IEEE Lecture for UIN Syarif Hidayatullah, Jakarta 2014.

1. Kuncoro Wastuwibowo
Chair, IEEE Indonesia Section
Jakarta, 15 October 2014

2. IEEE is the world's largest professional association dedicated to advancing
technological innovation and excellence for the benefit of humanity. IEEE
and its members inspire a global community through IEEE's highly cited
publications, conferences, technology standards, and professional and
educational activities.

3. IEEE has
 more than 425,000 members in
more than 160 countries;
 more than 116,000 Student
members;
 333 Sections in 10 geographic
regions worldwide;
 2,195 Chapters that unite local
members with similar technical
interests;
 2,354 student branches at
colleges and universities;
 800 student branch chapters of
IEEE technical societies;
IEEE
 has 38 Societies and 7 technical Councils
representing the wide range of IEEE technical
interests;
 has more than 3 million documents in the IEEE
Xplore Digital Library, with more than 8 million
downloads each month;
 has more than 1,400 standards and projects under
development;
 publishes more than 148 transactions, journals, and
magazines;
 sponsors more than 1,300 conferences in 80
countries while:
 publishing more than 1,200 conference proceedings
via IEEE Xplore.

4. Board ofDirectors
MEMBERS
Educational
Activities Board
Professional
Activities Board
Publications
Activities Board
Regional
Activities Board
Standards
Activities Board
Technical
Activities Board
MEMBERS
Board of Directors Assembly
PSPB IEEE-USA
Standards Assoc.EAB
MGA TAB Executive Comm.
Regions & Sections Societies & Councils Staff & Society Exec.
Directors
Chapters

6. Internet
2.0
Internet
3.0
Total Experience
Services
Context-aware
Applications
Internet of Things
Big Data &
Analytics
Smart Applications
Wisdom of
Crowds
Mash-up
Applications
User-Generated
Content

8. “Business
Intelligence
”
Data
Discovery
Things We Know
Things We Don’t Know
Questions We Ask
Questions We Don’t Ask

10. Science &
Technology• Search for Extra-
Terrestrial Intelligence
(SETI)
• Genome projects
• CERN’s Large Hadron
Collider
• The Square Kilometer
Telescope Array
• Social Genome
Business &
Community• Consolidation of
government data
holdings
• Consumer profile
databases
• Customer relationship
management
• Social Media
• Sensor data

13. Sensing Data
Cyberspace
Physical Space
Actionable
Information
Ubiquitous
Internet

15. Device
Provider
3rd Party
Context
Enabler
Context
Provider
Service
Platform
Provider
Content
Provider
User
Network
Provider
Service
Provider
Platform
Provider
Context Platform
Context Data
Context Data
Context Data
Context
Context-Aware Services

16. Google Search
•User’s interest
•User’s behaviour
Google Mail
•User’s profile
•User’s behaviour & schedule
•User’s relation
•(Even for Mac & iOS users)
Google+
•User’s relation
•User’s behaviour
Google Maps
•User’s location
•User’s interest
Youtube
•User’s interest
•User’s network capacity
Chrome
•User’s behaviour
•User’s interest
•(Even for Mac users)
Android
•User’s device
•User’s location
•User’s behaviour
•User’s application usage
Google Docs
•User’s business
•User’s schedule
Google Translate
•User’s business
•User’s interest
Google Playstore
•Guess it!
Google Scholar
•Guess it!
Google Drive
•Guess it!

17. Google
• Google Search
• Google Now
• Google Glass
Apple
• Siri
• Apple Watch
• iPhoto (autometically
managed with time,
location, event)
• Health

24. Target
customers by
capturing useful
information
about them
Identify more
effective
product
promotions and
create offers
targeted to
specific
customers.
Predict the risk
of each
customer going
to other
companies and
then identify
actions likely to
keep them
loyal.
Improve
efficiency by
reducing
unused
capacity or
unnecessary
duplication
WHY?
Organizations leveraging analytics will have a greater competitive
advantage. Those that don’t will lag behind their peers.

25. Big data analytics is valuable to many companies but has been too
complex and expensive for smaller businesses. This is beginning to
change.

