Application of Classification Algorithm C 4.5 for Predicting Asset Maintenance

Abstract

In asset management, determining maintenance actions is one of the problems faced by the company. The importance of maintenance to accelerate the production or performance of a company is now a necessity that must be run. The problem faced by Astra Daihatsu Motor is the difficulty in determining the maintenance action that must be chosen because of information delays when there are assets that are damaged, failed or failure. With the proposal using a decision tree with C4.5 algorithm can predict failures and damage that occur so that it can determine more accurate maintenance actions. Decision tree is a prediction model using tree structure or hierarchical structure. The concept of a decision tree is to transform data into decision trees and decision rules. The main benefit of using a decision tree is its ability to break down complex decision-making processes to be simpler so that decision makers will better interpret the solution of the problem. Using the decision tree method with the C4.5 algorithm can help the problems faced by Astra Daihatsu Motor in determining maintenance. This is shown from the test results of 98.20%. And it can be concluded that the application of C4.5 algorithm is able to produce asset maintenance patterns with better accuracy.