Reviewerly/exHarmony huggingface dataset:
DIGGING UP NON-ENGLISH TEACHERS’ PERSPECTIVES ON THEIR STUDENTS’ ESP NEEDS

This study aims to identify and explore non-English teachers' perspectives on their students' ESP needs. This study is a descriptive study with a qualitative approach. The participants in this study were 16 public health lecturers at STIKes Surya Global Yogyakarta. A semi-structured questionnaire was distributed to participants to gather information related to their needs. The study analyzes the data from closed questions using simple statistics and from open questions using interpretations. The results showed that the importance of learning English is to support students’ academic fields and their communication skills. Reading is a basic skill that needs to be mastered. The students found it difficult to write English journal abstracts, practice oral communication, read, comprehend, and review academic sources in English. Teachers sometimes use English in the form of resources including books written in English and international journals and websites. Students need to learn English during their study period and after graduation. The topics needed to learn to support students’ backgrounds were health technology, health business service management, web causation of disease, health insurance, abstract, environmental health, health information system, safety, health promotion, epidemiology triangle, iceberg phenomenon of disease, research design epidemiology, epidemic, and infectious diseases, wastewater treatment, hygiene, and sanitation.Keywords: Students’ needs, ESP, public health students
AN ANALYSIS ON THE FOURTH SEMESTER STUDENTS’ ABILITY IN USING PRONOUN AT THE ENGLISH EDUCATION DEPARTMENT OF STKIP INSAN MADANI AIRMOLEK

The method used to conduct this research was the descriptive qualitative method. The sample of the research was the fourth-semester students of the English Education Department which consisted of 24 students. The aim of this research is to know their ability in using pronouns. To collect the data, a written form of the test was used and it was divided into two categories (multiple choice and essay). The students were then asked to do the test of pronouns of a subject, object, adjective possessive, possessive and reflexive. The design of the test was based on the relevant literature review and the authors’ observation when the teaching and learning process about pronouns took place. After the analysis of the data, the average score obtained from the student's test was 6.4 which belonged to the fair good category. The result of the test showed 23 students (96%) whose abilities were in the middle category, 1 student (4%) whose ability was in the low category, and 0 students (0%) whose ability was in the high category. Even though the results make the authors surprised, the findings of the research can give some points of view for a lecturer to prepare the lesson materials better, apply various teaching techniques to get the student's attention and interest during the teaching-learning process and use various teaching aids to support the success of his teaching so that the students could have better understanding and competence in English.Keywords: Ability, Pronoun
Provably Constant-time Planning and Replanning for Real-time Grasping Objects off a Conveyor Belt

In warehouse and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick and place tasks. Because objects on the conveyor belts are moving, robots have limited time to pick them up. This brings the requirement for fast and reliable motion planners that could provide provable real-time planning guarantees, which the existing algorithms do not provide. Besides the planning efficiency, the success of manipulation tasks relies heavily on the accuracy of the perception system which is often noisy, especially if the target objects are perceived from a distance. For fast moving conveyor belts, the robot cannot wait for a perfect estimate before it starts executing its motion. In order to be able to reach the object in time it must start moving early on (relying on the initial noisy estimates) and adjust its motion on-the-fly in response to the pose updates from perception. We propose an approach that meets these requirements by providing provable constant-time planning and replanning guarantees. We present it, give its analytical properties and show experimental analysis in simulation and on a real robot.
Review of approaches for paraphrase identification

The article is devoted to a review of approaches to solving the problem of identifying paraphrases. This problem's relevance and use in tasks such as plagiarism detection, text simplification, and information search are described. Several classes of solutions were considered. The first approach is based on manual rules - it uses manually selected features based on the fundamental properties of paraphrases. The second approach is based on lexical similarity and various databases and ontologies. Machine learning-based approaches are also presented in this paper and describe different architectures that can be used to identify paraphrases. The last approach considered is based on deep learning and modern models of transformers.
New approach to similarity detection by combining technique three-patch local binary patterns (TP-LBP) with support vector machine

&lt;p&gt;Recognition systems have received a lot of attention because of their various&lt;br /&gt;uses in people's daily lives, for example in robotic intelligence, smart cameras,&lt;br /&gt;security surveillance or even criminal identification. Determining the&lt;br /&gt;similarity of faces by different face variations is based on robust algorithms.&lt;br /&gt;The validation of our experiment is done on two sets of data. In this paper, we&lt;br /&gt;compare two facial recognition system techniques according to the&lt;br /&gt;recognition rate and the average authentication time: in order to increase the&lt;br /&gt;accuracy rate and decrease the processing time. our approach is based on&lt;br /&gt;feature extraction by two algorithms principal components analysis scaleinvariant feature transform (PCA-SIFT) and speeded up robust features (SURF), then uses the random sample consensus (RANSAC) technique to cancel outliers. Finally, face recognition is established on the basis of proximity determination. The second technique is based on the association of support vector machine (SVM) classifier with the key point recovery technique. the results obtained by the second technique is better for both databases: The recognition rate of the base olivetti research laboratory (ORL) should be 98.125800 and that of the Grimace base 97.2851500. The evaluation according to the time of the second technique does not exceed 300ms on average.&lt;/p&gt;
Utilizing deep learning, feature ranking, and selection strategies to classify diverse information technology ticketing data effectively

