Data mining of Food Buyers behavior (Case study: Mashhad)

Based on presented information of WHO, high growth rate of non-communicable diseases which is caused by improper lifestyle specially malnutrition and its economic problems, considered as an important obstacle to social development. In this regard present research tries to present decision-making algorithms of customers in the case of selecting between healthiness, price and taste of food as their purchasing priorities, by applying new knowledge of data mining and C4.5 algorithm of decision tree and data of 220 customers. Results show that the factor of customer age is the most important factor influencing on customers behavior in selecting healthiness as the first priority. Other variables in later levels which have influence on selecting healthiness as the first priority are income and education level. Results would help policymakers in adopting suitable and targeted policies in this scope, in order to improve society’s nutrition model and attain healthy society.