Algoritma K-Means Untuk Analisis Presepsi Masyarakat Labuhanbatu Dalam Promosi Produk Berbasis Digital Pasca COVID-19

Shabrina Rasyid Munthe (Teknik Informatika - Universitas Al Washliyah)
Sudi Suryadi (Teknik Informatika - Universitas Al Washliyah)
Muhammad Irwansyah Hasibuan (Fakultas Ekonomi, Universitas Al Washliyah Labuhanbatu)
Ibnu Rasyid Munthe (Manajemen Informatika - Universitas Labuhanbatu)
Ronal Watrianthos (Teknik Informatika - Universitas Al Washliyah)

U-NET Jurnal Teknik Informatika
Vol. 5 No. 2 (2021): U-NET Jurnal Teknik Informatika | Agustus

The Labuhanbatu community who do business by promoting products utilize digital products with 142 post-covid-19 business actors where the attributes used are the use of the internet, social media, and product promotion. A total of 47 people took advantage, and as many as 95 business actors did not take advantage of product promotion opportunities. The method used for clustering is the K-Means algorithm and the process uses the CRISP-DM model. It is known that the results are processed using the rapidminer tool.