Open AccessSistem Pendukung Keputusan Pemilihan Dosen Terbaik Dengan Metode Simple Additive Weighting (SAW) Berbasis Web
Author(s) -
Herri Setiawan,
Husnawati Husnawati,
Tasmi Tasmi
Publication year - 2021
Publication title -
journal of information systems and informatics
Language(s) - English
Resource type - Journals
eISSN - 2656-4882
pISSN - 2656-5935
DOI - 10.51519/journalisi.v3i4.215
Subject(s) - weighting , attendance , flexibility (engineering) , quality (philosophy) , decision support system , service (business) , work (physics) , process (computing) , psychology , computer science , medical education , knowledge management , engineering , artificial intelligence , mathematics , marketing , business , medicine , statistics , economic growth , operating system , mechanical engineering , philosophy , epistemology , economics , radiology
Lecturers are academic staff in charge of planning and implementing the learning process, assessing learning outcomes, conducting guidance and training, as well as conducting research and community service. Lecturers are entitled to promotions and awards according to their academic performance. The selection of the best lecturers at STIKES Al Su'Aibah Palembang was carried out using several factors. The assessment is based on the performance assessment of each lecturer, namely knowledge of work, creativity, planning, quality of work, cooperation, attendance and attitudes towards other lecturers/employees. This study aims to build a decision support system that has the ability to analyze the selection of the best lecturers using the Simple Additive Weighting (SAW) method, where each criterion in this case the assessment factors and alternatives in this case the lecturers are compared with one another. so as to provide output values that produce a system that provides an assessment of each lecturer. This decision support system helps evaluate each lecturer, changes the criteria, and changes the weight value. This is useful to facilitate decision makers related to the problem of selecting the best lecturers, so that the lecturers who are most worthy of being given rewards or awards will be obtained.