Implementasi Metode K-Means Clustering Dalam Pengelompokan Bibit Tanaman Kopi Arabika

Benny Ginting, Fristi Riandari

Abstract


The emergence of various information on good coffee seeds to be planted has prompted the Agriculture and Plantation Service to group the seeds to be recommended in coffee planting centers in the working area of Sarimunthe Village, Kec. Munte Karo District. Data mining is used to extract valuable information from a dataset and then present it in a format that is easily understood by humans with the aim of making a decision. In this study, data processing for Arabica Coffee seedlings consisted of 30 items, in the Karo Regency Agriculture sector, in preparing the seeds to be distributed to the public, the assessment was divided into 3 phases, namely coffee seeds that did not produce (Phase 0-1 Year), immature (Phase 1-2 years) and produce (Phase 2 years and above). The final result of the grouping of Arabica coffee seedlings is that there are 10 recommended items suitable for planting

Keywords


Coffee Seeds; Clustering; Data Mining; Grouping; K-Means.



DOI: https://doi.org/10.35970/jinita.v2i02.394

Article metrics

Abstract view : 0 times
PDF (Bahasa Indonesia) - 0 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Indexed by:

             

 

 

Managed by.

Department of Informatics Engineering
Politeknik Negeri Cilacap
Jln. Dr.Soetomo No.01 Sidakaya, Cilacap, Indonesia
Telp: (0282) 533329
Email: jinita.ejournal@pnc.ac.id

 

 

Flag Counter  

 

View My Stats

 

 

 Creative Commons License
JINITA is licensed under a Creative Commons Attribution 4.0 International License.