Forecasting Brown Sugar Production Using k-NN Minkowski Distance and Z-Score Normalization
نویسندگان
چکیده
The demand for brown sugar products often falls below the level of production, resulting in unsold goods when market surpasses production capacity. This paper addresses challenge faced by many businesses estimating yields. Another issue, apart from uncertainty, is presence a dataset with significant nominal range. study focuses on specific producing company Indonesia. To address estimation problem, this research proposes use k-NN supervised learning as forecasting method. However, instead relying solely k-NN, suggests employing z-score normalization to handle dataset's large data used analysis spans March 2019 February 2022, comprising 144 weekly records. divided into training and testing data, an 8:2 split validation ratio. proposed method consists several steps, including using z-score, processing based Minkowski distance, concluding de-normalization process. results demonstrate successful implementation predicting levels. evaluation indicates average error margin 3.34%, which 5% threshold. predictive proves effective uncertainty addressing
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ژورنال
عنوان ژورنال: Journal of Information Systems and Informatics
سال: 2023
ISSN: ['2656-4882', '2656-5935']
DOI: https://doi.org/10.51519/journalisi.v5i2.485