Classification of Customer Satisfaction with the K-Nearest Neighbor Algorithm in Relation to Employee Performance at PT. Airkon Pratama

PT. Airkon Pratama is the technical consultancy company in the field of maintenance, repair, and operate system. Among its projects are a four-building, multi-story tax office complex. PT. Airkon Pratama experience obstacles to know how its customer satisfaction with their services that is was measured by a questionnaireobtained from work order form. The purpose of this study is to determine how well K-Nearest Neighbor data classification accurately classifies customer satisfaction based on employee performance by PT. Airkon Pratama. The data used in this study is from PT. Airkon Pratama with the data processing using RapidMiner with the K-Nearest Neighbor method which produces an accuracy of 96.53%. Among them four performance indicators were rated as "good", and two as "adequate". Of the 196 that were correctly predicted to be "good," three were "adequate." Most of the 04 respondents gave a positive response indicating their satisfaction with the management of tax office facilities provided by PT. Airkon Pratama in January 2024.

Authors

Publication Details

Journal
International Journal Software Engineering and Computer Science (IJSECS)
Published
2024-12-01
DOI
https://doi.org/10.35870/ijsecs.v4i3.2948
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
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article

Classification of Customer Satisfaction with the K-Nearest Neighbor Algorithm in Relation to Employee Performance at PT. Airkon Pratama

Untung Surapati, Aditya Zakaria Hidayat, Yuma Akbar, Ahmad Suprianto
International Journal Software Engineering and Computer Science (IJSECS)
Customer churn and segmentation
article

Classification of Customer Satisfaction with the K-Nearest Neighbor Algorithm in Relation to Employee Performance at PT. Airkon Pratama

Untung Surapati, Aditya Zakaria Hidayat, Yuma Akbar, Ahmad Suprianto
article en

Abstract

PT. Airkon Pratama is the technical consultancy company in the field of maintenance, repair, and operate system. Among its projects are a four-building, multi-story tax office complex. PT. Airkon Pratama experience obstacles to know how its customer satisfaction with their services that is was measured by a questionnaireobtained from work order form. The purpose of this study is to determine how well K-Nearest Neighbor data classification accurately classifies customer satisfaction based on employee performance by PT. Airkon Pratama. The data used in this study is from PT. Airkon Pratama with the data processing using RapidMiner with the K-Nearest Neighbor method which produces an accuracy of 96.53%. Among them four performance indicators were rated as "good", and two as "adequate". Of the 196 that were correctly predicted to be "good," three were "adequate." Most of the 04 respondents gave a positive response indicating their satisfaction with the management of tax office facilities provided by PT. Airkon Pratama in January 2024.

International Journal Software Engineering and Computer Science (IJSECS)Vol. 4(3)
Openalex Percentile: Top 69%
Customer churn and segmentation
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Classification of Customer Satisfaction with the K-Nearest Neighbor Algorithm in Relation to Employee Performance at PT. Airkon Pratama — Untung Surapati, Aditya Zakaria Hidayat, et al. · International Journal Software Engineering and Computer Science (IJSECS) (2024) | TGRS Research Map | TGRS