Reviewerly/exHarmony huggingface dataset:
EMPLOYING QAR STRATEGY TO IMPROVE STUDENTS’ READING COMPREHENSION

The objectives of the research was to see how Question Answer Relationship (QAR) strategy assisted students to improve their reading comprehension and describe the situation when Question Answer Relationship (QAR) strategy was employed in the reading class. The researcher was applied pre experimental design. The population was the Second Grade Students of SMPN ciptodadi in 2021/2022 Academic Year. The total number of population is 30 students. The researcher was used purposive sampling technique. relatively baseline knowledge based on their test examination average scores. The total number of sample was 30 students from class. In analyzing the numerical data, the writer was used SPSS for windows. After implementing the research, the researcher concludes that The use of Question Answer Relationship (QAR) strategy in teaching reading enriches the students’ reading comprehension; it is proved by the mean score of the students’ posttest. The t-test of the students’ reading achievement in posttest was smaller than ? (0.000 &lt; 0.05). It meant that the H1 of the hypothesis was accepted
THE EEFECT OF SMARTPHONE ON STUDENTS’ SPEAKING SKILLS

The aim of this research is to find out the Effect of Smartphone on Students’ Speaking Skill. The research design was used pre-experimental research with one group pre-test and post-test. This research was conducted at SMP Negeri 3 Bissappu. The researcher was used total sampling technique. The researcher uses this technique because all the members of the selected had similar characteristic and the same relatively baseline knowledge based on their test examination average scores. The total number of samples was 30 students from class VII. The Speaking tests were administered in the pretest and posttest. The instrument was intended to measure the students’ enrichment of speaking. The test Speaking aspects in this research are: fluency, vocabulary, pronunciation, accuracy and comprehensibility. Based on the research findings and discussion in the previous chapter, the researcher concludes that the use of Smartphone enriches the students’ speaking skill; it is proved by the mean score of the students’ posttest. The t-test of the students’ speaking achievement in posttest was smaller than ? (0.000 &lt; 0.05). It meant that the H1 of the hypothesis was accepted
Review of studies on the disfluency effect: Can a font change improve memorization and educational outcomes?

This review article is devoted to the disfluency effect, which is observed as an improvement in the memorization of information and subsequent educational results due to reduced processing fluency. According to the basic explanation of the disfluency effect, if information is written illegibly, the learner senses complexity, or disfluency, which leads to a deeper processing of information. Traditionally, the disfluency effect is considered from the perspective of Bjork’s desirable difficulties approach and Sweller’s cognitive load theory. In this article, we pay attention to these concepts and also discuss the main studies and meta-analyses devoted to the effect. It is worth noting that the existence of the disfluency effect is not seen as indisputable and raises doubts among the authors of the review and other colleagues. As indicated, a significant number of studies do not detect the effect; for this reason, possible moderators influencing its manifestation are also considered. A separate section of the review is devoted to research of the Sans Forgetica font. The font was specially created to be disfluent, and its developers proceeded from the assumption that the disfluency effect really exists. This review article is addressed to a wide range of readers, and it may be of interest to both specialists in the field of metacognition and for pedagogical practitioners.
USING PORO ENGLISH APPLICATION TO IMPROVE STUDENTS’ PRONUNCIATION LEARNING ENGLISH AT UPT SPF SMPN 35 MAKASSAR

The research explores android-based learning media and applies the learning technique to counter this issue. This study investigates the poro English application in teanching English pronunciation in the classroom.It aims to identify student’s responses toward the application in learning English pronunciation in which students of ninth grade of SMP Negeri 35 Makassar. This study using a qualitative method to explore teaching and learning English pronunciation in the classroom using the poro english application. The data were collected in two main instruments: observation and interviews.The observation explored the process of applies the poro English application in teaching English pronunciation. While the interviews were administered to reveal the student’s response. The result showed that poro English application in teaching English pronunciation could be applied in the classroom. In particular, most students responded positively to using the application in the learning activities. For example,they said that application really helped them to learn and made it easier for them to practice pronunciation.
IMPROVING STUDENTS’ WRITING SKILL THROUGH PERSONAL PHOTOGRAPH AT THE SECOND GRADE OF SMPN 35 MAKASSAR

