Word Cloud of UKSW Lecturer Research Competence Based on Google Scholar Data
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Word Cloud of UKSW Lecturer Research Competence Based on Google Scholar Data |
| 2. | Creator | Author's name, affiliation, country | Suryasatriya Trihandaru; Universitas Kristen Satya Wacana; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Hanna Arini Parhusip; Universitas Kristen Satya Wacana; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Bambang Susanto; Universitas Kristen Satya Wacana; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Carolina Febe Ronicha Putri; Universitas Kristen Satya Wacana; Indonesia |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | machine learning; word cloud; corpus; research competence |
| 4. | Description | Abstract | There is a need in the Universitas Kristen Satya Wacana (UKSW) to identify the research competence of their faculties at a study program and University level. To accomplish this requirement, we need to automate the analysis of research output and publications quickly. Research articles are scattered in many publisher systems and journals which may be reputable, unreputable, accredited, and unaccredited. We devised a computer code to quickly and efficiently retrieve publication titles recorded in Google Scholar using a machine learning algorithm. The result display is in the form of a word cloud so that dominant and frequent words will be prominent in the visualization. In determining scientific terms to display, we used a modified version of the word cloud Python module and unmodified Term Frequency - Inverse Document Frequency (TF-IDF) library. The algorithm was tested on publication titles of our study program in UKSW and confirmed directly. The system features the ability to produce a word cloud visualization for an individual faculty, for faculties in a study program, or in the University as a whole. We have not differentiated publication sources, whether they are reputable or unreputable, which might affect the accuracy of competence identification. |
| 5. | Publisher | Organizing agency, location | Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia |
| 6. | Contributor | Sponsor(s) | Hibah penelitian internal UKSW tahun 2020/2021 berjudul "Analisa Riset Unggulan UKSW Menggunakan Machine Learning dan Data Google" |
| 7. | Date | (YYYY-MM-DD) | 2021-06-21 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | https://journals.ums.ac.id/index.php/khif/article/view/13123 |
| 10. | Identifier | Digital Object Identifier (DOI) | https://doi.org/10.23917/khif.v7i2.13123 |
| 11. | Source | Title; vol., no. (year) | Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika; Vol. 7 No. 2 October 2021 |
| 12. | Language | English=en | en |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
Copyright (c) 2021 Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika This work is licensed under a Creative Commons Attribution 4.0 International License. |