Reviewerly/exHarmony huggingface dataset:
Improving Dialogue Management Through Data Optimization

Authors:
raw_author_name: Cayetano Guerra-Artal

Abstract: In task-oriented dialogue systems, the ability for users to effortlessly communicate with machines and computers through natural language stands as a critical advancement. Central to these systems is the dialogue manager, a pivotal component tasked with navigating the conversation to effectively meet user goals by selecting the most appropriate response. Traditionally, the development of sophisticated dialogue management has embraced a variety of methodologies, including rule-based systems, reinforcement learning, and supervised learning, all aimed at optimizing response selection in light of user inputs. This research casts a spotlight on the pivotal role of data quality in enhancing the performance of dialogue managers. Through a detailed examination of prevalent errors within acclaimed datasets, such as Multiwoz 2.1 and SGD, we introduce an innovative synthetic dialogue generator designed to control the introduction of errors precisely. Our comprehensive analysis underscores the critical impact of dataset imperfections, especially mislabeling, on the challenges inherent in refining dialogue management processes
Evaluation of Medium-Sized Language Models in German and English Language

Authors:
raw_author_name: René Peinl
raw_author_name: Johannes Wirth

Abstract: Large language models (LLMs) have garnered significant attention, but the definition of “large” lacks clarity. This paper focuses on medium-sized language models (MLMs), defined as having at least six billion parameters but less than 100 billion. The study evaluates MLMs regarding zero-shot generative question answering, which requires models to provide elaborate answers without external document retrieval. The paper introduces an own test dataset and presents results from human evaluation. Results show that combining the best answers from different MLMs yielded an overall correct answer rate of 82.7% which is better than the 60.9% of ChatGPT. The best MLM achieved 71.8% and has 33B parameters, which highlights the importance of using appropriate training data for fine-tuning rather than solely relying on the number of parameters. More fine-grained feedback should be used to further improve the quality of answers. The open source community is quickly closing the gap to the best commercial models.
Document Author Classification using Parsed Language Structure

Authors:
raw_author_name: Todd K. Moon
raw_author_name: Jacob H. Gunther

Abstract: Over the years there has been ongoing interest in detecting authorship of a text based on statistical properties of the text, such as by using occurrence rates of noncontextual words. In previous work, these techniques have been used, for example, to determine authorship of all of The Federalist Papers. Such methods may be useful in more modern times to detect fake or AI authorship. Progress in statistical natural language parsers introduces the possibility of using grammatical structure to detect authorship. In this paper we explore a new possibility for detecting authorship using grammatical structural information extracted using a statistical natural language parser. This paper provides a proof of concept, testing author classification based on grammatical structure on a set of “proof texts,” The Federalist Papers and Sanditon which have been as test cases in previous authorship detection studies. Several features extracted from the statistical natural language parser were explored: all sub trees of some depth from any level; rooted subtrees of some depth, part of speech, and part of speech by level in the parse tree. It was found to be helpful to project the features into a lower dimensional space. Statistical experiments on these documents demonstrate that information from a statistical parser can, in fact, assist in distinguishing authors.
Integration of Latex Formula in Computer-Based Test Application for Academic Purposes

Authors:
raw_author_name: Ikechukwu E.Onyenwe
raw_author_name: Ebele Onyedinma
raw_author_name: Obinna Agbata

Abstract: LaTeX is a free document preparation system that handles the typesetting of mathematical expressions smoothly and elegantly. It has become the standard format for creating and publishing research articles in mathematics and many scientific fields. Computer-based testing (CBT) has become widespread in recent years. Most establishments now use it to deliver assessments as an alternative to using the pen- paper method. To deliver an assessment, the examiner would first add a new exam or edit an existing exam using a CBT editor. Thus, the implementation of CBT should comprise both support for setting and administering questions. Existing CBT applications used in the academic space lacks the capacity to handle advanced formulas, programming codes, and tables, thereby resorting to converting them into images which takes a lot of time and storage space. In this paper, we discuss how we solvde this problem by integrating latex technology into our CBT applications. This enables seamless manipulation and accurate rendering of tables, programming codes, and equations to increase readability and clarity on both the setting and administering of questions platforms. Furthermore, this implementation has reduced drastically the sizes of system resources allocated to converting tables, codes, and equations to images. Those in mathematics, statistics, computer science, engineering, chemistry, etc. will find this application useful.
A Comparative Study of Text Comprehension in IELTS Reading Exam using GPT-3

