Data Mining Application for the Spread of Endemic Butterfly Cenderawasih Bay using the K-Means Clustering Algorithm

Authors

  • Fegie Y. Wattimena Faculty of Science & Technology, University of Ottow Geissler, Papua, Indonesia
  • Abilliyo S. Mampioper Faculty of Science & Technology, University of Ottow Geissler, Papua, Indonesia
  • Reni Koibur Faculty of Science & Technology, University of Ottow Geissler, Papua, Indonesia
  • I. Nyoman G. A. Astawa Electrical Engineering Major, Bali State Polytechnic, Bali, Indonesia
  • Dony Novaliendry Universitas Negeri Padang, Padang, Indonesia
  • Noper Ardi Department of Informatics Engineering, Politeknik Negeri Batam, Batam, Indonesia
  • Nenny Mahyuddin Universitas Negeri Padang, Padang, Indonesia

DOI:

https://doi.org/10.3991/ijoe.v19i09.40907

Keywords:

Papilionoidea, butterfly, Cendrawasih Bay Island, K-Means Clustering

Abstract


The superfamily Papilionoidea day butterfly, which is endemic to the Cenderawasih Bay islands (Numfor, Supiori, Biak and Yapen), consists of 6 family species: the Papilionidae, Hesperiidae, Pieridae, Riodinidae, Lycaenidae and Nymphalidae families. This study aims to analyze the grouping of endemic butterflies of the Bay of Cendrawasih based on wings and colours in 4 Clusters, namely Numfor, Supiori, Biak and Yapen Islands, by applying the function of the K-Means Clustering algorithm data mining method. The grouping selection was carried out 7 times with the conclusion that Numfor had 13 types of Endemic Butterfly species, Biak had 7 Papuan Endemic Butterfly Species, Supiori had 9 Endemic Butterfly Species, and Yapen had 11 Endemic Butterfly Species. The analysis results were then retested in an application built using the Waterfall system development method and the PHP and MySQL programming languages. In addition to applying the K-Means Clustering algorithm for grouping endemic butterflies, the application created produces a butterfly distribution map that displays butterfly information based on family.

Author Biographies

Fegie Y. Wattimena, Faculty of Science & Technology, University of Ottow Geissler, Papua, Indonesia

 

 

Abilliyo S. Mampioper , Faculty of Science & Technology, University of Ottow Geissler, Papua, Indonesia

 

 

Reni Koibur, Faculty of Science & Technology, University of Ottow Geissler, Papua, Indonesia

 

 

I. Nyoman G. A. Astawa , Electrical Engineering Major, Bali State Polytechnic, Bali, Indonesia

 

 

Dony Novaliendry, Universitas Negeri Padang, Padang, Indonesia

 

 

Noper Ardi, Department of Informatics Engineering, Politeknik Negeri Batam, Batam, Indonesia

 

 

Nenny Mahyuddin, Universitas Negeri Padang, Padang, Indonesia

 

 

Cover iJOE – Vol 19, No 09, 2023

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Published

2023-07-07

How to Cite

Wattimena, F. Y. ., Abilliyo S. Mampioper, Reni Koibur, I. Nyoman G. A. Astawa, Novaliendry, D., Ardi, N., & Mahyuddin, N. (2023). Data Mining Application for the Spread of Endemic Butterfly Cenderawasih Bay using the K-Means Clustering Algorithm. International Journal of Online and Biomedical Engineering (iJOE), 19(09), pp. 108–121. https://doi.org/10.3991/ijoe.v19i09.40907

Issue

Vol. 19 No. 09 (2023)

Section

Papers

License

Copyright (c) 2023 Fegie Y. Wattimena, Abilliyo S. Mampioper , Reni Koibur, I. Nyoman G. A. Astawa , Dony Novaliendry, Noper Ardi, Nenny Mahyuddin

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