26. Suvola
• Integrated systems
using hardware
and software from
selected vendors
to allow smaller
organizations buy
simpler, more
affordable all-in-
one systems for
which the seller
provides
maintenance and
support.
Big Vendors
• IBM
• Oracle
• SAP
• SAS
Start-ups
• QlickTech
• Tableau Software
• Tidemark

27. Uptime
Sotware
Continuui
ty
Right
Scale
Amazo
n
Cloudy
n
Cloud
Vertical
Newvem
BigML
Insights
One
Splunk
Storm
Rack
space
Cloudabilit
y

29. The Internet will enhance global connectivity, fostering
more planetary relationships and less ignorance.
The IoT, artificial intelligence, and big data will provide more
awareness of the world and our own behavior.
Augmented reality and wearable devices will monitor and
give quick feedback on daily life (for example, to enhance
personal health).
Political awareness and action will be facilitated. More
peaceful change and public uprisings will emerge.
Internet will diminish the meaning of borders, and new
“nations” of those with shared interests may emerge.

30.  Dangerous divides between haves and have-nots may expand, resulting
in resentment and possible violence.
 Abuses and abusers will “evolve and scale.” Human nature isn’t changing;
laziness, bullying, stalking, stupidity, pornography, dirty tricks, and crime
will continue, and those who practice them have new capacity to make life
miserable for others.
 Pressured by these changes, governments and corporations will try to
assert power—and at times succeed—as they invoke security and cultural
norms.
 People will continue—sometimes grudgingly—to make tradeoffs, favoring
convenience and perceived immediate gains over privacy. Privacy will
become something only the upscale enjoy.
 Humans and their current organizations may not respond quickly enough
to challenges presented by complex networks.
 Most people haven’t yet noticed the profound changes today’s
communications networks are already bringing about; these networks will
be even more disruptive in the future.

31. Encryption isn’t a perfect solution for securing big data, but it
could be a valuable component in a comprehensive privacy
solution.
Third parties would create various privacy profiles for
consumers who would then select a profile such that data
holders would be required to differentiate the way they use
data based on each consumer’s selection.
Anonymisation and de-identification have limited relevance
because data points linked to one another tend to take on
other identifiable attributes.
Deletion and non-retention policies aren’t effective means of
protecting individual privacy.

32. The focus should be on the actual uses of big data and not
so much on its collection and analysis.
To avoid obsolescence, policies and regulations should
be stated in terms of intended outcomes and not embed
particular technological solutions.
The Government should strengthen its research in privacy-
related technologies.
There should be more education and training opportunities
concerning privacy protection.
The Government should take the lead by adopting policies
that stimulate the use of practical privacy-protecting
technologies that exist today.

33. Kuncoro Wastuwibowo
Chair
IEEE Indonesia Section
info@IEEE.web.id
http://IEEE.web.id
@IEEEIndonesia

34. IEEE Indonesia Section
info@IEEE.web.id
http://IEEE.web.id
@IEEEIndonesia

35.  Brian M. Gaff, Heather Egan Sussman, Jennifer Geetter, Privacy and Big
Data, IEEE Computer, June 2014
 George F. Hurlburt, Jeffrey Voas, Big Data, Networked Worlds, IEEE
Computer, April 2014
 Jason Kolb & Jeremy Kolb, The Big Data Revolution, Applied Data Labs
Inc 2013.
 Neal Leavitt, Bringing Big Analytics to the Masses, IEEE Computer,
January 2013
 Niklas Elmqvist & Pourang Irani, Ubiquitous Analytics: Interacting with
Big Data Anywhere, Anytime, IEEE Computer, April 2013
 Pew Research Center, Digital Life in 2025, March 2014
 President’s Council of Advisors on Science and Technology, Report to
the President: Big Data and Privacy – A Technological Perspective,
May 2014.
 Xiaomeng Yi, Fangming Liu, Jiangchuan Liu, and Hai Jin, Building a
Network Highway for Big Data: Architecture and Challenges, IEEE
Network, July/August 2014
 Yin Zhang, Min Chen, Shiwen Mao, Long Hu, and Victor C. M. Leung,
CAP: Community Activity Prediction Based on Big Data Analysis,