Sales forecasting of marketing using adaptive response rate single exponential smoothing algorithm
نویسندگان
چکیده
Micro, small and medium enterprises (UMKM) is one of the important aspects to support improvement economy in Indonesia. Zee Mart’s business UMKM shop Pematang Siantar City with sales purchase transaction activities for supplies. The purpose this study predict Mart store goods coming month using adaptive response rate single exponential smoothing (ARRSES) method. ARRSES a method advantage having two parameters, alpha beta, where will change every period when data pattern changes. dataset obtained be pre-processed through selection, cleaning, transformation. best beta determined based on level accuracy calculated mean absolute percentage error (MAPE). Model development produce forecasting percentages errors each product MAPE. number 23,092 before preprocessing 23,021 after pre-processing, total quantity sold being 149,764 1,492 products. results show lowest MAPE value 9.85 at 0.6 highest 90.15% model implemented into web interface.
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ژورنال
عنوان ژورنال: Indonesian Journal of Electrical Engineering and Computer Science
سال: 2023
ISSN: ['2502-4752', '2502-4760']
DOI: https://doi.org/10.11591/ijeecs.v31.i1.pp423-432