Atatürk Üniversitesi Atatürk Üniversitesi
Ara
Yayınlara dön
Makale Tam Makale Uluslararası 2025

Classification of beekeeping provinces in Türkiye using data mining methods and research into production trends. Technical note

Hakan Serin, Alperen Varalan

Revista Cientifica de la Facultad de Veterinaria Cilt 35 · Sayı 3 · 01.01.2025
DOI ile aç

Özet

Beekeeping holds significant importance both in human nutrition and economically worldwide. The objective of this study is to classify provinces in T & uuml;rkiye based on beekeeping production indicators using K-Means clustering method. Furthermore, by utilizing national data related to production indicators, ascending and descending trends were identified. Five production indicators (number of enterprises, number of colonies, total honey production, beeswax production, and honey yield per colony) from the years 1991 to 2022 were analyzed. For an objective and accurate classification of the provinces, the K-Means clustering method, as a data mining technique, was employed. To identify trends, the Sen Trend and Modified Mann-Kendall test were used. As a result of the K-Means clustering method, a structure with three

Atıf için künye

Serin, H., & Varalan, A. (2025). Classification of beekeeping provinces in Türkiye using data mining methods and research into production trends. Technical note. Revista Cientifica de la Facultad de Veterinaria, 35(3). https://doi.org/10.52973/rcfcv-e35697

BibTeX
@article{serin2025-261439,
  author = {Serin, Hakan and Varalan, Alperen},
  title = {Classification of beekeeping provinces in Türkiye using data mining methods and research into production trends. Technical note},
  journal = {Revista Cientifica de la Facultad de Veterinaria},
  year = {2025},
  volume = {35},
  number = {3},
  issn = {0798-2259},
  doi = {10.52973/rcfcv-e35697},
  url = {https://akademik.atauni.edu.tr/yayinlar/261439-classification-of-beekeeping-provinces-in-turkiye-using-data-mining-methods-and}
}