Authors:
raw_author_name: Tauheed Khan Mohd

Abstract: This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the context of text understanding. We begin by describing the architecture and training process of GPT-3, and provide an overview of its impressive performance across a wide range of natural language processing tasks, such as language translation, question-answering, and text completion. Throughout this research project, a summarizing tool was also created to help us retrieve content from any types of document, specifically IELTS (0) Reading Test data in this project. We also aimed to improve the accuracy of the summarizing, as well as question-answering capabilities of GPT-3 (0) via long text.
Analisis Kemampuan Komunikasi Siswa Autis Kelas VII di SLB Negeri Autis Sumatera Utara (Studi Kasus Siswa Autis di SLB Negeri Autis Sumatera Utara)

Authors:
raw_author_name: Rafael Lisinus Ginting
raw_affiliation_string: Universitas Negeri Medan

Abstract: This research was conducted with the aim of knowing how the communication development of class VII autistic students at SLB Negeri Autism North Sumatra and to find out the forms of verbal and non-verbal communication. The method used in this study is a qualitative method with a case study approach. The primary subjects in this study were two students with autistic disorder in class VII autistic, and the secondary subjects were teachers and parents. Data were collected using interviews, observation, and documentation studies. The results showed that the development of communication in autistic students at the North Sumatra Autistic Public SLB was influenced by several things including the teacher's stimulus when teaching, therapy, children's hobbies, and parenting strategies. Forms of children's verbal communication is speaking, writing, reading, and listening. While the forms of non-verbal communication are touch, movement, and eye contact. Based on the research findings, it can be concluded that communication disorders in autistic children can be helped by providing stimulus by being invited to communicate more often and implementing appropriate parenting strategies.
Analisis Gaya Belajar Mahasiswa Program Studi Pendidikan Bahasa Indonesia Universitas Katolik Weetebula

Authors:
raw_author_name: Melkianus Suluh
raw_affiliation_string: Universitas Katolik Weetebula

Abstract: The purpose of this study is to describe learning styles and describe solutions in presenting learning in accordance with the learning styles of students of the Indonesian Education Study Program, Weetebula Catholic University. This type of research is survey research with a qualitative descriptive approach. The subject of this study was a student of PBI Study Program, Weetebula Catholic University. The data collection technique used in this study was questionnaire. Based on the results of the study, it was found that students who tended to visual learning style as much as 53.74%, auditorial learning style as much as 29.43%, and kinesthetic learning style as much as 16.83%. The results of these findings show that the most dominant type of learning style of Indonesian Education Study Program students is the visual learning style type. Lecturers in presenting learning the main type of learning used is the visual type of learning. To accommodate the other two learning styles, learning needs to be supported by auditorial and kinesthetic learning types. Research related to learning styles is important. The results of the research can be information for teachers or lecturers in making learning designs that are in accordance with the learning styles of students so that students can absorb the material optimally
Teacher’s Talk in English Classroom Using Foreign Language Interaction (FLINT) System

Authors:
raw_author_name: None Clarry Sada
raw_affiliation_string: Universitas Tanjungpura Pontianak
raw_author_name: None Eka Fajar Rahmani
raw_affiliation_string: Universitas Tanjungpura Pontianak

Abstract: The researcher conducted the research to describe the teacher and student interaction during the teaching-learning process and to analyze the frequent FLINT categories by Moskowitz (1976). The participant in this research was an English female teacher taught in class VII F at SMP Negeri 1 Sungai Raya in the academic year 2022/2023. This research was a case study design that used qualitative method. The data was collected by observing the teacher and student interaction during the teaching-learning process. The researcher used the teacher talk video transcript in analyzing the FLINT categories. The result of the research showed that the teacher’s dominant language was Bahasa Indonesia. The teacher’s utterances in Bahasa Indonesia appeared 95 times during the teaching-learning process, which means the teacher used Bahasa Indonesia in English lessons. The teacher should be built good oral during the teaching-learning process, not only focus on delivering the material. The frequent categories used by the teacher were giving information and asking questions. Moreover, the rare category the teacher used was the student’s ideas. Through analyzing the FLINT system, teacher talk in the classroom was accessible in describing the dominant language performed by the teacher and analyzed frequent categories used by the teacher during the teaching-learning process.
Pengaruh Media Pembelajaran Informasi dan Komunikasi Teknologi dan Minat Belajar Terhadap Hasil Belajar Siswa pada Mata Pelajaran IPS di SMP Negeri 1 Ingin Jaya Kabupaten Aceh Besar

Authors:
raw_author_name: Murdani Murdani
raw_affiliation_string: Universitas Bina Bangsa Getsempena
raw_author_name: Sariakin Sariakin
raw_affiliation_string: Universitas Bina Bangsa Getsempena
raw_author_name: Mardhatillah Mardhatillah
raw_affiliation_string: Universitas Bina Bangsa Getsempena

