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Hermawan, Sari
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Library & Information Science

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Library Book Loan Data Clustering Using K-Means Algorithm to Improve Book Loans Pratama, Denni; Hermawan, Sari; Juliane, Christina
Edulib Vol 13, No 2 (2023)
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/edulib.v13i1.50003

Abstract

Entering the post-pandemic new standard era in 2022 as of June, the number of borrowed books at the Indonesian University of Education Library could be more optimal compared to the year before the pandemic (2018 - 2019). Lending in 2022 can still be increased by arranging the most borrowed books in one group. This research aims to classify books more optimally, which will be applied to book arrangement. Optimal book arrangement allows library visitors to find books more efficiently based on the books that are most often borrowed so that they are interested in borrowing other books in a group. Data mining is a term used to describe knowledge in a database from a repository by finding patterns and trends in data through examination with statistical and mathematical techniques. Clustering is a data mining method that can be used to determine the data clusters. One of the algorithms that can be used is K-Means. The clustering pattern obtained shows 2 (two) grouping clusters. Book titles in cluster 0 contain book titles related to research methodology, statistics, measurement scales, assessment, and learning evaluation. While cluster 1 tends to contain psychology, counseling, religion, philosophy, management, economics, and history. This data can be used by librarians in prioritizing purchasing a collection of books in the subsequent procurement.
Reengineering Analysis of Business Process System "Read Full Text On Screen" Institutional Repository Hermawan, Sari
Edulib Vol 12, No 2 (2022)
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/edulib.v12i2.51594

Abstract

Scientific works produced by tertiary institutions are encouraged to be accessed online and openly through institutional repositories. This is motivated by various regulations from the government to prevent plagiarism and fulfil the public's information needs. The Indonesian University of Education Institutional Repository (UPI Repository), managed by the UPI Library during the COVID-19 Pandemic, experienced problems in providing access to limited collection data. Therefore this study aims to conduct a business process engineering analysis on the UPI Repository limited collection service so that it can be effectively and efficiently accessed by UPI academics so that they can contribute to the learning process. The business process reengineering analysis method refers to the System Development Life Cycle (SDLC) approach. The results of the research are that there are additional features in the UPI Repository, namely Full-text reading services, SSO login features, and Full-Text data display on-screen access features. Changes in the design of the business process have resulted in a reduction in the process, namely VPN access, before the UPI Repository. There has been an increase in users of the Read Full Text on Screen service after the new design changes were implemented.
Co-Authors Christina Juliane, Christina Pratama, Denni