial relationships between China and Nigeria. The study contributes to the existing literature on governance perception and provides practical implications for enhancing governance practices and stakeholder engagement in Chinese FDI projects.
Peningkatan literasi keuangan siswa melalui penggunaan media interaktif SIKU (Sikapi Uangmu)

For students to have the tools to manage their finances, they have to be taught about financial literacy from an early age wisely. The purpose of this research is to help senior high school students improve financial literacy through interactive media SIKU (Sikapi Uangmu). This research used a Quasi-experimental group experimental design with a Nonequivalent control group type. Samples were taken using total sampling techniques in 2 different classes. Class X IIS 2 was the experimental group, and Class X IIS 3 was the control group. The research data was taken using test instruments. The data that has been collected is then analyzed using a t-paired test. The results showed that the use of SIKU interactive media for senior high school students was able to increase student's financial literacy. Paired t-test testing which produces a significance of 0.000, t=-12.43, explains the increase in financial literacy of learning using SIKU. These results show that SIKU interactive media can be applied in the learning process in schools, and effectively contribute to improving students' financial literacy.
A Diachronic Study on the Cultivation of Innovative Talents in China’s Foreign Language Education: Achievements and Prospects

It is the historical mission and sacred duty of Chinese universities to cultivate innovative talents. Researchers in the domain of foreign language education have undertaken in-depth theoretical research around the cultivation of innovative talents in the past few decades. Taking 35 academic articles published in the Chinese Social Sciences Citation Index (CSSCI) as the research sample, this study uses textual analysis to conduct a diachronic review of the generation background, concept definition, quality indicators, and educational mechanisms to discover a wealth of innovative wisdom in the academic community. However, there is a lack of research in areas such as teacher education and educational evaluation, which will require focused attention in the future.
Scientific Article Writing Workshops for Students Indonesian Language Education Master Program FKIP Tanjungpura University

This Community Service aims to provide knowledge and skills to Indonesian Language Education Masters Study Program students in writing scientific articles. This activity must be carried out because students must publish their research articles in accredited national journals or international journals under the Regulation of the Minister of Research, Technology, and Higher Education Number 50 of 2018. This activity uses the problem-solving method to overcome three problems, preparation of training modules, implementation workshops/training, and the ability of students to write scientific articles. This community service activity produces the following things. (1) Availability of scientific article writing training modules. (2) The implementation of the workshop/training was well proven by &gt; 75% (16 people/76.19%) of students, who managed to get an average score of 76.19 in a pretty good category. (3) The ability to write scientific articles for students is at an average score of 76.19 in a fairly good category. The average score based on the indicator of completeness of the structure is 83.33 in the good category; the language aspect indicator is 77.38 in a fairly good category; the template suitability indicator of 76.19 in a pretty good category; the Mendeley application utilization indicator is 50.00 in the less category. The scientific article content indicator is 92.86 in the very good category and the literature review indicator of 77.38 in the fairly good category.
IMPLEMENTASI METODE HYPNOTEACHING DALAM PEMBELAJARAN MENULIS TEKS INSPIRATIF BERORIENTASI PADA STRUKTUR DAN ASPEK KEBAHASAAN PADA PESERTA DIDIK KELAS IX DI SMPN 21 BANDUNG

The background of this research is that there are several problems that are often experienced by students when writing inspirational story texts, namely students often find it difficult to get ideas and develop them. This research uses quantitative methods. In research methodology, it is important to pay attention to research ethics and ensure that research is carried out with integrity and objectivity. The author shows excellent skills in planning learning to write inspirational story texts using the Hypnoteaching method. As for the research results: 1) The writer obtained a score of 3.79 for the assessment of lesson planning. This shows that the writer has a very good ability in planning learning. 2) Students demonstrate the ability to write inspirational story texts using the Hypnoteaching method. This can be confirmed through the results of the Wilcoxon signed rank test which was carried out on the pretest and posttest data from the experimental class and the control class. Based on the results of the test statistics, the experimental class obtained an asymp value. Sig. (2-tailed) of 0.000 &lt;0.05, which indicates that the students' ability to write inspirational story texts using the Hypnoteaching method has increased. 3) the Hypnoteaching method for class IX students of SMPN 21 Bandung succeeded in improving student learning outcomes. The average value obtained by students in the experimental class who received the treatment of applying the Hypnoteaching method experienced a more significant increase compared to the average value obtained by students in the control class who did not receive the treatment of applying the Hypnoteaching method. This shows that the Hypnoteaching method is effective in improving students' learning outcomes in writing inspirational story texts.
Klasifikasi Kualitas Air Minum menggunakan Penerapan Algoritma Machine Learning dengan Pendekatan Supervised Learning

