The framework of inventory prediction model using ABC analysis for inventory management / Umi Safierah Masdiki and Rozita Kadar

• Main Authors: Masdiki, Umi Safierah, Kadar, Rozita
• Format: Article
• Language: English
• Published: Unit Penerbitan JSKM 2024
• Subjects: Pulau Pinang; Analysis
• Online Access: https://ir.uitm.edu.my/id/eprint/94493/1/94493.pdf; https://ir.uitm.edu.my/id/eprint/94493/; https://appspenang.uitm.edu.my/sigcs/

In the present day, there exist technologies that aid in forecasting the future. This is particularly beneficial in the business sector, where business intelligence technology is widely utilized for business development. Business analysis is a method that contributes to the advancement of business management. The aim of this study is to assist companies in managing inventory more systematically and effectively. The objective of this study is to propose a prediction model by applying business analysis and visualizing it in the form of a dashboard. Utilizing the CRISP-DM model as a framework, this study applies ABC analysis in the development of the prediction model. The choice of algorithm for this study will be based on selecting the best algorithm for model development proposal. Confusion Matrix is used in evaluating the model. The RapidMiner tool is used to develop the predictive model, while the dashboard is developed using the Power BI tool. The study will evaluate the dashboard by selecting three experts as assessors. Hopefully, this proposed model will enhance inventory management for the company even further.