Journal of Student Research Exploration
Vol. 2 No. 2: July 2024

Application of k-nearest neighbor algorithm in classification of engine performance in car companies using Rapidminer

Lintang, Irendra (Unknown)
Lestari , Apri Dwi (Unknown)
Prasetiyo, Budi (Unknown)



Article Info

Publish Date
08 Jul 2024

Abstract

Implementation of the k-Nearest Neighbor (k-NN) algorithm in the classification of CAR Car company engine performance using RapidMiner software. The company's engine performance is a very important aspect in the automotive industry that greatly affects operational efficiency and customer satisfaction. As an effort to monitor and improve engine performance, classification is an important key to identify machines that are feasible and require repair. The dataset used is a generated dataset from the AI Chat GPT bot whose prompts have been adapted to the research needs. The k-NN algorithm was chosen due to its ability to produce accurate predictions. The k-NN classification method utilizes training and testing data and calculates the distance between the data to determine the appropriate class. The results of this study show excellent performance in terms of accuracy, precision, and recall. The highest accuracy is 90.62% at the value of k = 2. The highest precision and recall are 100% and 93.75% at the values of k = 2, k = 4, and k = 7.

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Journal Info

Abbrev

josre

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

Description

The Journal of Student Research Exploration aim publishes articles concerning the design and implementation of computer engineering, information system, data models, process models, algorithms, and software for information systems. Subject areas include data management, data mining, machine ...