Penerapan Algoritma Naive Bayes Pada Analisa Penyebab Kurang Dan Lebihnya Penggunaan Cutting Tool (Study Kasus Di PT. Sumiden Sintered Component Indonesia (SSI)

Abstract

PT.Sumiden Sintered Component Indonesia (SSI) Is a company engaged in automotive component parts, and this company is also one of a group of companies from Japan namely Sumitomo Corporation in collaboration with local companies Santini Group. PT.SSI was founded in 2012 in the manufacture of component parts with metallurgical technology. Metallurgical technology with this synthesis is a new technology that has existed in Indonesia. PT.SSI has difficulty in processing data using cutting tools which often results in excess and underuse due to inaccurate data. To support this problem, the authors apply the Naive Bayes method to provide a solution in analyzing the problem of the lack and excess use of cuting tools at PT SSI. The data taken in this study is based on data in 2017 and 2018. This research is expected to help SSI companies in analyzing the problem of less and more use of cutting tools. That way, the application of this method is expected to help the user in doing his work. Naive Bayes Method Is a simple probabilistic classification that calculates a set of probabilities by adding up the frequency and combination of given dataset values. The algorithm uses the Bayes theorem and assumes all the attributes are independent or not interdependent given by the value of the class variable. In the above problem, the choice of using the Naive Bayes algorithm is due to the amount of data used in this study. Because the calculation of Naive Bayes algorithm only requires a small amount of training data to estimate parameters.

Keyword : Naive Bayes, Prediction, Cutting Tool.