Forecasting Raw Material Inventory Using the Single Moving Average and Supplier Selection Using the Analytical Hierarchy Process

التفاصيل البيبلوغرافية
العنوان: Forecasting Raw Material Inventory Using the Single Moving Average and Supplier Selection Using the Analytical Hierarchy Process
المؤلفون: Ardiles Sinaga, Eriana Astuty
المصدر: 2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS).
بيانات النشر: IEEE, 2021.
سنة النشر: 2021
مصطلحات موضوعية: Decision support system, Procurement, Ranking, Computer science, media_common.quotation_subject, Information system, Production (economics), Analytic hierarchy process, ComputerApplications_COMPUTERSINOTHERSYSTEMS, Quality (business), Raw material, Manufacturing engineering, media_common
الوصف: This study aims to help companies to be able to estimate the procurement of raw materials for production, not having stock of raw materials in the warehouse, and determine which suppliers can send goods quickly with affordable prices and good quality. Thus, the company is not optimal in the procurement of raw materials and the selection of appropriate raw material suppliers. In addition, the research aims to optimize the procurement of raw materials that can be used in forecasting in controlling raw materials and decision support systems for the selection of raw material suppliers. The method used to estimate the availability of raw materials is the Simple Moving Average and Analytical Hierarchy Process (AHP) method to determine suppliers. The results of this study indicate that the average percentage of forecast error is 4.17%. Whereas for supplier selection, the AHP method that is used can recommend which suppliers are eligible to be chosen based on predetermined criteria, then the results are sorted by highest ranking. It is expected that the results of this study can be used as a reference for further development, for example by creating information systems that can help companies.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::ff859952c27f3c4a5fedd2eca44eb880
https://doi.org/10.1109/aims52415.2021.9466081
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........ff859952c27f3c4a5fedd2eca44eb880
قاعدة البيانات: OpenAIRE