The objective of the research was to find out wheter using personal photograph method was able to improve students’ writing skill at second grade of SMP Negeri Makassar. This Research was used experiment method and research subjects are students of SMP Negeri 35 Makassar Class VII (1). This Research takes students of class VIII (1) totaling 30 Students. In this research was conducted pre-test, treatment, and post-test. Data obtained through the provision of pre-test and post-test. the result showed differences in the average value of the each test. The average value of students in pre-test 65.56 and post-test was 93.30. This shows that the personal photograph method the positive effect on students’ writing skills class VIII (1) SMP Negeri 35 Makassar.
EFL STUDENTS’ ACHIEVEMENT AND MOTIVATION IN WRITING TEXT THROUGH WEBBING TECHNIQUE

The objectives of the research were to find out whether or not the use of webbing technique can improve the writing skill of second year students of SMP Negeri 8 Makassar and to know how the motivation students in writing skill through webbing technique. The writer was applied pre experimental with one group pre-test and post-test. This research was conducted at SMP Maha Putra Makassar sub-district of Panakukang, Makassar city. In this research, the population was the eight grade students of SMP Maha Putra Makassar in academic year 2021/2022. The total numbers of population were 360 students. The researcher was used total sampling technique. The total number of sample was 40 students from class VIII-1. In analyzing the numerical data, the writer used SPSS for windows. After conducted the research, the writer concludes that that The use of webbing in teaching writing skills enriches the students’ achievement; it is proved by the mean score of the students’ in pre-test and posttest. The mean score of the pre-test before the treatment was 61.72 and after the treatment the students gained score 74.88. The t-test of the students’ achievement in posttest was smaller than ?. The researcher found that the p-value (probability value) was lower than ? (0.00 &lt; 0.05) and the degree of freedom was 39. The t-test value of pre-test and post-test was remarked significantly different. It indicated that the alternative hypothesis (H1) was accepted and, of course, the null hypothesis (H0) was rejected. The use of webbing technique can improve students motivation in learning writing skills
THE EFFECT OF INTEGRATIVE LEARNING MODEL TYPE THREADED IN READING AT CLASS VIIIIII STUDENTS OF SMP IT FAJAR ILAHI 1 BATAM

The aim of this research is to identify the effectiveness of the threaded type integrative learning model in learning to read for Class VIII students at SMP IT Fajar Ilahi 1 Batam. The researcher was applied pre-experimental design the population is the seven grade students of SMP IT Fajar Ilahi 1 Batam in academic year 2021/2022. Based on data analysis, hypothesis testing, and the results of the discussion that has been presented, the researcher can conclude that the results of the research that has been carried out are that the application of the Threaded Type Integrative Learning Model in Reading Learning for Class VIII Students at SMP IT Fajar Ilahi 1 Batam can improve students' reading abilities
IMPROVING LEARNING OUTCOMES THROUGH APPLICATION OF MODEL QUANTUM TEACHING

