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Reseach Article

Classification of Indonesian Smart Card Scholarship Recipients with Principal Component Analysis using the Naive Bayes and Decision Tree Methods Case Study: Stie Pariwisata API Yogyakarta

by Bowo Hirwono, Suhirman
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 5
Year of Publication: 2024
Authors: Bowo Hirwono, Suhirman
10.5120/ijca2024923375

Bowo Hirwono, Suhirman . Classification of Indonesian Smart Card Scholarship Recipients with Principal Component Analysis using the Naive Bayes and Decision Tree Methods Case Study: Stie Pariwisata API Yogyakarta. International Journal of Computer Applications. 186, 5 ( Jan 2024), 13-21. DOI=10.5120/ijca2024923375

@article{ 10.5120/ijca2024923375,
author = { Bowo Hirwono, Suhirman },
title = { Classification of Indonesian Smart Card Scholarship Recipients with Principal Component Analysis using the Naive Bayes and Decision Tree Methods Case Study: Stie Pariwisata API Yogyakarta },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2024 },
volume = { 186 },
number = { 5 },
month = { Jan },
year = { 2024 },
issn = { 0975-8887 },
pages = { 13-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number5/33068-2024923375/ },
doi = { 10.5120/ijca2024923375 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:29:49.025368+05:30
%A Bowo Hirwono
%A Suhirman
%T Classification of Indonesian Smart Card Scholarship Recipients with Principal Component Analysis using the Naive Bayes and Decision Tree Methods Case Study: Stie Pariwisata API Yogyakarta
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 5
%P 13-21
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research is motivated by the complexity of problems in the selection process for Smart Indonesia Card (KIP) scholarship recipients at STIE Wisata API Yogyakarta. Even though KIP is an important means of increasing access to education for poor families, conventionalmethods of conducting selection cause delays and uncertainty in the validity of the results. In an effort to increase the efficiency and accuracy of selection, this research proposes the application of the Naive Bayes and Decision Tree algorithms. Metode penelitian melibatkan implementasi Algoritma Naive Bayes dan Decision Tree untuk mengklasifikasikan kelayakan penerimaan beasiswa KIP, dengan tambahan penerapan Principal Component Analysis (PCA) guna meningkatkan akurasi hasil klasifikasi. Data penerima beasiswa KIP digunakan sebagai input, memungkinkan penelitian ini untuk menguji dan membandingkan performa kedua Algoritma. Penggunaan PCA sebagai dimensi reduksi diharapkan dapat memberikan kontribusi signifikan terhadap hasil akhir. The research results show that using the Naive Bayes Algorithm with PCA provides the highest accuracy of 85.19%, while Decision Tree with PCA achieves the highest accuracy of 83.33%. The use of PCA is proven to influence significant differences in accuracy in the two algorithms.

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Index Terms

Computer Science
Information Sciences

Keywords

Kartu indonesia pintar scholarship naïve bayes decision tree principal component analysis.