Abstract: This research aims to improve the learning process with a variety of ICT-based media and examine the influence of information and communication technology learning media and learning interest on student learning outcomes in Social Sciences subjects at the Want Jaya 1 State Junior High School, Aceh Besar Regency. This research is a type of survey research with quantitative methods. the results of the research show that: there is an influence of information media and communication technology and interest in learning on student learning outcomes in social sciences subjects at the 1 Want Jaya State Junior High School, Aceh Besar Regency which together have a significant influence, this can be seen from the three variables. has a high influence, namely 34.5 for the learning media variable and 37.9 for the learning interest variable, 0.24, which means the learning media and learning interest variables, and the school environment has an influence of 24.4% on learning outcomes, while the second These variables together have an influence on student results in the Social Sciences subject at Want Jaya State Junior High School 1, amounting to 49.4.
Exploring the Adoption of the Metaverse System among Elementary Students

Authors:
raw_author_name: None Raghad Alfaisal
raw_affiliation_string: Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim, Perak, Malaysia
raw_author_name: None Haslinda Hashim
raw_affiliation_string: Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim, Perak, Malaysia
raw_author_name: None Ummu Husna Azizan
raw_affiliation_string: Faculty of Computing and Meta-Technology, Universiti Pendidikan Sultan Idris, 35900 Tanjong Malim, Perak, Malaysia

Abstract: The metaverse is an envisioned realm offering immersive digital spaces, bolstering highly interactive environments within educational contexts. This digital dimension amplifies synchronous communication, uniting a vast number of users as they share their unique experiences. This research aims to scrutinize the perceptions of elementary students towards the metaverse system (MS). Our proposed model underwent validation through the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique. Data, sourced from 287 students of Dubai National School, revealed that the primary predictor of students' intent to engage with the MS is personal innovativeness. This is followed closely by perceived usefulness and then perceived ease of use. The findings of this research provide deeper insights into the driving factors behind the adoption of MS among young learners.
METODE ENSEMBLE ROBUST CLUSTERING USING LINKS (ROCK) UNTUK PENGELOMPOKAN PERGURUAN TINGGI SWASTA (PTS) DI KOTA SEMARANG

Authors:
raw_author_name: Iut Tri Utami
raw_author_name: Arief Rachman Hakim

Abstract: The purpose of this research is to group PTS that have performance achievements in five years, through the quality of Human Resources and Students (Input), the quality of Institutional Management (process), the quality of Short-Term Performance Achievements (Output) and the quality of Long-Term Performance Achievements (Outcome). In addition, it can also be seen from the form of PTS, PTS Accreditation and PTS Research Performance. This PTS grouping uses mixed data, namely numerical data and categorical data. The method used for grouping mixed data is the ROCK ensemble method (Robust Clustering Using Links). The results of clustering numerical data obtained the optimum number of groups 3, on categorical data obtained the optimum group 4. After clustering each type of data and merging and clustering obtained the optimum group 3 with a threshold (θ) is 0.2. The results of each group are: low quality consist of 29 PTS, medium quality consist of 7 PTS, and high quality there is 1 PTS. The results of this research can be used to cluster private universities in Semarang City, so that it can be used as a reference for prospective students in choosing private universities in Semarang, and can be referenced to the Central Java LLDIKTI in determining the quality of private universities in Semarang City.
Identifikasi Faktor Kesulitan Belajar Membaca Siswa di Kelas VI di SDN Karangpawitan III

Authors:
raw_author_name: Amelia Amelia
raw_affiliation_string: Universitas Buana Perjuangan Karawang
raw_author_name: Sonia Nadia Sari
raw_affiliation_string: Universitas Buana Perjuangan Karawang
raw_author_name: Yayan Alpian
raw_affiliation_string: Universitas Buana Perjuangan Karawang

Abstract: This study aims to determine the factors that cause difficulties in learning to read for students. The type of this research is descriptive qualitative research. The subjects of this research consist of sixth grade students and the homeroom teacher of the sixth grade. Data collection methods include interviews, observations, and documentation. The data obtained is then analyzed to determine the internal and external factors that cause difficulties in learning to read for students. The results of the study show that the factors causing difficulties in learning to read for sixth grade students at SDN Karangpawitan III are caused by internal factors (low intelligence, low student learning motivation, low student interest in reading, as well as social and emotional maturity and unstable student adjustment) and external factors (less varied teaching methods by teachers and lack of parental attention to students in the family environment). Therefore, it can be concluded that there are several factors causing difficulties in learning to read for students, namely internal and external factors.
PERBANDINGAN KINERJA METODE KLASIFIKASI K-NEAREST NEIGHBOR DAN SUPPORT VECTOR MACHINES PADA DATASET PARKINSON