In today's internet world, information technology (IT) ticketing services are potentially increasing across many corporations. Therefore, the automatic classification of IT tickets becomes a significant challenge. Feature selection becomes most important, particularly in data sets with several variables and features. However, enhance classification's precision and performance by stopping insignificant variables. Through our earlier research, we have categorized the unsupervised ticket dataset. As a result, we have converted the dataset into a supervised dataset. In this article, the classification of different IT tickets on Machine learning algorithms, Feature ranking, and feature selection techniques are used to improve the efficiency of machine learning algorithms. However, compared to the machine learning (ML) algorithms, the convolutional neural network (CNN) algorithm provides a better classification of the token IDs and provide better accuracy.
Glove based wearable devices for sign language-GloSign

&lt;p&gt;Loss of the capability to talk or hear has psychological and social effects on&lt;br /&gt;the affected individuals due to the absence of appropriate interaction. Sign&lt;br /&gt;Language is used by such individuals to assist them in communicating with&lt;br /&gt;each other. This paper proposes a glove called GloSign that can convert&lt;br /&gt;American sign language to characters. This glove consists of flex and inertial&lt;br /&gt;measurement unit (IMU) sensors to identify gestures. The data from glove is&lt;br /&gt;uploaded on IoT platform, which makes the glove portable and wireless. The&lt;br /&gt;data from gloves is passed through a k-nearest neighbors (KNN) Algorithm&lt;br /&gt;machine learning algorithm to improve the accuracy of the system. The&lt;br /&gt;system was able to achieve an accuracy of 96.8%. The glove can also be used&lt;br /&gt;to form sentences. The output is displayed on the screen or is converted to&lt;br /&gt;speech. This glove can be used in communicating with people who don’t know&lt;br /&gt;sign language.&lt;/p&gt;
Peningkatan Aktivitas dan Prestasi Belajar Matematika Materi Pengolahan Data Menggunakan Metode Kerja Kelompok pada Siswa Kelas VI SDN 3 Sribhawono Lampung Timur TP 2017/2018

The purpose of this study is to describe the increase in learning activity and achievement using the group work method, in class VI mathematics learning at SDN 3 Sribhawono East Lampung TP 2017/2018. The method used is Classroom Action Research (CAR). Data collection techniques with observation guidelines to obtain data about student learning activities and learning achievement tests at the end of each research cycle. Furthermore, the data obtained were analyzed descriptively qualitatively. The results showed that the use of the group work method can increase the activity and achievement of learning mathematics in class VI SDN 3 Sribhawono Lampung.
Reducing the time needed to solve a traveling salesman problem by clustering with a Hierarchy-based algorithm

&lt;div class="page" title="Page 1"&gt;&lt;div class="layoutArea"&gt;&lt;div class="column"&gt;&lt;p&gt;In this study, we compare a cluster-based whale optimization algorithm (WOA) with an uncombined method to find a more optimized solution for a traveling salesman problem (TSP). The main goal is to reduce the time of solving a TSP. First, we solve the TSP with the Whale optimization algorithm, later we solve it with the combined method of solving TSP which uses the clustering method, called BIRCH (balanced iterative reducing and clustering using hierarchies). Birch builds a clustering feature (CF) tree and then applies one of the clustering methods (for ex. K-means) to cluster data. Experiments performed on three datasets show that the convergence time improves by using the combined algorithm.&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;
PLACING CULTURE IN ENGLISH LANGUAGE TEACHING: THE INDONESIAN EFL STUDENTS’ PERCEPTION

This research article presents the study about the EFL students’ perception on placing culture in ELT practice, especially in Indonesia context. The purpose of this survey study is to examine students’ perception on the integration of culture into ELT practice. The participants were the third-semester students in Mathematics Education Study Program, STKIP PGRI Bandar Lampung (Institute of Teachers Training and Education of PGRI Bandar Lampung), Indonesia. The data was collected using a questionnaire which was posted for the students who were taking the compulsory English subject. It is found that tertiary level students in Indonesia have realized the necessity and importance of placing culture in learning English. One of the importance is that placing culture into English classes could encourage students’ interest and motivation in learning English. The students also agree that their English language skills, speaking, writing, reading and listening, influenced by the existence of cultural content in their learning activities could be improved. Consequently, the culture-based materials are suggested to be developed.
Improving Indonesian multietnics speaker recognition using pitch shifting data augmentation

