Proceedings of the International Conference on Science and Technology (ICST 2018)

Clustering of Potency of Shrimp In Indonesia With K-Means Algorithm And Validation of Davies-Bouldin Index

Authors
Firman Tempola, Achmad Fuad Assagaf
Corresponding Author
Firman Tempola
Available Online December 2018.
DOI
https://doi.org/10.2991/icst-18.2018.148How to use a DOI?
Keywords
shrimp; clustering K-Means; Davies Bouldin Index
Abstract
Among ASEAN countries, Indonesia is first ranked shrimp producers. Although shrimp from Indonesia is one of the main producers in the ASEAN region, in fact the potential of each province has not been explained in detail, so it needs to be studied further related to shrimp production in every province in Indonesia. This research will do mapping the potential of shrimp per province in Indonesia. The method applied in doing the mapping is by using K-Means Clustering algorithm, with clustering validation used is davies bouldin index. The result showed that clustering position was in the sixth iteration for two clusters, cluster 1 became the best cluster with the value of SSW 0,13507 and the value of DBI 0,96. As for the division of 3 clusters only occur once iteration, the first cluster becomes the best cluster with the value of SSW 0.095 and the value of DBI 0.76. Thus from the distribution of the number of clusters formed then the division of 3 clusters is better than the division of 2 clusters.
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Proceedings
International Conference on Science and Technology (ICST 2018)
Part of series
Atlantis Highlights in Engineering
Publication Date
December 2018
ISBN
978-94-6252-650-1
ISSN
2589-4943
DOI
https://doi.org/10.2991/icst-18.2018.148How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Firman Tempola
AU  - Achmad Fuad Assagaf
PY  - 2018/12
DA  - 2018/12
TI  - Clustering of Potency of Shrimp In Indonesia With K-Means Algorithm And Validation of Davies-Bouldin Index
BT  - International Conference on Science and Technology (ICST 2018)
PB  - Atlantis Press
SP  - 730
EP  - 733
SN  - 2589-4943
UR  - https://doi.org/10.2991/icst-18.2018.148
DO  - https://doi.org/10.2991/icst-18.2018.148
ID  - Tempola2018/12
ER  -