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Article 2025 · 0 citations

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

Serin, Hakan, Varalan, Alperen

Abstract

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

Keywords
Beekeping classification cluster analysis data EFFICIENCY EXAMPLE TURKEY
WoS Categories
Veterinary Sciences
Sustainable Development Goals
Citation
Journal
REVISTA CIENTIFICA-FACULTAD DE CIENCIAS VETERINARIAS
Year
2025
Volume
35
Issue
3
ISSN
0798-2259
DOI
10.52973/rcfcv-e35697
WoS UID
WOS:001578671000011
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