Melola Discovery

← Melola Discovery

Jurnal

Improving The Effectiveness of Research and Community Service Management System

Jurnal Penelitian Pendidikan · Vol. 41 No. 1 (2024) · hlm. 19–26

DOI
10.15294/5nzzpp44
ISSN
2580-4154, 2503-1260
Terbit
2024-08-12
Penerbit
Universitas Negeri Semarang
Bahasa
eng

Abstrak

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.

Kata kunci

Jaringan kolaborasi para penulis

40 penulis · 88 tautan kepenulisan bersama · 2 lintas organisasi · menampilkan 40 yang paling banyak terhubung

Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.

  • State University of Semarang
  • Universitas Halu Oleo
  • Diponegoro University
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Deby Luriawati NaryatmojoAfiliasi tidak diketahui2
Andri Sumihar SimbolonAfiliasi tidak diketahui2
Riza ArifudinState University of Semarang2
M Fikri AmrullahAfiliasi tidak diketahui2
Abdul KadirUniversitas Halu Oleo1
LM. Fid AksaraUniversitas Halu Oleo1
Nur Fajriah MuchlisUniversitas Halu Oleo1
Edward NgiiUniversitas Halu Oleo1
Taripar Matius AlexanderAfiliasi tidak diketahui1
Widowati WidowatiAfiliasi tidak diketahui1
Widya Hary CahyatiAfiliasi tidak diketahui1
Margareta RahayuningsihAfiliasi tidak diketahui1
Wandah WibawantoAfiliasi tidak diketahui1
Nugroho Edi KartijonoState University of Semarang1
Dony Hidayat Al-JananAfiliasi tidak diketahui1
Saptono PutroAfiliasi tidak diketahui1
Kusumantoro KusumantoroAfiliasi tidak diketahui1
Khoirul AnwarAfiliasi tidak diketahui1
Nanang IndardiAfiliasi tidak diketahui1
Vacktian Diva GumalaAfiliasi tidak diketahui1
Nana Kariada Tri MartutiState University of Semarang1
Inaya Sari MelatiState University of Semarang1
Rossi PrabowoDiponegoro University1
Florentina Yuni AriniState University of Semarang1
Athoillah AthoillahAfiliasi tidak diketahui1
Endang SugihartiState University of Semarang1
Kholiq BudimanAfiliasi tidak diketahui1
zaenal abidinAfiliasi tidak diketahui1
Hariyanto HariyantoAfiliasi tidak diketahui1
Ananto AjiAfiliasi tidak diketahui1
Bella Zulfia Aisyatul WahidahAfiliasi tidak diketahui1
Apik Budi SantosoAfiliasi tidak diketahui1
Anggi SafingahAfiliasi tidak diketahui1
Moch. ArifienAfiliasi tidak diketahui1
sri nata saputriAfiliasi tidak diketahui1
Yusuf KholikAfiliasi tidak diketahui1
Wuri Daningtias RakhmatinAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/journals/JPP/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 5 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Improving The Effectiveness of Research and Community Service Management System</dc:title>
	<dc:creator xml:lang="en">Sholeh, Muh. </dc:creator>
	<dc:creator xml:lang="en">Putra, Anggyi Trisnawan </dc:creator>
	<dc:creator xml:lang="en">Husodo, Martanto Setyo </dc:creator>
	<dc:subject xml:lang="en">artificial intelligence, effectiveness, management system</dc:subject>
	<dc:description xml:lang="en">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. </dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2024-08-12</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/journals/JPP/article/view/11667</dc:identifier>
	<dc:identifier>10.15294/5nzzpp44</dc:identifier>
	<dc:source xml:lang="en">Jurnal Penelitian Pendidikan; Vol. 41 No. 1 (2024): April 2024; 19-26</dc:source>
	<dc:source>2580-4154</dc:source>
	<dc:source>2503-1260</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/journals/JPP/article/view/11667/1186</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2024 Jurnal Penelitian Pendidikan</dc:rights>
</oai_dc:dc>