Sistem Prediksi Jumlah Produksi Baju Menggunakan Weighted Moving Average - Sri Nurhayati; Ahmad Syafiq (Jurnal Manajemen Informatika (JAMIKA), 2022)
Currently, technological advances for information processing are growing very rapidly. This information technology has been used in various fields in everyday life. By using this technology, it is hoped that the work will be faster and more efficient. Due to being able to manage information more quickly and efficiently, it is possible for every company in its work process to use this technology, one of which is the production process. The production process is the process of making or providing use value to an item. This process is one of the important processes because if there is a shortage or excess in the amount of production it will affect sales. Therefore, predictions are needed to estimate the number of products to be produced so that there is no shortage and excess production. In this study, a prediction system will be made where the data used is taken from the Ummajee Store which is a clothing store where the clothes sold are the results of their own production. The method used to determine the prediction of the amount of production using the Weighted Moving Average method, where this method has a different weighting technique for each given data. In this study to calculate the error in predicting the mean absolute percentage error (MAPE), while for the analysis of functional requirements the system uses the Unified Modeling Language (UML). The results of the research, the system has been running as needed and for the use of the method to get an error value of 21% so that the system with the Weighted Moving Average method can be used to predict the amount of production, as well as the system has been running in accordance with the analysis of functional requirements and the results of testing the user response system get the value of 92% which means that the system user states that the system can be used properly so that it can assist in making decisions to determine the amount of clothing production that will be produced in the next period.