Klasifikasi Nilai Kepuasan Masyarakat Terhadap Pelayanan E-KTP Menggunakan Algoritma C4.5 (Studi Kasus : Kantor Kecamatan Rengasdengklok )

  • Amelia Pratiwi Universitas Singaperbangsa Karawang
  • Aries Suharso Universitas Singaperbangsa Karawang
  • Hannie Hannie Universitas Singaperbangsa Karawang
DOI: https://doi.org/10.30871/jaic.v5i2.3264
Keywords: Klasifikasi, E-KTP, Data mining, C4.5

Abstract

The e-KTP service is very important for the community as an identification or identity card for Indonesian citizens. So it is necessary to do this research to find out the value of community satisfaction with e-KTP services, so that later it becomes a reference for e-KTP operators to be even better. Data on the value of community satisfaction At the Rengasdengklok District office, there is a lot of data. This study aims to classify the value of community satisfaction with e-KTP services using. The method used is KDD (Knowledge Discovery in Database) classification by going through the process of data selection, preprocessing, transformation, data mining and evaluation. The algorithm used in this study is the C4.5 algorithm, which is the result of the classification process in the form of rules that can be used to predict the value of the discrete type attribute of a new record. In evaluating the performance of the C4.5 algorithm in the classification of the value of community satisfaction with e-KTP services using Rapidminer tools. Evaluation of the model using kappa. Then it was obtained that the accuracy value was 94.67%. With a kappa value of 0.914% that has been obtained, it falls into the range of values ​​from 0.81 to 1.00, the results of this study have a value of the level of satisfaction with the e-KTP service in the very strong classification category.

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Published
2021-12-16
How to Cite
[1]
A. Pratiwi, A. Suharso, and H. Hannie, “Klasifikasi Nilai Kepuasan Masyarakat Terhadap Pelayanan E-KTP Menggunakan Algoritma C4.5 (Studi Kasus : Kantor Kecamatan Rengasdengklok )”, JAIC, vol. 5, no. 2, pp. 182-189, Dec. 2021.
Issue
Vol 5 No 2 (2021): December 2021
Section
Articles

Copyright (c) 2021 Amelia Pratiwi, Aries Suharso, Hannie Hannie

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