KLASIFIKASI ARTIKEL-ARTIKEL JURNAL PUSTAKALOKA BERDASARKAN SKEMA JITA

This research aims to determine the classification of articles in journal of Pustakaloka, and specifically to identify the largest and smallest subject groups based on JITA Classification System of Library and Information Science. Data for this research consist of 174 articles from 2009-2021 publication. To assign the subject of an article, its title and keywords were analyzed. Abstract and article content were also analyzed if the title and keywords were not able to reflect the subject. The data were coded according to the JITA scheme, sorted and counted to build up subject groups. The three largest subject groups are Users, literacy and reading, followed by Information sources, supports, channels, then by Management and Information technology and library technology. Meanwhile, the three smallest subject groups are Information use and sociology of information, followed by Theoretical and general aspects of libraries and information, Housing technologies, and the last is Publishing and legal issues. This research identified that in general, the articles in Pustakaloka are concentrated on some of intermediate and specific level that cover the aspect of users, directional and management functions, pragmatic and technical issues

An Analysis of Subject Coverage and Worldwide Involvement of E-LIS: the International Repository for Library and Information Science.

E-LIS, E-prints for Library and Information Science, is a subject-oriented repository initiated in January 2003 by a group of European information specialists. E-LIS is an open-access repository run by experts and editors from many different countries and with holdings originating in 110 countries. The first purpose of this study is to provide a description of E-LIS with special attention to the types of documents archived and the geographical distribution of its contributors. The second purpose is to determine the subject coverage, which is done by using several well-known bibliometric techniques. Using co-occurrences of subject terms, a cluster analysis is performed, producing four major clusters; a correspondence analysis of keywords and subject terms produces eight groups of association

Persebaran Subjek Artikel-Artikel Jurnal Tik Ilmeu 2017-2022

Penelitian ini bertujuan untuk mengetahui persebaran subjek dari artikel-artikel jurnal Tik Ilmeu. Data penelitian berupa 86 artikel dalam enam volume selama tahun 2017-2022. Subjek dihasilkan melalui analisis terhadap judul, abstrak dan kata-kata kunci. Subjek dikelompokkan menurut JITA Classification System of Library and Information Science. Selama enam tahun terbit, terdapat subjek yang mendapat perhatian tinggi yaitu Information sources, supports, channels sebanyak 15 kali (17%), disusul Users, literacy and reading 14 kali (16%), diikuti Information technology & library technology 13 kali (15%). Subjek Information treatment for information services 3 kali (4%), subjek Theoretical and general aspects of lib & Info, dan Industry, profession and education, sama-sama 4 kali (5%). Subjek Publishing and legal issues dan subjek Housing technologies hanya 1 (1%) dalam masa yang sama. Kedua subjek sama-sama diabaikan oleh penulis selama 5 tahun. Dari tahun ke tahun subjek yang konsisten terwakili dan mendapat perhatian terbanyak adalah Information sources, supports, channels. Subjek Information technology and library technology, meskipun persentasenya tinggi, tidak terwakili di tahun pertama. Subjek ini mencapai puncak tertinggi di tahun 2019 (36%) kemudian turun, dan di akhir periode hanya 12%

Analysis of Persian Wikipedia Articles in the Field of Library and Information Science