Student learning outcomes in subjects at SMPN 5 Panggarangan are still relatively low, this is because the learning model used is stillteacher centered, lack of maximizing student potential, without giving students an active role in learning. This study aims to improve the learning outcomes of students at SMPN 5 Panggarangan by using the quantum teaching. This type of research is a collaborative Classroom Action Research (CAR). The research subjects were students at SMPN 5 Panggarangan, totaling 37 students. The instruments used are observation sheets and tests. Observational data were analyzed descriptively qualitatively and data from the test results were analyzed descriptively quantitatively. The results of the pre-action research showed that students' learning outcomes in were low. The average value of the new class reached 64.21 and the percentage of completeness was 40.54%. After doing the action using the quantum teaching that varies various learning methods in cycle I, value class average increased to 68.70 and the percentage of completeness increased to 62.16%. Likewise after the improvement of Quantum Teaching which is accompanied by encouragement to actively ask questions, give feedback, reinforcement, and the distribution of heterogeneous groups in the action cycle II, further enhances students' learning outcomes. The class average value increased to 76.76 and the percentage of completeness increased to 94.59%.
IMPROVING ENGLISH LEARNING OUTCOMES THROUGHTWO STAY TWO STRAY LEARNING MODELAT SMPN BENTENG UTARA NO.4 KEPULAUAN SELAYAR

Based on the low learning outcomes of first grade students in English studies at SMPN Benteng Utara No.4 Kepulauan Selayar. The purpose of this study was to determine the level of effectiveness of the Two Stay Two Stray learning model as seen from the English studies learning outcomes of first grade students. The design of this study used the experimental method, with a sample of 24 students. The instruments used are observation and tests. There is a significant difference between English studies learning outcomes before and after the application of the Two Stay Two Stray learning model with the application of the lecture or conventional model. Those who scored 80-100 in the very good category were 13 students or 54.16%, while 6 students or 25% scored 66-79 in the good category, who scored 56-65 in the sufficient category from 5 students. or 20.84%. As well as students who get a score of 40-55 in the low category and no score &lt;40 or less category at all. Therefore, the Two Stay Two Stray learning model is more effective than the conventional model
THE EFFECT OF POW+TREE STRATEGY TOWARDS STUDENTS’ WRITING SKILL

This research is aimed prove whether the POW+TREE strategy has a significant effect or not and to determine the effect of POW+TREE strategy towards students’ writing skill of UPTD SMP Negeri 6 Sinjai. This research focused as pre-experimental research one group pretest and posttest. The population of this research were the ninth-grade students of UPTD SMP Negeri 6 Sinjai, in academic year 2021/2022 consisting of 210 students. Purposive sampling technique was used to take one classes as the sample of the research which consist of 29 students. The data were obtained from writing test. The results of the research used inferential analysis of t-test by SPSS v.16, showed that there was a significant improvement in the students’ mean score writing skill between the pretest and posttest. The mean score of the students’ writing increased from 45.83 in pre-test to 82.23 in post-test. The significance value calculated 0.000 is smaller than 0.05 (P-value = 0.000 &lt; 0.05). Therefore, the hypothesis of this study was accepted. It means that the POW+TREE strategy gave significant effect on students writing skill of UPTD SMP Negeri 6 Sinjai. In addition, students’ motivation after using this strategy also increased. The researcher concludes that the effect of POW+TREE strategy in teaching English enhances the students’ writing skill.
USE OF SERIAL IMAGE MEDIA TO IMPROVE THE READING SKILLS OF UPT SMKN 8 MAKASSAR

This research aims to improve the reading skills of Class XI students at UPT SMKN 8 Makassar for the 2023/2024 academic year. The research method used is classroom action research (PTK). The sample consists of 1 class totaling 21 people. Classroom action research carried out in cycle I and cycle II using serial image media was proven to have improved students' reading abilities. This can be seen from the results of the percentage of student learning completeness in the Pre-cycle stage of 38%, Cycle I of 62%, and an increase in cycle II of 81%. So, it can be concluded that the use of serial image media can improve the reading skills of class XI students at UPT SMKN 8 Makassar.
IMPROVING LOW CLASS WRITING SKILLS AT UPT SDN 1 GANDANGBATU SILLANAN