Authors:
raw_author_name: Triastuti Wuryandari
raw_affiliation_string: Departemen Statistika, Fakultas Sains dan Matematika, Undip, Indonesia
raw_author_name: Arief Rachman Hakim
raw_affiliation_string: Departemen Statistika, Fakultas Sains dan Matematika, Undip, Indonesia

Abstract: The government program in the form of social assistance (bansos) is part of the effort to improve the welfare of the community and ensure basic needs and improve the standard of living of the recipients. However, there are often cases of mistargeting of social assistance programs by the government. Improper data management and Data Terpadu Kesejahteraan Sosial (DTKS) which are not used as the cause of the distribution of social assistance are not well targeted. The data can be analyzed using the classification method to determine whether or not the family accepts the ban from the government. This study classifies the SUSENAS data by comparing K-Nearest Neighbor (KNN) and Support Vector Machines (SVM). The advantage of the KNN method lies in the level of accuracy to solve problems with large data while the SVM method has better performance in various fields of application such as bioinformacs, handwriting recognition, text classification and so on. Based on training data and testing data comparison 85%:15% showed that KNN method had a better classification performance than the SVM method. The accuracy value of KNN method is 80,95% higher than the accuracy value of SVM method is 78,79%.
The Effects of Education Service Quality and University Image on Student Satisfaction and Switching Intention - Focusing on Tourism/Hotel Departments of Four-Year Course Local University -

Authors:
raw_author_name: Jinyoung Lee

Abstract: This study is intended to investigate the influences of education service quality and university images on students' satisfaction and switching intention for those who major in hotel·tourism at local universities. Through the empirical analysis, the levels of education service quality is identified to enhance the quality of education, to establish school images and to improve value cognition, so that hotel·tourism related majors can be improved and developed. For the accomplishment of the purpose of this study, a survey was conducted on hotel·tourism majors in local four-year-course universities, and the data collection was done from May 20 to June 18, 2023. For the response samples, total 154 copies were used, and multiple regression analysis was done with the use of SPSS.20. In the results of the analysis, three factors of human, facility and welfare services in the education service quality have a significant influence relation, but administrative and education services were dismissed. Therefore, the hypothesis was partially adopted. The university image had a significant impact on student satisfaction, and student satisfaction had a negative impact on switching intention. In addition, the human service was the only one among the education service quality that had a negative impact on switching intention, which led to partial adoption. Based on the above results, this study can be used for basic resources to establish methods to prevent switching intention by comprehending improvement factors of education service quality and by enhancing student satisfaction.
Informasi Anatomi MSCT Sinus Paranasal pada Suspek Sinusitis dengan Variasi Rekonstruksi Algorithma

Authors:
raw_author_name: Sri Mulyati
raw_affiliation_string: JTRR Health Polytechnic Semarang
raw_author_name: Gatot Murti Wibowo
raw_affiliation_string: JTRR Health Polytechnic Semarang
raw_author_name: Jeffri Ardiyanto
raw_affiliation_string: JTRR Health Polytechnic Semarang

Abstract: Background: The standard operating procedure with the bone window technique and bone reconstruction algorithm is referred to the MSCT protocol for paranasal sinuses in Hospital. However, the majority of radiologists select a protocol that implements the algorithm reconstruction, which is still trial and error without an organized protocol development study. There is a chance that the accuracy of the MSCT SPN and the quality of the picture data may become crucial problems. This study set out to assess and examine the algorithmic reconstruction method that can yield more accurate SPN anatomical data in sinusitis suspects.Methods: A quasi-experimental technique was taken in conducting the research. Three filters (bone, boneplus, and edge) of the reconstruction method were used to get thirty SPN images from ten patients. The images were assessed by the two expert radiologist.Results: The results of non-parametric was obtained based on statistical tests using the Friedman test ρ-value of anatomy, namely 0.00 less than 0.05. These results indicate that H0 is rejected and Ha is accepted, meaning that there are differences in anatomical information between variations of bone, boneplus, and edge reconstruction algorithms on the MSCT scan examination of the paranasal sinuses with sinusitis suspect. The Friedman test results using the mean rank values of each anatomy show that Boneplus is superior in terms of visualizing anatomy. The Friedman test's mean rank value of the entire anatomy yielded the result that the boneplus reconstruction algorithm is superior to the bone and edge reconstruction algorithm in displaying anatomical information on the MSCT scan of the paranasal sinuses with sinusitis suspect.Conclusions: Based on value mean rank For each Friedman test anatomy and the results of the frequency distribution, variations of the bone plus reconstruction algorithm are more optimal in displaying anatomical information on the MSCT Scan of the paranasal sinuses compared with the edge and bone reconstruction algorithms.