How 802.1x Enhances Knowledge Extraction from Large Scale Campus WiFi Deployment

Mukhammad Andri Setiawan

2019

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 marketing 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.

Paper Citation

in Harvard Style

Setiawan M. (2019). How 802.1x Enhances Knowledge Extraction from Large Scale Campus WiFi Deployment. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 3: KMIS; ISBN 978-989-758-382-7, SciTePress, pages 391-397. DOI: 10.5220/0008366403910397

in Bibtex Style

@conference{kmis19,
author={Mukhammad Andri Setiawan},
title={How 802.1x Enhances Knowledge Extraction from Large Scale Campus WiFi Deployment},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 3: KMIS},
year={2019},
pages={391-397},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008366403910397},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 3: KMIS
TI - How 802.1x Enhances Knowledge Extraction from Large Scale Campus WiFi Deployment
SN - 978-989-758-382-7
AU - Setiawan M.
PY - 2019
SP - 391
EP - 397
DO - 10.5220/0008366403910397
PB - SciTePress