IMPLEMENTASI METODE WEIGHTED MOVING AVERAGE UNTUK PREDIKSI PENDAPATAN DI IKA LAUNDRY BERBASI WEB - Jaka Pradana , Yuda; Heru Mujianto , Ahmad; Kistofer , Terdy (Inovate, 2024)
This research aims to implement the Weighted Moving Average (WMA) method for income prediction in Ika Laundry's web-based system. The daily income data of Ika Laundry is used as a sample for prediction analysis. The WMA method is applied with predetermined weights to calculate the average forecast. The results of the study demonstrate that the utilization of the WMA method yields more accurate income predictions. Evaluation is conducted using accuracy such as Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and Mean Absolute Deviation (MAD). In the testing period, the MAPE is determined to be 7.51%, MSE is 117,549,222,222.22, and MAD is 279,190.48. By implementing the WMA method, Ika Laundry can effectively and efficiently predict its income. The findings of this research, as indicated by the measured accuracy through MAPE, MSE, and MAD, can serve as a guide for Ika Laundry in making more accurate income-based decisions. Moreover, this study contributes to the development of income prediction methods in the web-based service industry. conclusion, this research demonstrates that the implementation of the Weighted Moving Average (WMA) method for income prediction in Ika Laundry's web-based system results in more accurate predictions. The findings of this study can serve as a guide for Ika Laundry in making better decisions and improving their operational performance. Keywords: Weighted Moving Average (WMA), income prediction, Ika Laundry, prediction accuracy.