Penerapan Metode Komparasi Probabilitas Penentuan Penyakit Jantung
Abstract
Heart disease, a major global cause of mortality, necessitates a swift and precise diagnostic approach for effective prevention and management. In the era of information technology, probabilistic comparison methods such as Naïve Bayes and KNN offer a fresh perspective on assessing the risk and diagnosis of heart disease. This research, based on a dataset of 300 records with 14 attributes indicating the presence of heart disease, implements and compares these algorithms. The study reveals that Naïve Bayes, with or without normalization, achieves an accuracy of 92.67%, while normalized KNN outperforms with 93.33% accuracy, compared to 79.33% without normalization. Conclusively, the study supports the significant potential of probabilistic data analysis methods, emphasizing the integration of these techniques in the healthcare system for more accurate risk classification, early detection, and efficient management of heart disease.
References
[2] K. Di Penyakit Jantung Koroner Pada Pasien Rsud Prof Dr W Z Johannes Kupang Ice J Johanis, I. A. Tedju Hinga, And A. B. Sir, “Media Kesehatan Masyarakat Faktor Risiko Hipertensi, Merokok Dan Usia Terhadap,” Vol. 2, No. 1, 2020, [Online]. Available: Https://Ejurnal.Undana.Ac.Id/Mkm
[3] M. Saputri And S. R. Dewi, “Potensi Interaksi Polifarmasi Pasien Jantung Koroner (Pjk) Di Rumah Sakit I.A. Moeis Samarinda,” Jurnal Sains Dan Kesehatan, Vol. 5, No. 2, Pp. 109–114, Apr. 2023, Doi: 10.25026/Jsk.V5i2.1709.
[4] A. Ridwanmo, M. Fadillah, Dan Tri Hari Irfani, And B. Ilmu Kesehatan Masyarakat Ilmu Kedokteran Komunitas Fakultas Kedokteran Universitas Sriwijaya, “Deteksi Dini Faktor Risiko Penyakit Jantung Dan Pembuluh Darah, Hubungan Antara Obesitas, Aktivitas Fisik Dan Kolesterol Total Di Kecamatan Kertapati, Kota Palembang.”
[5] H. Sulastomo Et Al., “Edukasi Pencegahan Dan Deteksi Dini Penyakit Kardiovaskular Di Masa Pandemi Covid-19,” 2023.
[6] P. S. Ramadhan, “Penerapan Komparasi Teorema Bayes Dengan Euclidean Probability Dalam Pendiagnosaan Dermatic Bacterial,” Infotekjar (Jurnal Nasional Informatika Dan Teknologi Jaringan), Vol. 4, No. 1, Pp. 1–7, Sep. 2019, Doi: 10.30743/Infotekjar.V4i1.1579.
[7] K. Di Penyakit Jantung Koroner Pada Pasien Rsud Prof Dr W Z Johannes Kupang Ice J Johanis, I. A. Tedju Hinga, And A. B. Sir, “Media Kesehatan Masyarakat Faktor Risiko Hipertensi, Merokok Dan Usia Terhadap,” Vol. 2, No. 1, 2020, [Online]. Available: Https://Ejurnal.Undana.Ac.Id/Mkm
[8] Hasran, “Indonesian Journal Of Data And Science Klasifikasi Penyakit Jantung Menggunakan Metode K-Nearest Neighbor,” Vol. 1, No. 1, Pp. 6–10, 2020, [Online]. Available: Http://Bit.Ly/Datasetcardio.
[9] N. Noviyanto, “Penerapan Data Mining Dalam Mengelompokkan Jumlah Kematian Penderita Covid-19 Berdasarkan Negara Di Benua Asia,” Paradigma - Jurnal Komputer Dan Informatika, Vol. 22, No. 2, 2020, Doi: 10.31294/P.V22i2.8808.
[10] J. Media And A. Issn, “Analisis Algoritma Clustering Dalam Kasus Penentuan Jenis Bunga Iris,” 2017.
[11] R. N. Devita, H. W. Herwanto, And A. P. Wibawa, “Perbandingan Kinerja Metode Naive Bayes Dan K-Nearest Neighbor Untuk Klasifikasi Artikel Berbahasa Indonesia,” Jurnal Teknologi Informasi Dan Ilmu Komputer, Vol. 5, No. 4, Pp. 427–434, Oct. 2018, Doi: 10.25126/Jtiik.201854773.
[12] I. A. Angreni, S. A. Adisasmita, M. I. Ramli, And S. Hamid, “Pengaruh Nilai K Pada Metode K-Nearest Neighbor (Knn) Terhadap Tingkat Akurasi Identifikasi Kerusakan Jalan,” Rekayasa Sipil, Vol. 7, No. 2, P. 63, Jan. 2019, Doi: 10.22441/Jrs.2018.V07.I2.01.
[13] A. Nafalski And A. P. Wibawa, “Machine Translation With Javanese Speech Levels’ Classification,” Informatics, Control, Measurement In Economy And Environment Protection, Vol. 6, No. 1, Pp. 21–25, Feb. 2016, Doi: 10.5604/20830157.1194260.
[14] A. Ashari Muin, “Metode Naive Bayes Untuk Prediksi Kelulusan (Studi Kasus: Data Mahasiswa Baru Perguruan Tinggi),” Jurnal Ilmiah Ilmu Komputer, Vol. 2, No. 1, 2016, [Online]. Available: Http://Ejournal.Fikom-Unasman.Ac.Id
[15] A. A. Wulandari Et Al., “Klasifikasi Data Mining Menggunakan Naïve Bayes Classifier Dengan Algoritma C5.0 (Classification Data Mining Using Naïve Bayes Classifier With C5.0 Algorithm).” [Online]. Available: Https://Magestic.Unej.Ac.Id/
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