Speaker recognition to recognize multiethnic speakers is an interesting research topic. Various studies involving many ethnicities require the right approach to achieve optimal model performance. The deep learning approach has been used in speaker recognition research involving many classes to achieve high accuracy results with promising results. However, multi-class and imbalanced datasets are still obstacles encountered in various studies using the deep learning method which cause overfitting and decreased accuracy. Data augmentation is an approach model used in overcoming the problem of small amounts of data and multiclass problems. This approach can improve the quality of research data according to the method applied. This study proposes a data augmentation method using pitch shifting with a deep neural network called pitch shifting data augmentation deep neural network (PSDA-DNN) to identify multiethnic Indonesian speakers. The results of the research that has been done prove that the PSDA-DNN approach is the best method in multi-ethnic speaker recognition where the accuracy reaches 99.27% and the precision, recall, F1 score is 97.60%.
THE USE OF GOOGLE CLASSROOM TO TEACH ENGLISH FOR COLLEGE STUDENTS

The education system implemented in Indonesia in the new normal era underwent changes. Prevention of transmission of the corona virus by social distancing to avoid potential crowds is the main reason children have to go to school from home. Changes that occur include education which was originally face-to-face to online or online only. Another thing that has changed is the adjusted learning targets and also the adaptation of the curriculum used. education is required to adapt immediately. Education must not stop just because of the impact of the spread of Covid-19. One of the online learning media that is currently developing and starting to be used is Google Classroom. Google Classroom is a special application that is used for online learning carried out remotely and can be used anywhere. In using the Google Classroom application, it contains services for users such as being able to send assignments in the form of documents, photos, and learning videos to students related to the material discussed. This research aimed to know the benefits of google classroom and how the teachers and students use google classroom The methods used in this survey were library surveys and interviews. Arikunt discovers that literary studies in research are a way to collect data by finding information from books, newspapers, magazines, and other literature to build a theoretical foundation. I did (Arikunto, 2006)In addition to this opinion, literary research is a data collection technique by researching books, literature, records, and reports related to solved problems (Nazir, 1988)Data and information are available from academic books, research reports, academic papers, sets of rules, encyclopedias, diplomas, and other written and digital sources. In addition, we conducted a similar survey and collected data on Google classrooms and education usage during the pandemic. researcher concluded that the use of google classroom in coaching English for the pandemic is compelling withinside the mastering manner because the academics and college students can without problems to get entry to the google classroom. The instructor can set up the elegance, supply the material and supply the assignmentKeyword : During learning, Pandemic Covid-19, Google Classroom
Productivity of incident management with conversational bots-a review

&lt;p&gt;The use of conversational agents (bots) in information systems managed by company’s increases productivity in the development of activities focused on processes such as customer service, healthcare, and presentation. The present work is a systematic literature review that collects articles from 2019 to 2022 in the databases Scopus, Springer, Willey, Indexes-Csic, Taylor &amp;amp; Francis, Pubmed, and Ebsco Host. PRISMA methodology was used to systematize 47 relevant articles. As a result of the analysis, 2/19 very important benefits were obtained, which are: helping to obtain information and facilitating customer service; as for the types of conversational bots, a total of 9 types were found, of which conversational agents and chatbots with artificial intelligence (AI) are the most common; in the case of processes, 3/5 processes that optimize conversational bots were found, where the most prominent are: teaching process, health processes, and customer service processes. An architecture model for conversational bots in incident management is also proposed.&lt;/p&gt;
AN ERROR ANALYSIS IN WRITING RECOUNT TEXT AT SMPN 02 SEPAUK

The main problem of this research is the researcher wants to analyze the students' errors in writing recount text. This research aims to find out the error made by students in writing recount text. The subject of this research is 22 students writing products in writing recount text. The method used in this research is a qualitative research approach, the technique of data collection only using documentation, the document is the student's test results in writing recount text. The qualitative data were analyzed through assembling the data, coding the data, comparing the data, building interpretations, and reporting the outcomes. Based on the research finding, the researcher found three types of errors made by students in writing recount text: error of omission 54,9%, error of misinformation 19,6%, error of misordering 25,5%. Based on the finding, the researcher found omission error was a dominant error made by eight grade students of SMP Negeri 02 Sepauk.
Eligibility of village fund direct cash assistance recipients using artificial neural network