This study aims to determine the improvement of lower grade writing skills through media images in class II UPT SDN 1 Gandangbatu Sillanan students for the 2020/2021 academic year. The subjects of this study were class II students with a total of 27 students consisting of 14 male students and 13 female students. The method used is a class action research method (Classroom Action Research) where the analysis of learning outcomes is reflected in the next lesson. This research was divided into two cycles, namely cycle I and cycle II. Based on the research results, the writing ability of the low grade students in grade II can be improved by using media images. This can be proven from the increase in low class writing skills. In the pre-cycle the average value obtained was 55.37, it experienced an increase in the first cycle the average value obtained was 66.67, and experienced an increase in the second cycle the average value became 78.89. The conclusion of this study shows that media images can improve writing skills in class II students in class II.
FACE-TO-FACE LEARNING DURING THE PANDEMIC PERIOD COVID - 19 IN ENGLISH SUBJECT AT SMP NEGERI 5 AMARASI SATAP

The aim of this study to find out the effectiveness of face-to-face learning face-to-face learning during the pandemic covid-19 on social science subjects (ENGLISH) for class VII students at SMP Negeri 5 Amarasi Satap District , Makassar City . Method study quantitative could interpreted as method research based on the philosophy of positivism, the data is quantitative. Population and the sample of this study is the population of all students of class VII SMP Negeri 5 Amarasi Satap District , Makassar City which amount 46 people, and the sample that is whole student class VII SMP Negeri 5 Amarasi Satap District , totaling 46 people. Data is collected from value student report cards during face-to-face learning is limited, the data collected is analyzed use analysis technique statistics descriptive. Research result show that face-to-face learning Effective against social science learning (ENGLISH) students during the Covid-19 pandemic where the average student score was in the VII class namely with a total of 22 students with a percentage of 95.45% of students is at on category high.
Research on Power Network Fault Event Extraction Based on Hybrid Neural Network

In order to obtain event information of power grid faults in time, assist electric power workers to solve fault problems, make quick decisions, and reduce economic losses, a power grid fault event extraction model based on deep learning is proposed. The model is mainly composed of two Parts are composed of fault detection model and event role extraction model. Firstly, the power-related text is encoded based on the RoBERTa pre-training model. The fault detection model uses the BLSTM model to further extract the text features to obtain the specific fault category of the power public opinion text. Secondly, the event role extraction model uses the BLSTM-CRF model Extract the text features to get the event roles contained in the text. Finally, the power grid fault event information contained in the text data is obtained through the joint extraction of fault detection and event roles. Experimental tests show that the proposed model has better performance in grid fault event extraction results and accuracy.
Instance-based 3D Anchor for Monocular 3D Object Detection

The perception component of autonomous driving system usually consists of LiDAR and RGB camera. Compared with LiDAR, RGB cameras have the characteristics of low price and long life. Recently, some works focus on using a single RGB image to conduct 3D object detection task. Due to the lack of depth information in monocular images, it is necessary to constrain depth estimation or introduce depth clues in the detection pipeline. Compared to the depth-guided approach of MonoDETR, we introduce instance-based 3D anchors into the visual features encoder to guide the learning of network parameters. In this way, richer clues can be introduced for the encoding and decoding stages with faster inference speed. Our instance-based 3D anchor detector is trained in an end-to-end manner, achieving advanced performance on the KITTI benchmark with significant gains.
Sentiment Analysis of Russia-Ukraine Conflict: A Hybrid Approach Using VADER, GloVe-embedding and LSTM

Russian-Ukraine conflict is going on for quite a long period and it has become very crucial to understand the public opinion on this issue for various reasons like policy implication, peace building efforts, humanitarian reasons and many more. This paper aims to study the public sentiment on Russia - Ukraine conflict from twitter data using a hybrid approach. It presents a hybrid approach to perform sentiment analysis on twitter data using VADER, GloVe-embedding and LSTM. Our research analyses and classifies sentiments using deep learning techniques. A lot of work done till now using twitter data requires a lot of time to label the tweets. Twitter possesses huge amount of data and it becomes difficult to label each one of them manually. For training our model tweets were scraped from twitter using Tweepy library in python. We scraped 1 million tweets from first week of January 2023 till first week of February 2023. Tweets were scraped using various queries which are there in Tweepy library. In this paper we have shown the application of VADER which can be used to label unlabelled dataset. After labelling the data using VADER we performed word and GloVe embedding on our dataset. After performing GloVe embedding we performed sentiment analysis using Bi-directional LSTM. Our model achieved an overall accuracy of 97.09%. We also compare the accuracy achieved by other models with our hybrid approach.
Helmet detection algorithm based on improved yolov7

