Open AccessForecasting the Number of Offset Printing Machine Breakdowns Using the Support Vector Machine (SVM) Metdhod
Author(s) -
Nafis Khumaidah,
Tedjo Sukmono
Publication year - 2021
Publication title -
procedia of engineering and life science
Language(s) - English
Resource type - Journals
ISSN - 2807-2243
DOI - 10.21070/pels.v1i2.1027
Subject(s) - support vector machine , offset (computer science) , computer science , offset printing , process (computing) , artificial intelligence , industrial engineering , machine learning , engineering , inkwell , speech recognition , programming language , operating system
PT. MJT is a company engaged in manufacturing that produces various types of plastic tubes for cosmetic packaging. Production activities at PT. MJT uses an intermittent process, which in the printing division requires a longer total setup time because this process produces various types of specifications of goods to order. This has an effect on the amount of engine breakdown. The purpose of this research is to try the method of forecasting the number of breakdowns for offset printing machines at PT. MJT. One of the methods used in this research is the Support Vector Machine method. Support Vector Machine is a method that can help predict the number of breakdowns that will be experienced by the offset printing machine at PT. MJT. Support vector machine is a method that can reduce the error value in forecasting compared to other methods. From this research, it is hoped that it can produce a forecast of the number of breakdowns for offset printing machines at PT. MJT for a period of one year or twelve periods.