Application of Decision Tree Models in Artificial Intelligence for Decision Making in Expressing Anger according to Buddhist

Abstract

This research aimed to analyze the concepts of artificial intelligence technology and the Buddhism principles of anger management for applying decision tree models in artificial intelligence to decision-making regarding expressions of anger according to Buddhism principles. The research employed a qualitative documentary research methodology, using sources from the Pali Canon and commentaries.        

The research results were found as follows; Decision trees are a technique within artificial intelligence learning, used to develop machine or computer learning. The result is a model for predicting or forecasting future events, consisting of root nodes, branches, and leaves. Decision tree models in artificial intelligence can be applied to decision-making about expressing anger according to Buddhism principles. This is done by calculating the Information Gain of Entropy to determine the most suitable data set. In this research, the Information Gain values of attributes affecting outcomes—anger expression or forgiveness—were as follows: experience in meditation practice (0.717), product price (0.650), source (0.650), and provider (0.191). It is evident that Buddhism factors are the most influential in deciding whether to express anger or forgiveness. Therefore, there is potential for future use of artificial intelligence (AI) technology in Buddhism education.