CLUSTERING HASIL PANEN UBI KAYU MENGGUNAKAN ALGORITMA K-MEANS

  • Ratih Yulia Hayuningtyas Universitas Nusa Mandiri
  • Ida Darwati Universitas Bina Sarana Informatika

Abstract

Cassava is one commodity that has the potential to grow the country's economy. Cassava is a primary food requirement besides rice and corn. This research discusses the grouping of cassava products in the Trenggalek area, the data collected will later be formed into a group or cluster. There are 3 clusters created, namely high cluster, medium cluster and low cluster, to determine which data will enter the 3 clusters. Clustering is an analysis method of data mining. This research uses an algorithm, namely K-Means, to process cassava production results into a cluster. The results of the research produced a high cluster of 3 items, a medium cluster of 1 item and a low cluster of 10 items. Judging from these results, there are still many areas in Trenggalek that produce low quantities of cassava. This research can provide strategies or information to increase cassava production in the future.

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Published
2024-06-30
How to Cite
HAYUNINGTYAS, Ratih Yulia; DARWATI, Ida. CLUSTERING HASIL PANEN UBI KAYU MENGGUNAKAN ALGORITMA K-MEANS. Jurnal Tekinkom (Teknik Informasi dan Komputer), [S.l.], v. 7, n. 1, p. 25-32, june 2024. ISSN 2621-3079. Available at: <https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/1327>. Date accessed: 21 july 2024. doi: https://doi.org/10.37600/tekinkom.v7i1.1327.
Section
Articles