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All Journal JURSIMA (Jurnal Sistem Informasi dan Manajemen) JURSIMA Jurnal Sistem Informasi dan Manajemen
Nurjana Adi Wijaya
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science Social Sciences

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Journal : JURSIMA (Jurnal Sistem Informasi dan Manajemen)

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IMPLEMENTASI DATA MINING PADA KETEPATAN PENGIRIMAN BARANG DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS Arif Rinaldi Dikananda; Nurjana Adi Wijaya; Mulyawan Mulyawan; Ahmad Faqih
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 3 (2022): Jursima Vol.10 No.3 Desember 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.472

Abstract

Abstract The development of digital technology E-commers is increasing, online shop goods delivery services are needed to support daily needs. The delivery man is in charge of sending goods to customers, with the delivery of goods applications can monitor delays in delivery of goods to customers so as to obtain data on delays in delivery of goods or called Over SLA. However, in processing the data, they still use manuals with Microsoft Excel so that they are lacking in providing more accurate information such as the accuracy of the accuracy of the delivery of goods, grouping of data on delays in the delivery of goods. The method used in this study by utilizing data mining using the K-Nearest Neighbors or KNN algorithm to classify or group data on delays in shipping goods. This method is used in data mining using Rapidminer machine learning applications. This study aims to classify data on delivery of goods and grouping data on timeliness of delivery so that data can be processed properly so as to produce information about the accuracy of delivery of goods by delivery man, to be more effective and faster in presenting data and classifying data. Keywords: Data mining, Classification, K-Nearest Neighbor (KNN).
Co-Authors Ahmad Faqih Arif Rinaldi Dikananda Mulyawan Mulyawan