Author:
Mukhammad Andri Setiawan
Affiliation:
Department of Informatics, Universitas Islam Indonesia, Yogyakarta and Indonesia
Keyword(s):
WiFi Knowledge Extraction, 802.1x, Campus WiFi.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Business Intelligence
;
Intelligent Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
In recent years, the world has witnessed how internet connectivity is exponentially growing in cities around the world. Universitas Islam Indonesia (UII) as one of biggest private universities in Indonesia is also seeing the similar trend like the rest of the world. With more than 700 high density access points and roughly 30,000 users, most of internet connectivity in campus is provided from WiFi access. After 802.1x WiFi authentication-method deployment, UII saw an opportunity to utilise WiFi metadata as a source of business intelligence. Previously, many business processes or managerial decisions in the university were decided by some hidden assumptions and approximations. These assumptions and approximations sometimes created sub-optimal managerial decisions. To improve the strategic decision, we proposed an evidence-based management based on WiFi data. We utilise this data to extract spatial knowledge, movement behaviour, seamless attendance record, and traffic analysis for mark
eting purpose. The results show promising result where many of university decision is helped by the result given from the knowledge extraction system. Managements can act faster as information is elicited from tacit knowledge within WiFi metada in real time and more accurate.
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