You may see my previous post on this link: “Menimba ilmu di Tech in Asia (TIA) PDC 2017“. I didn’t actively contribute at that time. I just became an audience. Became someone who just listened to what speakers trying to provide.
But the day came, one year after, on October 24, 2018. I was trusted to become one of the speakers. I gave big Thanks to my leader: Mia Melinda, who trusted me to become a TIA speaker. The speaker means someone who give values to others. Someone who have to be responsible to not wasting 30 mins time of the super-busy audience. The audience who had spent time and money more than 1 mio rupiahs for just entering this 2 days-event. Continue reading “Sharing Mobility Data Insights at Tech In Asia Conference 2018 Jakarta”
I attended Big Data Week Jakarta event on March 23, 3017 as a participant, came along with Hamid, Amir, and Ramdisa (Stream Intelligence‘s buddies). One of the speaker is Komang Aryasa from Telkom Indonesia. I couldn’t agree more that his presentation content is very good, because he shared about big data use cases that they have done by big analytics team that he is now lead. Something that we cannot get from a text book!
Well, what are they?
Customer Problem Reporting (especially about telco network). Imagine that all of the telco elements are human. If a human is sick, he will pop up the symptoms. Same as the telco elements, they will pop up the alarms. In this use case, his team provides visualizations and failure prediction of those telco elements. So the maintenance team can respond to the problem quickly before the telco elements are ‘dead’ – (read: malfunction).
Decreasing Churn Rate (by regions). He said that his team have built 62 churn model. The models were split by region. Why? Surprisingly, North Jakarta customers are more price sensitive than South Jakarta. Meaning, if the price is increased, they are more likely to switch to another operator or cut the subscription. Conversely, South Jakarta customers are more problem sensitive than price sensitive, meaning saying if there are outage for several hours, they are less likely stay on the subscription. Shortly said that this is the way of Telkom Indonesia understand customers by location. Interesting!
Effective Collection Caring. Have you ever bugged by a customer service call while you are on a meeting? Very annoying right? He said that his team were able to built predictive models, what is the best time for a customer care service calling a certain customer. Have you thought how to do that? Yes! One of them is by looking at their behavior of browsing. For example if the browsing behavior at 8pm changed to news channel, meaning that the parents (e.g. Dad) just arrived home and he accessed to the news. Well, it should be the best time for the customer service contact him. So, he will be able to continue the conversation, meaning that the customer information collection is effective.
Waste Management and Crime Reporting. He mentioned that this use case is a partnership with Bandung Government. The IoT devices (GPS trackers) are installed on the waste truck, and Bandung Smart City controller can track in real time. While on crime reporting, it’s like a panic button system that can be used by Bandung citizen to report problems like heavy traffic, road damage, etc.
Value Chain Transparency with Digital Tools & Empower Farmers with microloans, Banks, Bulog, BUMDs, DukCapil, etc.
Tourism dashboards, built for Indonesian governments to track tourism spots visited by tourists in neighboring countries like Malaysia, Thailand, and Singapore, by utilizing real-time dashboards. The objective of this tracking is to attract 20 million foreign tourists come to Indonesia in one year.
This is a short brief of Komang Ardyasa. He is Deputy Research of Big Data at PT Telkom Indonesia. His organization serve internal (Telkom) and external clients. His partner, Cloudera, is in charged in Telkom’s big data infrastructure and architecture, so before his speech, Cloudera Country Manager, Fred Groen shared a short brief about his company.