APPLICATION OF BAYESIAN NETWORKS: WHY STUDENT PREFER FAST-FOOD, KAMPAR DISTRICT

Abstract

It is common in nowadays where people eat at restaurant rather than cook or prepare meal by themselves. Comparing to home cook meal, eating at restaurant may have been ignoring the hygiene and balance nutrition issue by human for the sake of convenient and time saving. Thus, fast-food has naturally become one of the choices of their preference. We used Bayesian network to identify the factors that influence UTAR Kampar students to have fast-food as their proper meal. Bayesian Networks is one of the probabilistic graphical models and the network must be a directed acyclic graph. The network structure is formed by nodes (random variables) and they are linked by a directed arc corresponding to the causal relationship between them. In this paper, we discovered that the main reason for McD fast-food to be treated as a proper meal mostly in not because of “fast”, i.e., the time saving factor, though it is the inspiration of emerging fast-food restaurants. Besides the unexpected result, the food preference of university students is not easily influenced by friends’ suggestions. Keywords: Bayesian Network, Fast-Food, Structural Network, Directed Acyclic Graph.