Decision Support System for Determining the Feasibility of Material Utilization Using the Naïve Bayes Method

Abstract

A company is engaged in the mechanical and electrical industry in providing goods and services, especially in medium and high power installations. In this company, the data management process carried out is still semi-computer, on a sheet of paper then copied into a computer with the Microsoft Excel application. Every work done by a technician in using material contains materials that are not used up or used materials. The material is then returned to the warehouse to be used as a report which is then carried out by the utilization process. The purpose of this research is to create a system that can assist in providing suggestions for used or used materials in the warehouse for utilization by applying the Naïve Bayes method. Naïve Bayes is a data mining technique with a classification function. This data mining application methodology uses the KDD (Knowledge Discovery in Database) stage starting from the selecting, preprocessing, transformation, data mining, evaluation stages. The testing technique used for data validation uses the k-fold cross-validation technique accompanied by a Confusion Matrix. This research has produced a decision support system application and has been tested with an accuracy rate of 73.33%.