TY  - JOUR
TI  - Analysis of Agricultural Credit Performance of Turkey using Kmeans Clustering Algorithm
AB  - Agriculture is a significant sector that supplies raw materials to many sectors as well as providing nutrients to humans and animals andensures employment. The economic crises, rapid population growth, the rise in demand for food products have increased importanceand necessity of agriculture. For this reason, agriculture must be supported in order not to be affected by adverse conditions and effects.Thus, agricultural credit is an important factor in the development of the production and investment structure of the agricultural sector.In this study, agricultural credit performance of 81 provinces in Turkey in 2018 was compared by taking into consideration the value oftotal agricultural production, total cultivated area and the amount of agricultural credit used. The data used in this study were collectedfrom the Banking Regulation and Supervision Agency (BRSA) and the Turkish Statistical Institute. In order to determine relationshipsbetween the 81 provinces of Turkey, one of the nonhierarchical clustering method, i.e. the K-means clustering method was applied usingSPSS Clementine data mining software. As a result, the credit performance of provinces was evaluated and similarities and differenceswere revealed using agricultural production value, total cultivated land, agricultural credit volume data.
AU  - SABUNCU, Selin
AU  - CEYLAN, ZEYNEP
DO  - 10.31590/ejosat.638434
PY  - 2019
JO  - Avrupa Bilim ve Teknoloji Dergisi
VL  - 0
IS  - 0
SN  - 2148-2683
SP  - 478
EP  - 484
DB  - TRDizin
UR  - http://search/yayin/detay/358498
ER  -