PENERAPAN FORECASTING METHODS UNTUK PENJUALAN PRODUK UMKM DENGAN ALGORITMA K-NEAREST NEIGHBOR

Erlin Elisa, Tukino Tukino, Koko Handoko
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Abstract

This research will be carried out on MSMEs in the city of Batam, precisely in the Cipta Asri housing phase II block fir, the analysis is an experiment on sales data so far on MSMEs engaged in the culinary field with the aim of predicting the level of sales in the future. This study will utilize the Forecasting method with the K-Nearest Neighbor datamining algorithm technique to forecast product sales and to test the suitability of the researcher's accuracy using rapidminer software. The results obtained are based on the analysis carried out from 26 training data, there are 20 data that have been classified correctly and 6 data that have not been classified correctly, namely the percentage for Correctly Classified Instances is 77.00% while the percentage for Incorrectly Classified Instances is 23.00%. In conclusion, the results of the analysis can be effective in determining the results of future sales targets and will affect the next level of sales.
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本研究将在巴淡市的中小微企业中进行,确切地说,在Cipta Asri住宅二期街区fir中,分析是迄今为止从事烹饪领域的中小微企业的销售数据的实验,目的是预测未来的销售水平。本研究将利用预测方法与k -最近邻数据挖掘算法技术来预测产品销售,并使用rapidminer软件测试研究人员的准确性的适用性。得到的结果是对26个训练数据进行分析,分类正确的数据有20个,未分类正确的数据有6个,即分类正确的实例百分比为77.00%,分类错误的实例百分比为23.00%。总之,分析的结果可以有效地确定未来销售目标的结果,并将影响下一阶段的销售。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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