Application of K-Means Clustering to Monitoring the level of Fertilizer Usage in Rice Fields in Ngawi Regency

Authors

  • Iwan Ady Prabowo STMIK Sinar Nusantara, Indonesia
  • Hendro Wijayanto STMIK Sinar Nusantara
  • Sujud Aji Wantoro STMIK Sinar Nusantara

DOI:

https://doi.org/10.30646/tikomsin.v10i1.600

Keywords:

Applications, endemic, clustering, k-means clustering, farmers

Abstract

Fertilizer is a substance given to plants that could be food for plants. Fertilizer  itself divided into two types, that  is  inorganic  fertilizers  and  organic  fertilizer.  Fertilizer  is  very important  to  the  needs  of farmers,  especially  farmers.  Therefore  fertilizer  needs should be able  to in monitoring  in  order  not to occur lack. The purpose of this study is a grouping of the use of fertilizer in every town in the districts of Ngawi with k-Means algorithm. The formulation of the problem to overcome is how to apply the method of k-means  algorithm  to  categorize  fertilizer  needs  in  every  town  in  the  Ngawi.  K-means  is  clustering algorithm where one object can be in group based on data similarities. Clustering results K-means Clustering is seen in the first group high (Cluster 1) contains 6, In the second group medium (Cluster 2) contains 2 sub-districts, while in the third group low (cluster 3rd) contains 11 sub-districts.

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Published

2022-05-19

Issue

Vol. 10 No. 1 (2022): Jurnal TiKomSiN, Vol. 10, No. 1, April 2022

Section

Articles

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