Faujatun Hasanah, Tatik Suprapti, Nining Rahaningsih, Irfan Ali
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引用次数: 1

摘要

计算机技术的使用大大帮助了人类在各种数据和信息管理方面的表现。因此,研究人员使用计算机进行分析,可以根据图书馆借书记录的数据预测最喜欢的书。研究人员使用的是数据挖掘。数据挖掘是一个术语,用于描述在数据库中发现知识,使用统计技术,数学,人工智能和机器学习来提取和识别对科学有用的信息。数据挖掘的使用需要一种可以管理图书借阅数据的方法,以便它得到最喜欢的书籍的预测。使用的方法是k -最近邻(KNN)。本研究结果的准确率为98.75%,无兴趣预测为28个数据,无兴趣预测为1个数据,无兴趣预测为0个数据,有兴趣预测为54个数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementasi Algoritma K-Nearest Neighbor dalam Menentukan Buku Berdasarkan Peminatan
The use of computer technology helps a lot in human performance in various data and information management. Therefore, researchers use computers to make analyzes that can predict favorite books based on data from book borrowing records in the library. Researchers use is data mining. Data mining is a term used to describe the discovery of knowledge in databases, using statistical techniques, mathematics, artificial intelligence, and machine learning to extract and identify information that is useful for science. The use of data mining requires a method that can manage book borrowing data so that it gets the predictions of favorite books. The method used is K-Nearest Neighbor (KNN). The results of the accuracy in this study are 98.75%, Prediction of Disinterest with true Not Interest is 28 data, Prediction of Disinterest with true Interest is 1 data, Prediction of Interest with true No Interest is 0 data, Interest Prediction with true Interest is 54 data.
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