The week's pick
Random Articles
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
| 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
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.
References
- Ardilla, Y., Manuhutu, A., Ahmad, N., Hasbi, I., Manuhutu, M. A., Ridwan, M., & Wardhani, A. K. (2021). DATA MINING DAN APLIKASINYA. Penerbit Widina.
- Azmi, B. N., Hermawan, A., & Avianto, D. (2023). Analisis Pengaruh Komposisi Data Training dan Data Testing pada Penggunaan PCA dan Algoritma Decision Tree untuk Klasifikasi Penderita Penyakit Liver. JTIM : Jurnal Teknologi Informasi Dan Multimedia, 4(4), 281–290. https://doi.org/10.35746/jtim.v4i4.298
- Dr. Abdul Kahar, M. P., & Dr. Rahmat Fadhli, E. M. (2021). Beasiswa Pemutus Mata Rantai Kemiskinan. Indonesia Emas Group.
- Mulyani, A., Kurniadi, D., Nashrulloh, M. R., Julianto, I. T., & Regita, M. (2022). The Preduction of PPA and KIP-Kuliah Scholarship Recipients Using Naive Bayes Algorithm. Jurnal Teknik Informatika (JUTIF), 3(4), 821–827.
- Rini, O., & Kunang, S. O. (2021). Implementasi Data Mining Menggunakan Metode Naive Bayes Untuk Penentuan Penerima Bantuan Program Indonesia Pintar ( Pip ) ( Studi Kasus : Sd Negeri 9 Air Kumbang ). Bina Darma Conference on …, 714–722.
- Tempola, F., Rosihan, R., & Adawiyah, R. (2021). Holdout Validation for Comparison Classfication Naïve Bayes and KNN of Recipient Kartu Indonesia Pintar. IOP Conference Series: Materials Science and Engineering, 1125(1), 012041. https://doi.org/10.1088/1757-899x/1125/1/012041
- Utamajaya, J. N., Mentari, A., & Masnunah, S. (2019). Penerapan Algoritma Naive Bayes Untuk Penentuan Calon Penerima Beasiswa PIP Pada SDN 023 Penajam. Jurnal Sistem Informasi, 3(1), 11–17.
- Warella, S. Y., Revida, E., Abdillah, L. A., Pulungan, D. R., Purba, S., Firdaus, E., Tjiptadi, D. D., Faisal, M., Lie, D., & Butarbutar, M. (2021). Penilaian Kinerja Sumber Daya Manusia. Yayasan Kita Menulis.
Index Terms
Keywords