In order to solve the problems of low detection accuracy, wrong detection and missed detection in the traditional target detection algorithm in the safety helmet detection task, a safety helmet detection algorithm based on improved YOLOv7 is proposed. The algorithm is based on the YOLOv7 framework structure. Firstly, in the backbone network, the 3x3 convolution in the ELAN structure is replaced by the SAC convolution, and the receptive field size is adaptively selected in combination with the dilated convolution to improve the detection accuracy. At the same time, the SimAM attention mechanism is introduced to focus on key information and improve the accuracy of model detection. Finally, WIoU loss is used to replace the cross entropy in the original loss function to improve the weight of positive and negative samples, accelerate the convergence speed of the model, and further improve the detection accuracy. The experimental results show that the accuracy of the algorithm on the safety helmet data set is 3.6 percentage points higher than that of YOLOv7, which improves the detection accuracy of the safety helmet and has certain application value.
A Study of Unsupervised Multi-document Sentiment Summarization Techniques Based on Graph Structure

To address the problems of large amount of redundant information and difficulty in extracting key information in commentary text information in the Internet, as well as the problems of difficulty in constructing data sets and limited application fields in summary generation based on supervised multi-document summary methods. In this paper, we propose an unsupervised multi-document sentiment summary extraction method based on multi-featured sentiment-semantic relationship graph. Firstly, a corpus based on news commentaries is collected using a combination of crawler and manual methods, and manual summary extraction is performed; secondly, sentiment features, inflectional words features, keyword features, punctuation features and semantic features are used to construct sentiment-semantic relationship graphs to capture sentence relationships; then, spectral clustering, multi-sentence compression and sentence ranking and selection are used to obtain summaries; finally, the proposed method is experimentally validated on the dataset. The experimental results show that the unsupervised multi-document summary extraction method based on sentiment-semantic relationship graph significantly outperforms other unsupervised methods and is easy to deploy and apply without a heavy learning process compared to supervised methods.
Semantic Topic Extraction from Research Artifacts

The GENESIS project introduces a novel framework for Research Artifact Data Semantics to enhance semantic web technologies within academic institutions. This paper introduces a system developed as part of the GENESIS challenge, focusing on extracting and labelling topics from diverse research artifacts. The approach employs knowledge graphs, topic models, and named entity recognition to infer meaningful topics. Evaluation encompasses measures such as topic coherence and semantic similarity. Future work includes refining entity linking techniques, optimizing system performance, and implementing advanced graph centrality algorithms. This contribution advances semantic understanding in various research contexts.
Detection of Financial Fraudulent Activities with Machine Learning:A Case Study of Detecting Potential Tax and Invoice Fraud

Financial fraud is a widespread problem that can cause significant economic losses. Traditional fraud detection methods often rely on manual audits and rules-based systems, which can be time-consuming and error-prone. In recent years, machine learning methods have emerged as a promising approach to automating fraud detection by leveraging large-scale data analysis. This article explores the use of machine learning methods to detect financial fraud by using tax, invoice, and big data. We first introduce the challenges and opportunities of using these data sources for fraud detection, and then survey various machine learning techniques that have been applied to this problem. We also discuss the evaluation metrics and case studies of these methods, and highlight the potential benefits and limitations of using machine learning for fraud detection. Finally, we identify some future research directions and challenges in this area. This article aims to provide a comprehensive method of the state-of-the-art in using machine learning methods for financial fraud detection, and to inspire further research and development in this important field.