&lt;p&gt;Bantuan Langsung Tunai Dana Desa (BLT-DD), or known as Village Fund Direct Cash Assistance is assistance from the Indonesian government which causes problems and conflicts in the community when the assistance is not on target. The classification algorithm is proven to use in determining BLT-DD recipients. In this study, the radial basis function (RBF) and elman recurrent neural network (ERNN) models compare to classify the eligibility of BLTDD recipients. In the experiment, the optimal performance of the RBF and ERNN compare in determining the eligibility of BLT-DD recipients. Also, it’s compared with the classification algorithm that implements the same data, namely BLT-DD data for Kubu Raya District. The experimental results show the effectiveness of the RBF model in recognizing test data, while the ERNN model is effective in identifying test data. The RBF and ERNN models can achieve the same total accuracy of 98.10%.&lt;/p&gt;
Perkembangan Motif Batik Gonggong Khas Kota Tanjungpinang (2010-2020)

In Indonesia, batik grows and develops as a manifestation of cultural wealth in Indonesia so that there are product innovations from various regions and each region has an icon to make it easier for customers to remind batik products from each region. Batik, which originally only existed in Java, especially Central Java, then developed into other regions and each region has a variety of batik patterns that are characteristic of each region. Among other areas, the Riau Archipelago (Kepri) has batik with its distinctive style, namely marine biota such as gonggong. In this study the researchers compiled and described the development of Batik Gonggong because it was still not well known by the people and was rarely used even though it had become a typical batik from the City of Tanjungpinang. Therefore, to find out the history and development of Gonggong Batik and the government's role in preserving Gonggong Batik, this research was conducted. This study uses descriptive qualitative research methods with data collection techniques, namely through interviews, observation, documentation and literature study. From the results of the study, it was found that Efiyar A. Amin was the first to create or pioneer the Batik Gonggong motif typical of Tanjungpinang City in 2010. The government plays a role in maintaining this batik through various events held.
Classification and visualization: Twitter sentiment analysis of Malaysia’s private hospitals

Malaysia has many private’s hospitals. Thus, feedback is important to improve service quality, becoming reviews for other patients. Reviews use the channel service provided on social media, such as Twitter. Nevertheless, online reviews are unstructured and enormous in volume, which leads to difficulties in comparing private hospitals. In addition, no single websites compare private hospitals based on users’ interests, bilingual reviews, and less time-consuming. Due to that, this study aims to classify and visualize the Twitter sentiment analysis of private hospitals in Malaysia. The scope focuses on five factors: 1) administrative procedure, 2) cost, 3) communication, 4) expertise, and 5) service. Term frequency-inverse document frequency is used for text mining, information retrieval techniques, and the Naïve Bayes, a machine learning algorithm for the classification. The user can visualize the specified state’s private hospitals and compare them with any selected state. The system’s functionality and usability have been tested to ensure it meets the objectives. Functionality testing proved that the private hospital’s Twitter sentiment could be predicted based on the training and testing data as intended, with 77.13% and 77.96% accuracy for English and Bahasa Melayu, respectively, while the system usability scale based on the usability testing resulted in an average final score of 95.42%.
AN ANALYSIS OF INFLECTIONAL MORPHOLOGY USED IN STUDENTS’ WRITING

The study aimes to analyse inflectional morphology used in students’ writing. It is qualitative study. There were 73 students the fourth semester of English department of STKIP PGRI Bandar Lampung who were taken purpossively as the sample. It is found that, from 554 sentences, there are 17.15% (or 95 words) errors made by the students in the forms of nouns, 19.13% (or 106 words) errors in the forms of pronouns and determiners, 96.2% (or 533 words) errors in the forms of verbs, and 2.53% (or 14 words) errorrs in the forms of adjectives. Based on the results, it is known that the EFL learners mostly made errors in using verbs in the term of infectional mophology.
CAPACITY BUILDING CIVITAS AKADEMIKA STAI AL HUSAIN DALAM PEMANFAATAN SISTEM INFORMASI AKADEMIK

Good academic civitas data processing will make the reporting needed by the appropriate database to process policies such as national diploma numbering (PIN), this is very much required to minimize cases of diploma forgery that are rife, to complete and report appropriate civitas data, there must be optimal facilities, infrastructure, and resources. The purpose of this service is to find out the optimization of data processing for the STAI Al Husain academic community with the educational information system (SIAKAD) through mentoring activities with the ABCD approach, and this approach is to empower existing assets. In carrying out an ABCD-based process, we must look for the availability of assets and synchronization with the academic community's role to measure the success of ABCD. The data processing and reporting activities of the academic community that are accompanied have basically produced results, such as the data is appropriate, and the reporting is applicable. However, they still find the role of the community who still do not understand well about Siakad and still need assistance.