Open AccessComparison of PROMETHEE –TOPSIS method based on SAW and AHP weighting for school e-learning readiness evaluation
Author(s) -
Sri Andayani,
B. Sumarno Hm,
NH Waryanto
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1581/1/012012
Subject(s) - analytic hierarchy process , weighting , strengths and weaknesses , ranking (information retrieval) , topsis , computer science , human resources , process (computing) , knowledge management , management science , psychology , operations research , artificial intelligence , mathematics , management , engineering , social psychology , medicine , economics , radiology , operating system
As the demand for using e-learning rising for all subjects at schools in digital era, the successful implementation of e-learning is important to be well prepared. The successful is influenced by many factors, including the provision of technology infrastructure, Human Resources, organizational culture and leadership factors. For this reason it is necessary to evaluate the readiness of schools in implementing e-learning, which is known as e-learning readiness (ELR). Evaluation of school ELR is carried out to analyse the strengths, weaknesses and dominant factors in implementing e-learning in schools, so that it can be a reference in policy making by related parties. ELR evaluation is carried out using the PROMETHEE and TOPSIS methods based on the weighting of Simple Additive Weighting (SAW) and Analytical Hierarchy Process (AHP). The data used is the readiness for e-learning implementation on the specified criteria. There are eight criteria to measure e-learning readiness (ELR) of schools, namely Psychological readiness, Sociological readiness, Environmental readiness, Human resource readiness, Financial readiness, Technological skill (aptitude) readiness, Equipment readiness, Content readiness. The evaluation model using the PROMETHEE and TOPSIS methods will provide the results of a school’s e-learning readiness ranking, based on the weighting of criteria determined using SAW and AHP. In addition, these results are expected to reveal the weaknesses that need improvement, as well as the strengths that support the implementation of e-learning.