K-NEAREST NEIGHBOR ALGORITHM AS A PREDICTION METHOD BEST SELLING ELECTRONIC PRODUCTS

Afrizal Martin(1), Ari Bowo(2), Eviliana Putri Dwifandi(3),


(1) Digital Bunssines of Study Program, Bakti Nusantara Institute, Lampung
(2) Information Systems of Study Program, Bakti Nusantara Institute, Lampung
(3) Information Systems of Study Program, Bakti Nusantara Institute, Lampung
Corresponding Author

Abstract


The use of electric vehicles is now supported by a braking Development increasingly advanced technology rapid bring impact on various sectors, including sector trade. One of the affected sectors impact is trading product electronics. Products electronic be one of the most popular products among the public Because need will increasingly advanced technology increased. MK Store is having trouble in predict sale product electronic best seller, then from That done study optimization planning provision stock product electronics at MK Store with use prediction sale product electronic best seller. With implementing prediction models sale product electronic best seller at MK Store using data mining methods for optimize planning supplies stock product electronics at MK Store with use prediction sale product electronic best seller, and implementing a prediction model sale product electronic best seller at MK Store developed use K-Nearest Neighbor method in provision product electronics. Using The K-Nearest Neighbor algorithm is believed to can give very accurate results with count use distance neighbor nearest , and use variable 10 variables For predicted . Using the Orange tool because can make it easier in operate with use between drag-and-drop face create channel work, data analysis and own diverse widgets components that include data processing, modeling predictive, visualization and analysis text. The result of research conducted use the K-Nearest Neighbor algorithm produces mark with correlation positive (excellent), and the results prediction product electronic best seller at MK Store namely Magicom/Rice Cooker. With existence study This expected for study next, recommended expand range with develop criteria new and considering use method alternative.

Keywords


Data Mining; Prediction; K-Nearest Neighbor; Orange.

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DOI: 10.56327/ijiscs.v8i3.1779

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