The need for the provision and service of clean water from time to time is increasing which is sometimes not matched by the ability and knowledge of clean water. The majority of people still do not know whether water is suitable for consumption or not. The quality of drinking water can be distinguished based on the mineral parameters contained in the water. This article will explain the classification of water sample data by applying a Machine Learning Algorithm, which includes modeling with Logistic Regression, Support Vector Machine (SVM), Random Forest Classifier, K- Nearest Neighbor(KNN), XGBoost Classifier. Classification models produce varying degrees of accuracy. The highest accuracy is obtained in the Random Forest Classifier model with an accuracy rate of 78%. Analysis of drinking water quality with machine learning algorithms is very easy to understand, because the results of this study produce very simple results so that they are easy to understand
ANALISIS KEMAMPUAN MENULIS TEGAK BERSAMBUNG KELAS V SDN KARANGANYAR GUNUNG 02

This research is motivated by the difficulties and long time taken by students in class V C when given writing tasks using cursive handwriting. Some students also struggle with writing proper shapes and curves in cursive writing. Consequently, these frequently encountered issues lead many students to not apply cursive writing in their daily writing activities. Moreover, cursive writing activities are necessary to stimulate brain function, particularly the right brain hemisphere responsible for various forms of art and aesthetics, and the left brain hemisphere as the generator of words, ideas, and concepts to be written. The main problem under investigation is the cursive writing ability of class V C students at Karanganyar Gunung 02 Elementary School.
THE RELATIONSHIP BETWEEN COLLEGE STUDENTS’ ATTITUDES TOWARD LEARNING ENGLISH AND THEIR ACTUAL ACHIEVEMENT IN EXAMINATIONS

This study aimed to investigate the relationship between college students' attitudes toward Learning English as a foreign language (EFL) and their academic achievement in examinations at the Faculty of Education/Saber - University of Lahij. A total of (60) university students participated in the study as the sample from whom data was gathered. A survey questionnaire and samples of students' scores in examinations were used as the instruments for data collection. The questionnaire aimed to gather information about the students' attitudes toward learning English as a foreign language and the samples of scores were used to carry out a comparison between students' attitudes and their achievement in examinations. The results showed that the students had highly positive attitudes toward learning English. In comparing such results with their achievement in examinations, the data showed that there was a gap between students' attitudes and their achievement in examinations. The study proposed some suggestions and solutions to develop students' attitudes toward learning English and raise their awareness of the importance of English in their academic life.
Analisis Sentimen Masyarakat Terhadap Penghapusan Honorer Berdasarkan Opini Dari Twitter Menggunakan Naïve Bayes Classifier

The removal of honorees is currently a hot topic throughout Indonesia. Sharing how honorary personnel do so that the honorary removal policy is not implemented. Most honorary personnel have served for several years, but the government has issued a circular on the abolition of honorees. Various pros and cons of society regarding the abolition of honorees, such as honorary workers can lose their jobs, not get income, and unemployment is increasing. The purpose of the study is that the government can provide strategies that must be carried out in the event of the removal of honorees, such as appointing all honorees to become Civil Servants or Government Employees with Work Agreements. So the removal of the honoree became one of the trending topics on Twitter social media in 2022. From the results of the analysis conducted, public opinion that uses Twitter is very influential for honorary workers by grouping opinions into three categories, namely positive opinions, neutral opinions, and negative opinions. So the study with text mining used the Naïve Bayes Classifier algorithm with data from Twitter tweets from January 2022 to December 2022 with 2,705 data. The results of this study obtained accuracy with 10 K-fold Cross Validation on K-10, which was 73.01%. And it was found that sentiment polarity against the removal of honorees on positive class sentiment by 10% against agreeing to remove honorees with 285 data tweets, neutral class sentiment by 67% against agreeing and disagreeing with the removal of honorees with 1,801 data tweets, and negative class sentiment by 23% against disagreeing with the removal of honorees with 619 data tweets
Analisis Sentimen E-Wallet Menggunakan Support Vector Machine Berbasis Particle Swarm Optimization

