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All Journal International Journal Of Computer, Network Security and Information System (IJCONSIST)
firdaus, aldan
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Computer Science & IT

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CLUSTER ANALYSIS OF FACEBOOK ADS USER FOR DIGITAL MARKETING USING K-MEANS ALGORITHM firdaus, aldan; Fahreza, Rafli; Arfiansyah, Rhifky; Satria, Dhian
IJCONSIST JOURNALS Vol 4 No 1 (2022): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v4i1.72

Abstract

Facebook provides a digital advertising feature called Facebook Ads. Facebook Ads was developed in 2013 and started operating in 2014, but the advertising system at that time was only limited to advertisers. Facebook at that time had not opened up to mobile application developers or website publishers. Until finally Facebook Ads can be used or accessed by anyone. Facebook Ads are very popular with business people, complete features and clear information make it easier for business people to market their products. From the Facebook Ads process, Facebook user data can be retrieved starting from the number of ads that appear, the ads clicked, age range, and gender, to the amount of money spent on these advertising products/services. In this study, Facebook Ads data clustering was carried out to be analyzed. The final visualization results describe the level of clustering according to the attributes used in the study.
Co-Authors Arfiansyah, Rhifky Fahreza, Rafli Satria, Dhian