Ni'am, Muhammad Izzun
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

The Implementation of Semantic Annotation Recognizing Technique in the Scraper Engine on the E-Publishing Website of the National Research and Innovation Agency (BRIN) Indonesia Ni'am, Muhammad Izzun; Frimansyah, Muhammad Haris; Alfarhisi, Zikrie Pramudia
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 2 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i2.23755

Abstract

The increasing need for swift information dissemination in line with modern technological advancements has emphasized the importance and significant impact of data analysis and processing as relevant academic disciplines. These processes encompass data acquisition from various sources, either through direct collection or extraction methods. Among the most crucial and widely utilized techniques for extracting data from the internet is web scraping, particularly when gathering data for research maintenance during the consolidation of multiple institutions into BRIN (National Research and Innovation Agency). Challenges emerge in effectively integrating existing research into a unified system without proper upkeep, as neglecting maintenance can lead to system degradation and hinder access to stored research. Successful maintenance necessitates centralized repositories for researchers' work data. The implementation of semantic annotation recognizing techniques within the web scraping feature of the E-Publishing website holds the potential to expedite this process. The use of web scraping promises to significantly simplify research data collection, while semantic annotation recognizing techniques are poised to streamline implementation, particularly due to the XML data foundation within the Open Archives Initiative (OAI) system. In the context of institution merging and research sustainability, technologies like web scraping and semantic annotation recognizing play pivotal roles in addressing these challenges.