Library Services during COVID-19 Pandemic: A Bibliometric Analysis and knowledge Mapping

The increased usage of libraries during the Covid-19 pandemic has been well known to science communicators, but scientific communication has not evaluated the distributions of its published findings. Thus, this study intends to identify and map library services in international publishing, particularly the Scopus database during the pandemic. Sixty-four publications in the Scopus database were assessed using the bibliometric approach and fifty-seven documents are considered. To find documents from January 2020-June 2021, the author utilized keywords such as library services AND covid-19. Microsoft excels and VOSviewer software was used to analyze the result and visualize the knowledge map. The results showed that most of the papers are dealt with favorable and adoptive library services techniques, implementation of different users demands during the pandemic. The study found the most prolific authors. Rafiq, M., Batool, S. H., Ali, A. F., & Ullah, M. received a maximum of 20 citations from a single document and Michalak R., Ortiz-Díaz E.M., Pacheco-Mendoza J., Rysavy M.D.T., Saavedra-Alamillas C. published 2 documents each. The United States of America is ranked top to publish the scholarly publication on the Library Services during the COVID-19 related documents with 21 documents. India is in the 2nd rank with eight papers, followed by Pakistan, China, Nigeria, Peru, and South Korea. As a result, publications concerning this topic have a high likelihood of emerging. The most frequent terms used by authors are COVID-19(22.90%), library services (7.01%), academic libraries (5.61%). The shift towards advanced virtual and digital services offers more than just boosting librarians and library patrons; it serves as a move to keep the library relevant in a tech-centered society

Enhancing Hate Speech Detection in Sinhala Language on Social Media using Machine Learning

To counter the harmful dissemination of hate speech on social media, especially abusive outbursts of racism and sexism, automatic and accurate detection is crucial. However, a significant challenge lies in the vast sparsity of available data, hindering accurate classification. This study presents a novel approach to Sinhala hate speech detection on social platforms by coupling a global feature selection process with traditional machine learning, the research scrutinizes hate speech intricacies. A class-based variable feature selection process evaluates significance via global and local scores, identifying optimal values for prevalent classifiers. Utilizing class-based and corpus-based evaluations, we pinpoint optimal feature values for classifiers like SVM, MNB, and RF. Our results reveal notable enhancements in performance, specifically the F1-Score, underscoring how feature selection and parameter tuning work in tandem to boost model efficacy. Furthermore, the study explores nuanced variations in classifier performance across training and testing datasets, emphasizing the importance of model generalization

Institutional Repositories in the Indonesian Higher Education Sector: Current State and Future Prospect

This research aims to provide the first detailed survey of various aspects of institutional repositories serving Indonesia’s higher education sector. This includes establishing the current state of implementation of repositories and their major characteristics, and assessing their future potential. The study adopts a mixed-methods research strategy. Methods employed are: 1) a longitudinal content analysis of university repository websites; 2) an online survey of Indonesian academics; and 3) interviews with stakeholders in three Indonesian universities

Biopsychosocial Assessment and Ergonomics Intervention for Sustainable Living: A Case Study on Flats

This study proposes an ergonomics-based approach for those who are living in small housings (known as flats) in Indonesia. With regard to human capability and limitation, this research shows how the basic needs of human beings are captured and analyzed, followed by proposed designs of facilities and standard living in small housings. Ninety samples were involved during the study through in- depth interview and face-to-face questionnaire. The results show that there were some proposed of modification of critical facilities (such as multifunction ironing work station, bed furniture, and clothesline) and validated through usability testing. Overall, it is hoped that the proposed designs will support biopsychosocial needs and sustainability

Examining the effectiveness of a GeoGebra-assisted open-ended approach on students’ mathematical creative thinking ability

Researchers use open-ended as a learning method to help students improve their math skills. Each open investigation of mathematical knowledge produces mixed results for components of mathematical ability, each school level, and the content taught. There are more and more studies on open-ended questions nowadays. This study tested the effectiveness of the open-ended approach assisted by GeoGebra on students' mathematical creative thinking abilities. The use of meta-analysis techniques is to analyze the effect (effect size) of a preliminary study. The instruments used were coding protocol sheets and coding sheets/Comprehensive Meta-Analysis (CMA) programs to analyze data. The resulting findings are that there are differences in the research method with the most significant effect size in the quasi-experimental research method, the research year with the most significant effect size in the 2012-2022 research year, indexing journals with the most significant effect size on web indexing scientific journals; the type of publication that has the most critical influence on the kind of thesis publication. Furthermore, the GeoGebra-assisted open-ended approach to creative thinking ability has no significant effect when viewed from the research characteristics of the sample size and level of education

The Student's Perception of The Use of The Google Form Application for Assessment at Senior High School

