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Comparison of the Results of the K-Nearest Neighbor (KNN) and Naïve Bayes Methods in the Classification of ISPA Diseases (Case Study: RSUD Fauziah Bireuen)

Riska Yolanda Putri, Zara Yunizar, Safwandi Safwandi

Abstract


Acute Respiratory Infection or commonly called (ARI) is a disease caused by bacteria or viruses. (ARI) can attack all ages, especially children. This study aims to compare the accuracy of classification in (ARI) disease. The data used is data from patients affected by (ARI) disease at Fauziah Bireuen Hospital. K-Nearest Neighbors and Naïve Bayes can be used in the classification of (ARI) diseases. Measurement of accuracy using Confusion Matrix in the K-Nearest Neighbors method with the Eulidean Distance approach in the case of (ARI) disease classification obtained a percentage of precision of 91%, recall 84% and accuracy of 88%. While the Naïve Bayes method obtained a percentage of precision of 95%, recall 78% and accuracy of 86%. The results of the accuracy comparison of the two methods show that the K-Nearest Neighbors method has a higher accuracy rate than the Naïve Bayes method.


Keywords


Classification; K-Nearest Neighbors (KNN); Naïve Bayes; Acute Respiratory Infection (ARI)

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References


Arifin, Z. (2019). Penerapan Metode Knn (K-Nearest Neighbor) Dalam Sistem Pendukung Keputusan Penerimaan Kip (Kartu Indonesia Pintar) Di Desa Pandean Berbasis Web Dan Mysql. NJCA (Nusantara Journal of Computers and Its Applications), 4(1). https://doi.org/10.36564/njca.v4i1.101

Bari, M., Sitorus, S. H., Ristian, U., Rekayasa, J., Komputer, S., Mipa, F., Tanjungpura, U., Prof, J., Hadari, H., & Pontianak, N. (2018). Penyebaran Wabah Penyakit ISPA (Studi Kasus: Wilayah Kota Pontianak). In Jurnal Coding, Sistem Komputer Untan (Vol. 06, Issue 03).

Darnila, E., Maryana, M., & Azmi, M. (2021). Aplikasi Klasifikasi Status Gizi Balita Menggunakan Metode Naïve Bayes Berbasis Android. METHOMIKA Jurnal Manajemen Informatika Dan Komputerisasi Akuntansi, 5(2),135–141. https://doi.org/10.46880/jmika.Vol5No2.pp135-141

Dinata, R.K., Adek, R.T., Hasdyna, N., Retno, S. (2023). K-nearest neighbor classifier optimization using purity. AIP Conference Proceedings. 2431(1).

Hua, W., Xiaofeng, L., Zhenqiang, B., Jun, R., Ban, W., & Liming, L. (2020). Consideration on the strategies during epidemic stage changing from emergency response to continuous prevention and control. Chinese Journal of Endemiology, 41(2), 297–300. https://doi.org/10.3760/cma.j.issn.0254-6450.2020.02.003

Hasdyna, N., Retno, S. (2022). Machine Learning Approach to Determine the Drug-Prone Areas in Lhokseumawe City, Indonesia. International Journal of Multidiciplinary Research and Analysis. 5(9): 2354-2464.

Prayoga Permana, A., Ainiyah, K., & Fahmi Hayati Holle, K. (2021). Analisis Perbandingan Algoritma Decision Tree, kNN, dan Naive Bayes untuk Prediksi Kesuksesan Start-up. In JISKa (Vol. 6, Issue 3). https://www.kaggle.com/manishkc06/startup-success-prediction.

Retno, S., Dinata, R.K., Hasdyna, N. (2023). Evaluasi model data chatbot dalam natural language processing menggunakan k-nearest neighbor. Jurnal CoSciTech (Computer Science and Information Technology. 4(1): 146-153.

Susanti, E., Al-Kautsar Aidilof, H., & Priyanto, D. (2022). Comparison of Naive Bayes and Dempster Shafer Methods in Expert System for Early Diagnosis of COVID-19. Teknik Informatika Dan Rekayasa Komputer, 22(1), 217–230. https://doi.org/10.30812/matrik.v22i1.22

Yanosma, D., Johar T, A., & Anggriani, K. (2016). Implementasi Metode K-Nearest Neighbor (KNN) Dan Simple Addittive Weighting (SAW) Dalam Pengambilan Keputusan Seleksi Penerimaan Anggota Paskibraka (Studi Kasus: Dinas Pemuda Dan Olahraga Provinsi Bengkulu). In Jurnal Rekursif (Vol. 4, Issue 2).




DOI: https://doi.org/10.29103/jacka.v1i1.14535

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