The Prediction Trend of Production in Decision Support System Based on ARIMA-Artificial Intelligence

The Industrial Era 4.0 has seen industries start shifting towards implementing Decision Support System (DSS) in the manufacturing sector.Technological advancements have made it possible for the development of DSS to be based on Artificial Intelligence (AI) using past data generated by industry, especially in the furniture manufacturing industry.The furniture manufacturing industry is now faced with the challenge of Extreme Programming (XP) model complexity that hinders production and inventory management.The manufacturing industry finds it difficult to comprehend which industries to produce based on the current market trends.This research, therefore, seeks to comprehend how an AI-based DSS system can learn furniture model production trends.Based on such problems, this research can potentially assist in designing an AI-based DSS employing the Autoregressive Integrated Moving Average (ARIMA) model from the XP system development paradigm.This research is segmented into five phases, i.e., problem identification, decision model design, data collection and processing, system development and integration, and implementation.The delivery of this research is a list of bestselling furniture fads from market analysis generated through DSS.These findings are useful in the development of DSS, especially in AI to make predictions of furniture model trends.