Improving The Effectiveness of Research and Community Service Management System

In recent years, technological developments and paradigm shifts in the world of education and research demand a transformation in the management system of research and community service. The Institute for Research and Community Service (LPPM) of Universitas Negeri Semarang (UNNES) in its role of realising the responsibility of the Tri Dharma of Higher Education, has made a breakthrough in the field of research and community service through an application called SIPP (Research and Community Service Management Information System) which can be accessed on the website. However, there are still five obstacles that need to be improved. This research intends to identify concrete problems faced by Universitas Negeri Semarang in this regard, and design solutions that can increase the effectiveness of the research and community service management system. The results showed that the development of an Artificial Intelligence (AI)-based Recommendation System has become one of the most effective strategies in enhancing user experience in improving the effectiveness of the research and community service management system at Semarang State University. By utilising AI technology, the SIPP application can optimise the data management process, identify research trends, and facilitate collaboration between researchers.

Authors

Institutions

Publication Details

Journal
Jurnal Penelitian Pendidikan/Jurnal penelitian pendidikan
Published
2024-08-12
DOI
https://doi.org/10.15294/5nzzpp44
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving The Effectiveness of Research and Community Service Management System

Muh Ibnu Sholeh, Anggyi Trisnawan Putra, Martanto Setyo Husodo
Jurnal Penelitian Pendidikan/Jurnal penelitian pendidikan
Diverse Approaches in Healthcare and Education Studies
article

Improving The Effectiveness of Research and Community Service Management System

Muh Ibnu Sholeh, Anggyi Trisnawan Putra, Martanto Setyo Husodo
article en

Abstract

In recent years, technological developments and paradigm shifts in the world of education and research demand a transformation in the management system of research and community service. The Institute for Research and Community Service (LPPM) of Universitas Negeri Semarang (UNNES) in its role of realising the responsibility of the Tri Dharma of Higher Education, has made a breakthrough in the field of research and community service through an application called SIPP (Research and Community Service Management Information System) which can be accessed on the website. However, there are still five obstacles that need to be improved. This research intends to identify concrete problems faced by Universitas Negeri Semarang in this regard, and design solutions that can increase the effectiveness of the research and community service management system. The results showed that the development of an Artificial Intelligence (AI)-based Recommendation System has become one of the most effective strategies in enhancing user experience in improving the effectiveness of the research and community service management system at Semarang State University. By utilising AI technology, the SIPP application can optimise the data management process, identify research trends, and facilitate collaboration between researchers.

Jurnal Penelitian Pendidikan/Jurnal penelitian pendidikanVol. 41(1)
State University of Semarang (ID)
Openalex Percentile: Top 59%
Diverse Approaches in Healthcare and Education Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.