Google Forms is an educational application that teachers use in teaching activities to assess students. Teachers usually create questions, quizzes, and assessments through Google Forms. This research investigated the student's perception of the Google Form application as an instrument for assessment that teachers use. The researcher used a quantitative descriptive method through an online Malang senior high school students’ questionnaire. Twenty-nine students have used Google Forms in English learning for assessment, and to get more information about their perceptions in experiences using it, the researcher needs to give 16 questions in online questionnaires. The researchers found more than a few issues that stimulus the students' online learning process in assessment: In terms of utility, convenience of use, ease of learning, and satisfaction, 62.0% of participants believed that Google Forms is practical. 51.1% of them agree that the application is simple to use. The next component also agrees that 57.1% of the students went through easiness to learn how to utilize the software. The last is about the level of satisfaction; 61.8% of the students experience satisfaction. The results showed that oogle Forms can be very helpful in boosting students' abilities, skills, discipline, and impartial learning through instructional resources

Plagiarism detection for Indonesian texts

As plagiarism becomes an increasing concern for Indonesian universities and research centers, the need of using automatic plagiarism checker is becoming more real. However, researches on Plagiarism Detection Systems (PDS) in Indonesian documents have not been well developed, since most of them deal with detecting duplicate or near-duplicate documents, have not addressed the problem of retrieving source documents, or show tendency to measure document similarity globally. Therefore, systems resulted from these researches are incapable of referring to exact locations of ``similar passage'' pairs. Besides, there has been no public and standard corpora available to evaluate PDS in Indonesian texts. To address the weaknesses of former researches, this thesis develops a plagiarism detection system which executes various methods of plagiarism detection stages in a workflow system. In retrieval stage, a novel document feature coined as phraseword is introduced and executed along with word unigram and character n-grams to address the problem of retrieving source documents, whose contents are copied partially or obfuscated in a suspicious document. The detection stage, which exploits a two-step paragraph-based comparison, is aimed to address the problems of detecting and locating source-obfuscated passage pairs. The seeds for matching source-obfuscated passage pairs are based on locally-weighted significant terms to capture paraphrased and summarized passages. In addition to this system, an evaluation corpus was created through simulation by human writers, and by algorithmic random generation. Using this corpus, the performance evaluation of the proposed methods was performed in three scenarios. On the first scenario which evaluated source retrieval performance, some methods using phraseword and token features were able to achieve the optimum recall rate 1. On the second scenario which evaluated detection performance, our system was compared to Alvi's algorithm and evaluated in 4 levels of measures: character, passage, document, and cases. The experiment results showed that methods resulted from using token as seeds have higher scores than Alvi's algorithm in all 4 levels of measures both in artificial and simulated plagiarism cases. In case detection, our systems outperform Alvi's algorithm in recognizing copied, shaked, and paraphrased passages. However, Alvi's recognition rate on summarized passage is insignificantly higher than our system. The same tendency of experiment results were demonstrated on the third experiment scenario, only the precision rates of Alvi's algorithm in character and paragraph levels are higher than our system. The higher Plagdet scores produced by some methods in our system than Alvi's scores show that this study has fulfilled its objective in implementing a competitive state-of-the-art algorithm for detecting plagiarism in Indonesian texts. Being run at our test document corpus, Alvi's highest scores of recall, precision, Plagdet, and detection rate on no-plagiarism cases correspond to its scores when it was tested on PAN'14 corpus. Thus, this study has contributed in creating a standard evaluation corpus for assessing PDS for Indonesian documents. Besides, this study contributes in a source retrieval algorithm which introduces phrasewords as document features, and a paragraph-based text alignment algorithm which relies on two different strategies. One of them is to apply local-word weighting used in text summarization field to select seeds for both discriminating paragraph pair candidates and matching process. The proposed detection algorithm results in almost no multiple detection. This contributes to the strength of this algorithm

Towards A Taxonomy of Emerging Topics in Open Government Data: A Bibliometric Mapping Approach

The purpose of this paper is to capture the emerging research topics in Open Government Data (OGD) through a bibliometric mapping approach. Previous OGD research has covered the evolution of the discipline with the application of bibliometric mapping tools. However, none of these studies have extended the bibliometric mapping approach for taxonomy building. Realizing this potential, we used a bibliometric tool to perform keyword analysis as a foundation for taxonomy construction. A set of keyword clusters was constructed, and qualitative analysis software was used for taxonomy creation. Emerging topics were identified in a taxonomy form. This study contributes towards the development of an OGD taxonomy. This study contributes to the procedural realignment of a past study by incorporating taxonomy building elements for taxonomy creation. These contributions are significant because there is insufficient taxonomy research in the OGD discipline. The taxonomy building procedures extended in this study are applicable to other fields