E-Wallet applications in Indonesia have started to be in demand since the Covid-19 pandemic. The object being analyzed is an e-wallet application that is widely used in Indonesia and can be downloaded on the Google Playstore. The applications analyzed are Dana, Ovo, PayPal Link Aja and Doku. The advantages of these five applications are that Dana is user friendly or easy to use, while using Ovo is superior in terms of benefits, and Doku is superior in terms of security, Link Aja tends to be perceived by consumers in a neutral condition between security and user convenience because it is an e-wallet. It is still considered new in Indonesia, and PayPal has become a successful online payment system in C2C field. The focus of this research is to compare the comments of the users of the five applications. The method used in this study is the Support Vector Machine (SVM) algorithm. To produce high accuracy it is optimized using the Particle Swarm Optimization (PSO) algorithm. This was taken based on previous studies which stated that SVM-PSO has the highest percentage of accuracy compared to other algorithms. The data used is a thousand (1000) per application. So, the total amount of data is five thousand (5000) data. The results of the research show that the Ovo e-wallet is superior because it has the most positive comments, namely 579 and 421 negative comments, while the lowest position is occupied by Link Aja which only has 579 positive comments and 421 negatuve comments. In the process of sentiment analysis, the accuracy percentage of the SVM-PSO algorithm was also obtained, which was 91.10% in the Link Aja application. This means that SVM-PSO is very suitable to be combined to get the highest accuracy
Analisis Pola Asosiasi Data Transaksi Penjualan Minuman Menggunakan Algoritma FP-Growth dan Eclat

Every day transaction activities between companies and consumers continue to be carried out. This makes transaction data more and more and accumulate. This transaction data can be processed into more useful information using technology. Data mining is a technology that can work on a collection of transaction data into information that can be taken by companies as decision makers. The association rule method is used as a method to see the relationship between items in a transaction data. To analyze transaction data, researchers used the FP-Growth and Eclat algorithms. There are three stages of association in this study which are distinguished from the confidence value. The results in the first stage have a minimum confidence value of 0.4, the FP-Growth algorithm produces 41 association pattern rules, while the Eclat algorithm produces 32 association pattern rules. Then in the second stage the minimum trust value is 0.5, the FP-Growth algorithm produces 40 association pattern rules, for the Eclat algorithm it produces 32 association pattern rules. In the third stage, the minimum trust value is 0.6, the FP-Growth algorithm generates 32 association pattern rules, while the Eclat algorithm generates 30 association pattern rules. The results of the association pattern rules show that the Eclat algorithm is more efficient in determining the association pattern rules than the Fp-Growth algorithm
Reflective Analysis on Neurodiversity and Student Wellbeing

With the number of neurodivergent students entering Higher Education increasing, it is essential that we understand how to provide an inclusive educational experience which facilitates positive wellbeing. In this reflective analysis we draw upon our position as neurodivergent academics alongside relevant theory and literature to foster understanding and provide practical strategies for those supporting neurodivergent students. We emphasise the importance of questioning normative assumptions around expected student learning behaviours, and the negative impact that these assumptions can have upon neurodivergent students. We then provide several practical strategies that can be used to develop more inclusive practice, drawing upon principles embedded within a Universal Design for Learning approach.&#x0D;
INCREASING INTEREST IN READING IN ESTABLISHING A CRITICAL AND TOLERANT MULTICULTURAL COMMUNITY READING CULTURE

This study aims to provide a discourse on the importance of increasing reading interest in forming a critical and tolerant multicultural society reading culture. These research studies are literature from various sources that discuss reading interest, reading culture, and its relationship with a multicultural society. The study results that have been carried out show that reading activities can broaden the horizons and horizons of human thinking so that they are not left behind by the rapid development of the times. Everyone must be encouraged to have high interest, activity, and reading habits. Low interest, hobbies, activities, and reading habits can be factors for the decline in the level of progress of a nation. Intolerance, feeling the most correct, the best, and not wanting to respect the opinions, behaviors, and cultures can arise because of low insight, intelligence, and thinking horizons. Therefore, to create a multicultural society that is critical, tolerant, open, and pluralistic, it is necessary to have high reading activities, habits, and culture. This needs to be realized because a high reading tradition can support the acceleration of people's intelligence in responding to various life problems in a nation