Research Article
A Decision Support System for Appointment of Teaching Staff Islamic Boarding School Using a Weighted Product Algorithm
@INPROCEEDINGS{10.4108/eai.11-7-2019.2298062, author={Nur Lukman and Deden Suparman and Jati Gunawan and Wildan Budiawan Zulfikar and Rio Guntur Utomo}, title={A Decision Support System for Appointment of Teaching Staff Islamic Boarding School Using a Weighted Product Algorithm}, proceedings={Proceedings of the 1st International Conference on Islam, Science and Technology, ICONISTECH 2019, 11-12 July 2019, Bandung, Indonesia.}, publisher={EAI}, proceedings_a={ICONISTECH}, year={2021}, month={1}, keywords={decision support system weighted product algorithm islamic boarding school}, doi={10.4108/eai.11-7-2019.2298062} }- Nur Lukman
Deden Suparman
Jati Gunawan
Wildan Budiawan Zulfikar
Rio Guntur Utomo
Year: 2021
A Decision Support System for Appointment of Teaching Staff Islamic Boarding School Using a Weighted Product Algorithm
ICONISTECH
EAI
DOI: 10.4108/eai.11-7-2019.2298062
Abstract
Human resources are one of the important things at Al-Basyaryah Islamic Boarding School in order the school meets the national standards of Islamic boarding schools. However, the appointment of teaching staff in Al-Basyaryah Islamic boarding schools is still poorly managed. It is necessary to have a good process of teaching appointment for the school to be categorized as a good Islamic boarding school. Using information technology, the appointment of teaching staff in Islamic boarding schools can be facilitated by a decision support system that acts as a recommendation (proposal) to support the management decisions in the boarding school in planning the appointment of teaching staff. The purpose of this research is to facilitate the appointment of teaching staff in Islamic boarding schools as an agreement for the management of Islamic boarding schools to deal with complaints about the appointment of teaching staff. The decision support system for the appointment of teaching staff in Islamic boarding schools was developed by using a weighted product algorithm. This approach recommended teaching staff to be more effective than 30 teaching staff.