Objective: Wikipedia is a social multilingual encyclopedia that integrates all information about a particular topic on its platform. The present study aims to analyze the thematic content of Persian articles contributed in the field of library and information science (LIS) in Wikipedia and to identify the thematic gaps in this field. Materials and Methods: The data were collected using two different methods: document analysis and observation. In the first and second phases of the study, 591 Persian articles written in the categories of Library and Information Science and other related sub-categories were identified and analyzed. Then, their thematic content and gaps were investigated using a checklist developed based on the JITA Classification System of LIS. The collected data were analyzed using Microsoft Excel. Findings: The results revealed the following thematic content distribution of Persian articles written in the field of Library and Information Science in Wikipedia based on the JITA Classification System: “I. Information treatment for information services” class with 134 articles (22.69% out of 591 articles), “H. Information sources, supports, channels” class with 126 articles (21.32%), “L. Information technology and library technology” class with 84 articles (14.24%), “E. Publishing and legal issues” class with 58 articles (9.82%), “B. Information use and sociology of information” class with 57 articles (9.65%), “G. Industry, profession and education” class with 51 articles (8.64%), “D. Libraries as physical collections” class with 40 articles (6.78%), “A. Theoretical and general aspects of libraries and information” class with 16 articles (2.72%), “J. Technical services in libraries, archives, museum” class with 10 articles (1.7%), “F. Management” class with 9 articles (1.52%), “C. Users, literacy and reading” class with 4 articles (0.68%), and “K. Housing technologies” class with 2 articles (0.34%). Conclusion: Due to the thematic dispersion of Persian Wikipedia articles, Iranian LIS professionals should improve the quantity and quality of Persian articles on Wikipedia, especially on topics with thematic gaps. While reviewing the articles, it was observed that some articles were weak in terms of content and scope. It is suggested that librarians, information specialists, and information professionals help Wikipedia to strengthen and improve its articles, which in turn benefits the millions of users around the world

KLASIFIKASI ARTIKEL-ARTIKEL JURNAL PUSTAKALOKA BERDASARKAN SKEMA JITA

Penelitian ini bertujuan untuk mengetahui klasifikasi artikel-artikel jurnal Pustakaloka, dan secara spesifik mengetahui kelompok subjek terbesar dan kelompok subjek terkecilnya berdasarkan JITA Classification System of Library and Information Science. Data penelitian terdiri atas 174 artikel dari tahun 2009-2021. Untuk menentukan subjek, dilakukan analisis terhadap judul dan kata kunci. Abstrak dan konten artikel ikut dianalisis jika judul dan kata kunci tidak mampu merefleksikan subjek artikel. Data diberi kode menurut skema JITA, diurutkan dan dihitung hingga menghasilkan kelompok-kelompok subjek. Tiga kelompok terbesar adalah Users, literacy and reading, diikuti Information sources, supports, channels, kemudian Management dan Information technology and library technology. Tiga kelompok terkecil adalah Information use and sociology of information, diikuti Theoretical and general aspects of libraries and information, Housing technologies, dan yang terakhir adalah Publishing and legal issues. Penelitian ini mengidentifikasi bahwa secara garis besar, artikel-artikel di dalam jurnal Pustakaloka terkonsentrasi pada sebagian level intermediate dan specific yaitu aspek pengguna, fungsi pengarahan dan manajemen, isu pragmatis dan teknis

Automatic Classification of the Berliner Handreichungen zur Bibliotheks- und Informationswissenschaft

Classification systems are one of the most established methods of knowledge organization with many advantages and yet, the collection of the Berliner Handreichungen zur Bibliotheks- und Informationswissenschaft (BHR) is missing a classification scheme. Therefore, an objective of the thesis at hand is to achieve a classification system for the collection and to potentially use Machine Learning (ML) methods for the automatic allocation of the BHR documents to the obtained classification system. The research questions that will be answered, are whether the JITA Classification System of Library and Information Science (JITA) is an appropriate classification system for the BHR and if automatic classification with ML can be applied to allocate the documents of the collection to a classification system without a using BHR data in the training dataset. To evaluate JITA an evaluation checklist was created based on recommendations of the cited literature. Using this checklist, it was concluded that JITA is not suitable as classification system of the BHR. Thus, using the same checklist as a reference, a new classification system was created. No expert evaluations nor user studies were conducted, which is a clear limitation of the thesis at hand. After a suitable classification scheme for the BHR was created, titles and abstracts of documents from different sources were scraped to use them as the training set for the ML experiments. Naïve Bayes, SVM, and Logistic Regression classifiers as well as Deep Learning classifiers, using the FLAIR framework, were tested. None of the obtained models yielded satisfying results, which is why no further experiments classifying the BHR documents were conducted. It was concluded that an automatic classification of the BHR documents is not possible without a BHR training set. Several limitations, especially during the creation of the training set, could have led to the unsatisfactory results which will be discussed in this thesis, which offers a basis for future studies that aim to evaluate classification schemes or for further Text Classification experiments