|Judul||:||A Big Data Architecture to Support Bank Digital Campaign|
Bank marketers still have difficulties to find the best
implementation for credit card promotion using above the line,
particularly based on customers preferences in point of interest
(POI) locations such as mall and shopping center. On the other
hand, customers on those POIs are keen to have recommendation
on what is being offered by the bank. On this paper we propose a
design architecture and implementation of big data platform to
support bank’s credit card’s program campaign that generating
data and extracting topics from Twitter. We built a data pipeline
that consist of a Twitter streamer, a text preprocessor, a topic
extractor using Latent Dirichlet Allocation, and a dashboard that
visualize the recommendation. As a result, we successfully
generate topics that related to specific location in Jakarta during
some time windows, that can be used as a recommendation for
bank marketers to create promotion program for their customers.
We also present the analysis of computing power usages that
indicates the strategy is well implemented on the big data
|Tahun||:||2018||Media Publikasi||:||jurnal internasional|
|Kategori||:||Jurnal||No/Vol/Tahun||:||- / 8 / 2019|
|PTN/S||:||Universitas Pakuan||Program Studi||:||ILMU KOMPUTER|
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