Comparison between ANN and Multiple Linear Regression Models for Prediction of Warranty Cost

Authors

  • Mohd Faaizie Darmawan Soft Computing & Intelligent System (SPINT), Faculty of Computer Systems & Software Engineering, University Malaysia Pahang Lebuhraya Tun Razak, Gambang, 26300, Kuantan, Pahang, Malaysia
  • Nur Izzati Jamahir Soft Computing & Intelligent System (SPINT), Faculty of Computer Systems & Software Engineering, University Malaysia Pahang Lebuhraya Tun Razak, Gambang, 26300, Kuantan, Pahang, Malaysia
  • RD Rohmat Saedudin School of Industrial Engineering, Telkom University, 40257 Bandung, West Java
  • Shahreen Kasim Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia

Abstract

Nowadays, warranty has its own priority in business strategy for a manufacturer to protect their benefit as well as the intense competition between the manufacturers. In fact, warranty is a contract between manufacturer and buyer in which the manufacturer gives the buyer certain assurances as the condition of the property being sold. In industry, an accurate prediction of warranty costs is often counted by the manufacturer. Underestimation or overestimation of the warranty cost may have a high influence to the manufacturers. This paper presents a methodology to adapt historical maintenance warranty data with comparison between Artificial Neural Network (ANN) and multiple linear regression approach.

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Published

25-11-2018

How to Cite

Darmawan, M. F., Jamahir, N. I., Saedudin, R. R., & Kasim, S. (2018). Comparison between ANN and Multiple Linear Regression Models for Prediction of Warranty Cost. International Journal of Integrated Engineering, 10(6). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/2775

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